2025-2026 Projects

Research projects for the College of Science and Mathematics focus on areas like peptide therapeutics, proteomics, and novel chemical compounds. Each project addresses significant society challenges, aiming to develop advanced treatments for various diseases and solutions for ecological concerns. Explore project descriptions, student outcomes, and weekly duties, and see how these research efforts contribute to advancements in health and science.

Return to the Main Projects Page Questions: Email Us

 

Chemistry and Biochemistry (Marina Koether)

Intermolecular Forces Effect on the Kinetics of Dissolution

  • The question that will be answered with this project is 鈥淒oes anion and/or cation size influence the dissolution rate of isomalt, a sugar substitute?鈥�  Preliminary studies using water, 5%, 10%, and 15% sodium chloride solutions have shown that the activation energy increases with increased percent of sodium chloride, NaCl, in the dissolution media. Thus, an increased ion concentration decreases the dissolution rate of isomalt. The NaCl solution introduced ion-dipole interactions that pulled the water molecules to the positive and negative ions that salt contains.  This study will compare the dissolution effects of sodium chloride to sodium bromide and potassium chloride to potassium bromide.  The larger cation and/or the larger anion may influence the dissolution rate. Other comparisons will include cesium chloride, magnesium chloride, calcium chloride, magnesium bromide, calcium bromide, potassium iodide, magnesium iodide, cesium nitrate, potassium nitrate, calcium nitrate and magnesium nitrate solutions.   The pH of the solutions may also be a factor and thus the effect of three different pH values on the dissolution rate will be studied and adjusted by sodium hydroxide or hydrochloric acid. 

    The procedure involves preparing several isomalt 鈥渄rops鈥� and solutions.  Subsequently, the solutions are heated to the desired temperature, and the premade isomalt 鈥渄rop鈥� is dropped into the solution. The stirring process is started, and the drop is removed every 2 minutes for weighing and returned to the solution for further dissolution.  The actual experiment typically takes 10-15 minutes.   This is repeated in triplicate and with three temperatures.  The activation energy can be calculated from the natural logarithm of the slopes of the graphs containing mass versus time, and inverse temperature.  Rather than using mass percent solutions, solutions will be prepared with similar molarities to make better comparisons. 

  • The student will learn to make solutions of correct molarity.  They will use a volumetric flask, a balance and a stir plate to make these solutions.  The student will dissolve isomalt and pour the hot liquid into molds to create identical 鈥渄rops鈥�.  The student will use a dissolution instrument to provide the correct heated temperature and stir rate. The student will write standard operating procedures for the methods employed.  In addition, the student will create waste cards for the hazardous waste containers where they will add their solutions.  Lastly, the student will learn to use Word, Excel and PowerPoint to make the graphs, calculate the activations energies, write a report and present a poster. 
  • Each week, the student will follow all safety protocols. The student will make fresh isomalt drops, prepare the dissolution media, and perform the experiment in triplicate at each temperature for each solution.  Each test solution will be fresh, as the previous solution will be poured into the waste container. The student will record the mass of the salts used, and the mass of each 鈥淒rop鈥� after every 2 minutes in the dissolution tester until the drop disappears. The student will graph the data on Excel for review. The lab area will be cleaned up after each use and the waste card will be created when the waste container is full. 
  • Face-to-Face
  • Dr. Marina Koether, mkoether@kennesaw.edu 

Chemistry and Biochemistry (Mohammad Abdul Halim)

Developing Next Generation Peptide Drugs for Neurodegenerative, Infectious and Cancer Diseases

  • Peptide therapeutics are very attractive over small-molecule medications, as they are highly selective, well-tolerated, and have less adverse effects. Generally, the poor oral bioavailability of peptides requires subcutaneous administration. A short half-life poses additional challenges for their formulation and clinical utility. Despite these obstacles, the current rate of approval by the FDA for peptide drugs is twice as fast as for small molecules. Worldwide, 88 peptide drugs are approved, and 170 peptides are currently being evaluated in clinical trials. Peptide stapling, a cyclization technique, is a widely used approach to develop staple peptides. However, the traditional hydrocarbon and triazole/disulfide stapling methods produced low yield and required catalyst separation. Hence, a novel high yielding stapling method is required.

    Our long-term goal is to design, synthesize and evaluate the efficacy of novel pi-pi staple and potentially orally active peptide targeting the various proteins related to Neurodegenerative, Infectious and Cancer Diseases. This project has following two specific aims:

    Aim 1.  To develop potent staple peptide mimetics: A pool of novel pi-pi staple analogues will be designed and optimized targeting amyloid beta, alpha synuclein in Alzheimer and Parkinson diseases, main protease of SARS-CoV-2 and Rhinovirus in infectious diseases, and MDM2 (Double Minute 2 Protein) in cancer disease. Computer aided design and solid phase peptide synthesis protocol will be employed. 

    Aim 2. To evaluate inhibition efficiency, metabolism and stability. To assess the inhibition efficiency, various essays including FRET and LCMS will be conducted. In-vitro metabolic and stability assays will be performed improving half-life, and oral bioavailability.

    The expected outcome of this project is to develop the next generation of peptide drug to treat dementia, infectious and cancer diseases and advance our knowledge of how these peptides can be further improved.

  • This research training will help students to learn basic biochemistry, peptide synthesis, molecular modeling, mass spectrometry-based assay and gain experiences on performing interdisciplinary research, collecting, and analyzing experimental and computational data, interpreting, and presenting results, presenting in conference, writing, and publishing manuscripts.

    These diverse research experiences in peptide synthesis, molecular modeling and peptide characterization by liquid chromatography and mass spectrometry, and biological assays will help students to pursue their PhD on biomedical science, obtain their degree in MD/PhD or secure position in CDC, FDA, and pharmaceutical/biochemical industry.

  • Student will do various tasks in the different phase of the projects including:

    i) assignments,

    ii) reading and reviewing scientific articles,

    iii) performing computer aided peptide design,

    iv) synthesizing and characterizing peptides,

    v) acquiring and interpreting mass spectrometry-based inhibition and metabolic assays, and

    vi) drafting poster, presentation, and manuscript.

  • Hybrid
  • Dr. Mohammad Abdul Halim, mhalim1@kennesaw.edu 

Chemistry and Biochemistry (Progyateg Chakma)

Photo-Responsive Solid-State Reactions Through Crystalline Peptoid Assemblies

  • Organic nanomaterials are highly desirable because of their high stability, robustness, morphological diversity, and high crystallinity. In the field of crystal engineering, there are significant aspects, as tunable molecular arrangements in organic nanomaterials allow for the modulation of intra- and intermolecular interactions, leading to advanced materials with tailored functionalities.  In particular, the formation of covalent bonds via solid-state reactions offers unique advantages, including enhanced reactivity and regional and stereospecificity, which might be difficult to access through conventional organic synthetic methods. However, the primary challenge in performing a solid-state reaction is to properly align the reactive molecules in a specific orientation with a proximal distance, which is challenging to realize and control. We aim to utilize the assembly of sequence-defined peptoids into highly crystalline nanomaterials to address this challenge. 

    Polypeptoids are a novel class of synthetic polymers that share a similar backbone structure with polypeptides, but with the side chain attached to the nitrogen atom instead of the 伪-carbon. This subtle modification enhances flexibility, resistance to proteolysis, and stability, while maintaining biocompatibility and ordered folding behavior akin to that of polypeptides. Polypeptoids serve as a link between biological polymers and synthetic polymers, providing opportunities to create sequence-programmable, folded polymers with the durability of synthetic materials, leading to different applications such as antimicrobial agents, diagnostic agents, drug delivery, and bio-separation. 

    Interestingly, amphiphilic peptoids can be self-assembled into highly crystalline nanosheets, nanoribbons, and nanotubes with a backbone-to-backbone distance of 4.5 脜 along the x direction. This is very significant, as per Schmidt鈥檚 rule, as for efficient solid-state 2+2 photodimerization, the distance between the carbon-carbon double bonds should be approximately 4.2 脜. Based on this principle, we aim to design a series of amphiphilic peptoids functionalized with photo-responsive molecules, which can self-assemble into highly crystalline nanomaterials and initiate highly efficient 2+2 solid-state photodimerization. Peptoids will be synthesized using a highly efficient solid-phase synthesis methodology, purified by preparative high-performance liquid chromatography (HPLC), and characterized by liquid chromatography-tandem mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. The self-assembly of the purified peptoids will be performed using a facile slow evaporation method, and characterization will be carried out using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Finally, 2+2 photodimerization will be performed using a photoreactor, and efficiency will be characterized by NMR and UV-Vis spectroscopy. The long-term goal of this project is to develop dynamic materials with applications in catalysis. 

  • Students involved in this program will gain hands-on interdisciplinary research experience in basic organic synthesis, peptoid synthesis, and materials chemistry.  In addition to performing research, students will gain expertise in data collection and analysis, scientific writing, and public presentations at conferences and symposiums. They will be trained in instruments such as liquid chromatography, mass spectrometry, NMR spectroscopy, UV-Vis spectroscopy, and electron microscopy, which will be highly beneficial for them to pursue advanced degrees, such as Master's or PhDs, in materials science, biochemistry, polymer chemistry, chemical engineering, and biomedical science. Additionally, expertise in these methodologies and characterization techniques will be vital in securing industrial positions in fields such as pharmaceuticals, biomedical, and adhesive industries. 
  • Students will be involved in various duties weekly in different stages of the project, including 鈥� 1) reading and reviewing of scientific literature, 2) take part in group meetings, 3) synthesis and characterization of peptoids, 4) self-assembly of peptoids into nanomaterials and their characterization, 5) proper data collection and critical analysis, 6) drafting of posters, involvement in manuscript writing, and giving presentations. 
  • Face-to-Face
  • Dr. Progyateg Chakma, pchakma@kennesaw.edu 

Chemistry and Biochemistry (Tyler Adams)

Creating and Testing Color Changing Organic Molecules

  • This project will focus on making several color changing small molecules and testing their coloration and fluorescence. After proving successful creation, the new molecules will be blended with polymers to create thin plastic sheets. Upon exposure to light, we expect to see a color change of the material. This can be later used for applications like self-tinting windows, drug detection devices, and sensors. More specifically, we will use two and three step synthesis to make thiophene bridged extended viologens. These compounds are water soluble and able to gain two electrons, causing the color change. Because of this reversible gain and loss of electrons, the molecules will also be studied for redox flow battery applications. We will be synthesizing several different molecules, adding and changing different pieces to change the electronic properties and ultimately the colors of the molecules we make. 
  • Students that join the project will develop keen skills with multistep organic synthesis, including refluxing, oxygen-free synthesis, gravity filtration, vacuum filtration, and vacuum drying. They will also become skilled with instrumentation like Nuclear Magnetic Resonance (NMR) spectroscopy, UV-Vis spectroscopy, and fluorescence spectroscopy. Students will also become proficient with MS Excel and MS PowerPoint. In addition, students will build soft skills like working in a team and giving presentations. Although this seems like a lot, we will work on it together over time. 
  • Students will participate in the research lab, creating and testing new molecules. This includes hands-on organic synthesis and purification, using instrumentation, and looking at data in excel. Students will be expected to add their weekly progress to PowerPoint slides so they can present at weekly group meetings or have short one-on-one meetings with Dr. Adams. Students will also be encouraged to read scholarly articles relevant to the research.
  • Face-to-Face
  • Dr. Tyler Adams, tadam145@kennesaw.edu 

Chemistry and Biochemistry (Daniela Tapu)

Breaking Bonds, Building New Catalysts: An Integrated Mechanochemical Approach to NHC-based Transition Metal Complexes

  • The Department of Energy鈥檚 Vision 2020 report highlights the development of advanced catalysts as a critical scientific challenge. Catalysts鈥攕ubstances that accelerate chemical reactions without being consumed鈥攁re central to green and sustainable chemistry. Catalysts drive green and sustainable chemistry by speeding reactions without being consumed, enabling the production of medicines, plastics, fertilizers, fuels, and more. This project will explore a novel approach of producing transition metal-based catalysts through mechanochemical methods. Mechanochemistry offers solvent-free or solvent-minimized alternatives to traditional reactions, reducing environmental impact while often enhancing reaction efficiency, selectivity, and scalability. This project will help students understand modern green chemistry principles and expose them to cutting-edge research techniques. The student(s) will prepare new N-heterocyclic carbenes and their corresponding transition metals complexes and explore their function in catalysis.  

    The specific goals of the project are three-fold:
    1) Synthesis and characterization of novel carbene ligands
    2) Synthesis and characterization of the corresponding transition metal complexes via mechanochemistry
    3) Investigation of the catalytic activity of these new complexes in several model reactions

  • By participating in this project, the students will get an intensive immersion in the practice of science, including the foundation of scientific knowledge, experimental design, data handling and collaboration. They will learn to critically read manuscripts, to prepare reports and poster presentations, to keep records and to plan strategy. They could become coauthors on publications. Upon graduation, the students will be equipped with the fundamental knowledge and problem-solving skills needed for a successful career in chemistry. This research experience will significantly enhance their competitiveness for admission in graduate schools or potential employment, as most graduate school and companies place great value on such experience.
  • The students will receive in the beginning training with our standard techniques and instrumentation (NMR, UV-Vis, IR, glovebox/Schlenk-line operation, chromatography etc.). Each student will be actively involved in the preparation and characterization of the proposed targets. They will attempt improvements in product yields and product purification. Each student will initiate his/her own exploratory experiments and will keep an accurate and complete experimental
    record of laboratory data. The students will participate in group meetings (online or in person, as the situation allows) where discussions about experimental design, problems, concepts and interpretations will take place. The students will be involved in writing and editing the manuscripts and preparation of their poster/oral presentations.
  • Face-to-Face
  • Dr. Daniela Tapu, dtapu@kennesaw.edu 

Chemistry & Biochemistry (Kai Shen)

Development of Bone DNA Extraction Methods for Forensic DNA Typing in Missing Person Casework

  • DNA profiling is one of the most powerful tools available for human identification, especially in forensic science. It is commonly used in solving criminal cases, disaster victim identification, and helping families of missing persons through kinship analysis. However, obtaining high-quality DNA from hard tissues such as bones remains a significant challenge. Bones often contain very little usable DNA, and the DNA that can be extracted is often degraded or contaminated by the mineral matrix, mainly calcium, that makes bones so rigid.

    Current DNA extraction methods frequently produce DNA of low yield and poor quality. This limits the ability to create accurate DNA profiles, which are essential for matching individuals to relatives or confirming identity. To address this problem, our project focuses on developing a more efficient method for extracting DNA from bone samples.

    Our approach combines different strategies to first remove the calcium-rich bone matrix, which can interfere with DNA recovery, and then improve the extraction of DNA that is preserved within the bone tissue. By doing so, we expect to increase both the amount and quality of DNA obtained. High-quality DNA is critical for downstream applications such as DNA typing and kinship analysis, which rely on clear, reliable genetic information.

    This research project is designed for first-year students to gain hands-on experience in real-world problem solving within forensic science. Students will learn about the principles of DNA extraction, the challenges posed by hard tissue samples, and the importance of method development in advancing forensic capabilities. Beyond the technical aspects, they will also gain an appreciation for how scientific research can have direct social impact鈥攈elping bring closure to families of missing persons and strengthening the reliability of forensic evidence in the justice system.

    In summary, this project aims to advance forensic science by improving DNA extraction from bones, making DNA profiling more accurate and effective for human identification.

  • This project will provide first-year undergraduates with authentic research experience in forensic DNA analysis. Students will gain hands-on laboratory skills in DNA extraction, quantification, and profiling while learning to critically evaluate and optimize methods for bone DNA recovery. Through this process, they will strengthen their problem-solving and data interpretation abilities.

    The project also emphasizes communication and professional growth. Students will prepare reports, present findings at research conferences, gaining experience in explaining science to diverse audiences. By addressing a problem with societal relevance, students will see the impact of their work while preparing for careers or graduate study in chemistry, biochemistry and related fields.

    • Literature Review: Read and summarize assigned articles to connect weekly lab work to current forensic research.
    • Laboratory Work: Perform DNA extraction experiments on bone samples, test modified protocols, and assess DNA yield and quality.
    • Documentation: Maintain detailed lab notebooks with procedures, results, and troubleshooting notes.
    • Data Analysis: Compare outcomes across methods to refine protocols.
    • Mentorship Meetings: Meet with faculty mentor to review progress, challenges, and next steps. (face-to-face or virtual via Teams)
  • Hybrid
  • Dr. Kai Shen, kshen@kennesaw.edu 

Chemistry & Biochemistry (Lu Kang & Sudiksha Khadka)

Design of a Cubic Shape Helmholtz Coil to Balance the Geomagnetic Field in 3 Dimensions

  • The geomagnetic field, i.e., Earth's magnetic field, is a magnetic field that surrounds the Earth due to the movement of molten iron in the Earth's outer core. With a field strength of 0.25 - 0.65 Gauss, it is strong enough to deflect the trajectories of charged particles in the plasma beam. For example, aurora, the brilliant light ribbons weaving across Earth's polar regions, is the result of an interaction between corona mass ejection (solar wind with charged particles) and Earth's magnetosphere. 

    My research on the study of microwave spectroscopy uses a Fourier transform microwave (FTMW) spectrometer to measure the rotational spectra transitions of exotic species, e.g., free radicals and ions, in the supersonic beam expansion of plasma created by a discharge nozzle. Since the moving charges can be affected by geomagnetic fields due to the Lorentz force, collisions of those particles ruin the spectral resolution at the increased collision line width. To avoid this, I intend to build a 3-D Helmholtz coil to annihilate the geomagnetic fields inside the spectrometer.  A classical design of the Helmholtz coil is made by wrapping enameled copper wires on a ring. Each dimension needs two such coils to balance the geomagnetic field. Thus, six copper wire looped rings are necessary to build a 3-D Helmholtz coil. However, such a design is not applicable to my instrument because the vacuum chamber is a cylinder with a 21-inch diameter. To put it inside the 3-D Helmholtz coil, an even larger ring, say, 25-inch diameter, is necessary. It is not cost effective to build 6 rings like that size. I plan to use commercial strut beams such as the 80/20 T-slot extrusion to make a cubic shape to accommodate the vacuum chamber. Their integrated 鈥渟lots鈥� on the extrusion bars are perfect spots to wrap the enameled copper wires. The downside is that geometric complexity of a cage gives us a challenge to figure out the magnetic field distributions inside the cage. Fortunately, Calculus and Biot-Savart Law will help us solve this problem. 

    With the drilling press and band saw in my lab, a 3-D Helmholtz coil can be built with additional materials and devices of T-slot bars, power supplies, enameled copper wires, etc. A Gauss meter will be used to measure and map the geomagnetic field distributions, which helps us tune the electric current strengths to balance the geomagnetic fields. 

  • At the end of this proposed research, students should be able to:

    • Explain how their research activities contribute to the research project.
    • Learn and understand the terminology associated with the research topics.
    • Develop the capability to construct a simple model to explain the experimental results. 
    • Develop necessary data analysis skills.
    • Use quantitative method to evaluate data collections and/or experimental results.
    • Search and track useful information from journal articles and their citations.
    • Develop necessary work ethics as a team member in a small research group.
    • Acquire knowledge and polish skills that are necessary to support STEM research, e.g., MATLAB, SolidWorks, etc.
    • Improve time-management, self-control, analytical thinking, and problem-solving skills.
    • Group meeting with faculty member and/or senior research students for guidance/direction
    • Teamwork with peer students to create new ideas for the machinery design of the Helmholtz coil cage
    • Literature search and information analysis
    • Theoretical calculations 鈥� Biot-Savart Law  
    • Use SolidWorks as the mechanical graphic design tools to create the 3D graph of the Helmholtz coil 
    • Machinery work to build the Helmholtz coil
    • Build the electric circuits to control the electric currents
    • Measure and adjust the artificial magnetic fields generated by the Helmholtz coil 
  • Face-to-Face

  • Dr. Lu Kang, lkang1@kennesaw.edu 

    Dr. Sudiksha Khadka, skhadka2@kennesaw.edu 

Ecology, Evolution, and Organismal Biology (Justin Varholick)

Uncovering What Regenerates When Skin Nerves Are Injured in Highly Regenerative Animals

  • Our skin is filled with sensory nerves, allowing us to text, type, love, eat, play sports, etc. Traumatic injuries to the skin, like burns or surgeries, can permanently damage these skin nerves. This damage leads to lifelong dysfunction in sensation, chronic pain, numbness, etc. Interestingly, some animals have an amazing capacity to regenerate their skin nerves. But, how and to what degree they can regenerate remains mostly understudied. The goal in our research lab is to understand how we can optimize and improve the recovery of skin nerves after injury. The goal of this project is to survey multiple highly regenerative animals (e.g., Spiny mice, neonatal rodents, and salamanders) and determine to what degree do their skin nerves regenerate, or are restored. This will involve using preserved skin samples from uninjured and healed skin, and cutting thin sections to examine the structural properties of the nerves under the microscope. Students will learn technical skills like histology, microscopy, and using imaging software like QuPath or ImageJ. They will also learn how to think critically about the quality of healing across evolution, and how to make structural comparisons at the microscopic level. Once this project is completed, students will have opportunity to advance within the lab as we begin to manipulate molecular, cellular, and environmental properties of the animal to affect the quality of nerve restoration.  

  • Students participating in this project will acquire a diverse set of technical and analytical skills, central to research in biology. They will gain hands-on experience in histology, including preparing and sectioning tissue samples, staining, and mounting slides for microscopic analysis. They will also learn to operate light and likely fluorescent microscopes to examine the structural properties of the skin nerves, and will be trained to use imaging software like QuPath or ImageJ to capture, quantify, and analyze microscopic data. 

    Beyond technical skills, students will develop critical thinking abilities by evaluating the quality of nerve regeneration across different animal models and drawing meaningful comparisons between uninjured and healed skin. They will practice designing experiments, formulating research questions, and interpreting results in the context of evolution and regenerative medicine.

    Throughout the project, students will strengthen their scientific communication skills by discussing findings with lab members, contributing to lab meetings, and preparing presentations for a symposium. They will also learn the value of teamwork and collaboration in a research setting. By the end of the program, students will have a strong foundation in laboratory techniques, data analysis, and scientific inquiry, preparing them for future research opportunities in biology and related fields.

  • Each week, students will engage in a variety of hands-on and collaborative activities designed to build their research skills and deepen their understanding of nerve regeneration. Typical weekly duties will include preparing and sectioning tissue samples for histological analysis, staining and mounting slides, and using microscopes to examine nerve structures in both uninjured and regenerated skin. Students will capture and analyze images using specialized software such as QuPath or ImageJ, learning how to quantify and interpret biological data.

    In addition to laboratory work, students will participate in weekly lab meetings where they discuss research progress, troubleshoot experiments, and review relevant scientific literature as a group. They will be encouraged to ask questions, share observations, and contribute ideas for experimental design and data interpretation. Students may also assist with maintaining lab records, organizing materials, and ensuring that data is accurately recorded and stored.

    As the project progresses, students will work collaboratively to prepare figures and presentations, practicing how to communicate their findings to both scientific and general audiences. Throughout the semester, students will have the opportunity to develop time management and teamwork skills while gaining exposure to the broader scientific process. By engaging in these weekly activities, students will experience the full cycle of research, from hands-on experimentation to data analysis and presentation.

  • Face-to-Face
  • Dr. Justin Varholick, jvarhol2@kennesaw.edu 

Ecology, Evolution, and Organismal Biology (Tiago Pereira)

Assessing Soil Microeukaryotic Biodiversity Using Environmental DNA Approaches

  • Soils harbor significant global biodiversity, particularly among microorganisms that provide essential ecosystem services such as soil fertility, stability, and nutrient cycling, all of which contribute to human well-being. Despite this, the biodiversity of soil microeukaryotes remains largely unexplored due to the demanding taxonomical expertise and time-consuming nature of traditional methods. Molecular approaches have become the standard for biodiversity and ecological surveys in both terrestrial and aquatic environments. For example, environmental DNA (eDNA) metabarcoding allows for the rapid and cost-effective recovery of entire biological communities. In this project, students will investigate a molecular dataset (DNA sequences) from soil samples collected in semi-arid habitats of Southern California. The primary goal is to assess the diversity of microeukaryotic organisms鈥攕uch as fungi, nematodes, and tardigrades鈥攁cross various habitats and soil types. Additionally, students will compare two methods of community DNA extraction from soil to explore biodiversity patterns.
    1. Students will gain critical bioinformatics skills to analyze big data, focusing on quality control of molecular data (e.g., DNA sequences) using a High-Performance Computing Cluster (HPCC). The PI will secure student access to the KSU-HPCC throughout the project, teaching them to connect and run tasks remotely using bash language skills.
    2. Students will explore various software packages through RStudio to conduct statistical and ecological analyses, enhancing their basic statistical skills and refining their abilities in plotting and data visualization.
    3. Students will learn wet lab techniques essential for eDNA metabarcoding, including DNA extraction, PCR, and DNA quantification, while adhering to best practices in laboratory settings.
    4. A thorough understanding of eDNA metabarcoding and other molecular methods used in biodiversity and ecological studies will be developed, with an emphasis on their application in scenarios like biomonitoring.
    5. Students will cultivate a deep appreciation for science and the scientific method.
    6. Finally, students will produce relevant findings to present at various events.
    1. Meet regularly with the PI (5 to 10 hours per week).
    2. Demonstrate progress on tasks previously assigned by the PI (e.g., create a specific plot).
    3. Read relevant literature to enhance learning. While most reading will be assigned by the PI, students are encouraged to search for additional relevant papers.
    4. Participate in Q&A sessions with the PI and colleagues to clarify key concepts related to the project.
    5. Present results to the PI and colleagues for feedback opportunities.
  • Face-to-Face
  • Dr. Tiago Pereira, tpereir6@kennesaw.edu 

Mathematics (Eric Stachura)

Analysis of Differential Equations on Fractals

  • Fractals are geometric shapes that have a certain detailed structure at small scales, and many fractals appear similar at each scale. Many familiar objects have fractal features, such as frost crystals, DNA, neurons, and trees. The mathematics of fractals can be tricky because these objects are 鈥渘on-smooth鈥�, so classical mathematical techniques and ideas do not immediately apply. 

    In this project, students will study a fractal version of a well-known equation which arises often in physics and engineering: the Helmholtz equation. In optics, this classical equation corresponds to the wave equation for the electric field. In the fractal setting, things get trickier, and differential equations like this need to be understood in a 鈥渨eak鈥� sense, since the usual notion of derivative may not be well-defined. 

    Both theory and numerical implementation will be involved throughout the project. The first part of the project will be devoted to determining solutions to a one-dimensional fractal Helmholtz equation. The second part of this project will be a numerical implementation to determine approximate eigenvalues and eigenfunctions. 

    • Students will learn basic Mathematica programming language and how to simulate and visualize solutions to differential equations
    • Students will visualize their simulations in the Immersive Visualization Environment (IVE) research cluster鈥攁 dome shape display with a 5-meter diameter, 210-degree horizontal field of view which is housed within the Coles College of Business.
    • Students will have a deeper understanding of the mathematics of fractals and determine properties of solutions to differential equations in this framework.

    The tools that students will learn during the project will be useful beyond the research itself and will help prepare them for scientific careers beyond KSU. Students will also be encouraged to continue their research with the PI in the 2026-2027 academic year. They will be coauthors on any resulting manuscripts. 

    • Students will devote 5-10 hours per week to this project.
    • Students will read assigned literature and complete all the assignments from the supervisor.
    • Students will also learn basic Mathematica programming and complete all related assignments.
    • Students will meet the supervisor once a week and make a 15-minute presentation with a weekly progress report. 
  • Face-to-Face
  • Dr. Eric Stachura, estachur@kennesaw.edu 

Mathematics (Min Wang & Zhu Cao)

Machine Learning in Theme Parks: Making Your Visit Better

  • Machine learning (ML) has emerged as one of the most active and transformative fields in the past decade, with proven success across science, engineering, and industry. This project explores how ML can be applied to enhance the visitor experience in theme parks, focusing on overall enjoyment, operational efficiency, and safety.

    Using real-world data collected from various theme parks in USA, we will (1) identify patterns in visitor behavior, and (2) develop predictive models using state-of-the-art ML techniques to improve park operations and guest satisfaction. Our approach combines data analysis with advanced mathematical modeling to create actionable insights for smoother visitor flow, reduced wait times, and more personalized park experiences.

    Potential applications include dynamic ride scheduling, real-time adjustments to staffing and resource allocation, and monitoring for unusual crowd patterns to support safety operations. By integrating insights from movement, occupancy, and activity levels, the models can help parks respond promptly to changing conditions without disrupting the guest experience.

    The novelty of this project lies in two aspects:

    1. Innovative use of existing data sources to gain deeper insights into visitor flow, waiting times, and crowd distribution.
    2. Development of advanced, data-driven models that integrate ML techniques with rigorous mathematical derivations to optimize both operational efficiency and the overall guest experience.

    The student researcher will actively participate in two major components of the project:

    • Data Analysis and Aggregation -- cleaning, processing, and visualizing raw data to identify meaningful patterns.
    • ML Model Development -- applying modern algorithms to build predictive models for visitor behavior, operational planning, and related applications.

    Through this work, the student will gain:

    • A practical understanding of the mathematical foundations of ML.
    • Hands-on skills in data analytics, programming, and mathematical modeling.
    • Experience in applying theory to real-world, interdisciplinary problems鈥攕kills that are highly valuable in the data science industry.

    Ultimately, this project seeks to demonstrate how emerging ML methods can supplement existing operational systems in theme parks. By making rides more efficient, lines shorter, and environments more responsive to visitor needs, we aim to provide a framework that can 鈥渕ake your visit better鈥� while contributing to advances in intelligent, data-driven park management.

    • Develop hands-on Python programming skills on data analytics and machine learning.
    • Develop the ability to implement mathematical formula/flowchart/pseudo code with Python.
    • Develop the independent study ability leveraging various resources, e.g. KSU library, online databases, online tutorials, etc.
    • Develop skills on public presentation and technical writing.
    • An oral or poster presentation based on the project outcomes will be given by the first-year student researcher.
    • Attend weekly project meetings and give 10-minute presentations on the progress made in the previous week.
    • Complete the tasks assigned in weekly project meetings, e.g. literature search, reference review, data processing and analysis, model implementation with Python, etc.
    • Write weekly progress reports and prepare presentation slides for the upcoming weekly project meeting.
    • The students are encouraged to attend appropriate scholarly activities, e.g. Applied Mathematics in Industry Seminar, Analysis and Applied Math Seminar, KSU R Day, etc.
  • Hybrid

  • Dr. Min Wang, mwang23@kennesaw.edu 

    Dr. Zhu Cao, zcao@kennesaw.edu 

Mathematics (Md Masud Rana)

Using Math and AI to Explore Drug Discovery

  • How do medicines actually work in the body? At the most basic level, a medicine (a small molecule, or 鈥渓igand鈥�) works by attaching itself to a protein in our body. Whether a medicine is effective often depends on how strongly it binds to that protein. Scientists call this 鈥渂inding affinity鈥�. Discovering which molecules bind well to a target protein is at the heart of drug discovery鈥攂ut testing every possible combination in the lab is slow, expensive, and sometimes impossible.

    Our project uses mathematical tools and artificial intelligence (AI) to speed up this process. We build computer models that can learn from thousands of known protein鈥搇igand pairs and then predict how strongly a new molecule might bind. To do this, we translate the structure of a protein鈥搇igand complex into a form the computer can understand. Instead of looking at them as static shapes, we represent them as networks (graphs), where atoms are 鈥渄ots鈥� and their connections are 鈥渓ines鈥�. These networks capture both the geometry (the 3D structure) and the chemistry (the types of interactions).

    By training deep learning models on these graph-based representations, we aim to uncover patterns that determine binding strength. If successful, this approach could help scientists more quickly identify promising drug candidates, reduce the cost of drug discovery, and open doors to new treatments.

    Students who join this project will not need prior coding or chemistry experience鈥擨 will provide the training. You will gain experience working with real biological data, learn how to use AI tools for scientific research, and contribute to a project at the intersection of mathematics, computer science, and biology.

  • Students participating in this project will gain hands-on experience at the intersection of artificial intelligence, biology, and applied mathematics. By working on a real-world problem, students will learn both technical and transferable skills that will serve them in a wide range of disciplines.

    On the technical side, students will be introduced to the basics of protein and ligand structures, why binding affinity matters, and how computational tools can be used to study these interactions. They will learn how to represent biological systems as networks (graphs) and use this representation to analyze molecular interactions. Students will also gain experience with data preparation, visualization, and analysis. For those interested in computation, I will provide guided training in basic programming concepts, enabling students to work with artificial intelligence models in a structured, beginner-friendly environment.

    In addition to technical training, students will develop key skills essential to scientific research. These include critical thinking, problem-solving, and attention to detail when working with data. They will practice communicating their findings clearly鈥攂oth in group discussions and in short presentations or written reports鈥攂uilding confidence in scientific communication. Students will also gain experience collaborating in a research team, learning how to contribute to ongoing projects while developing independence and initiative.

    Overall, students will leave this project with a stronger foundation in computational and biological sciences, practical research experience, and skills that extend beyond the laboratory or classroom. By participating in an active research program, they will also gain insight into the process of discovery and a sense of belonging in the scientific community.

  • Each week, students will participate in structured activities designed to gradually build their knowledge and skills while contributing to the research project. Weekly duties will balance learning new concepts, practicing technical skills, and engaging in collaborative research.

    Students will begin with guided reading and discussion sessions to build a foundational understanding of proteins, ligands, and why binding affinity matters in drug discovery. They will also be introduced to the idea of representing molecules as graphs (networks), with in-class exercises to reinforce these concepts.

    A portion of each week will focus on hands-on computational work. Students will work with datasets of protein鈥搇igand complexes, learning how to clean, organize, and visualize data. They will gradually be introduced to basic programming tasks in a structured, step-by-step way. These may include running simple scripts, modifying parameters, or recording results from experiments with artificial intelligence models.

    Weekly group meetings will give students opportunities to present short updates on their progress, share challenges, and receive feedback. Students will also engage in group problem-solving activities, learning to brainstorm next steps and contribute ideas. Mentorship sessions will be included to check on individual progress and ensure students are supported in their learning.

    By the later weeks, students will begin interpreting their computational results and discussing their scientific meaning with the team. They will prepare short written reflections or slides summarizing their findings and practice presenting them to their peers.

    Overall, weekly duties will provide students with a balance of structured instruction, independent practice, and collaborative teamwork鈥攅nsuring that each student actively engages in research while developing confidence and skills as a budding scholar.

  • Hybrid
  • Dr. Md Masud Rana, mrana10@kennesaw.edu 

Mathematics (Emanuel Indrei)

Almgren's Problem and the Polya-Szego Conjecture

  • The undergraduate researcher(s) will work on one of the two problems mentioned below.

    1. The Almgren problem appears in classical thermodynamics when one seeks to understand whether minimizing the free energy with a potential in the class of sets of finite perimeter under a mass constraint generates a convex minimizer representing a crystal assuming solely that the sub-level sets of the a priori fixed potential are convex. Historically, this is one of the most complex problems and one of the most important problems in physics. The physical principle connecting minimizers to crystals was independently discovered by Gibbs in 1878 and Curie in 1885. Only a handful of convexity results exist for all masses, even in two dimensions. The PI recently solved the problem in dimensions 1 and 2:

    Indrei, E. The one-dimensional equilibrium shape of a crystal. arXiv 2025, arXiv:2501.07900.

    Indrei, E. On the equilibrium shape of a crystal. Calc. Var. Partial. Differ. Equ. 2024, 63, 97.

    and made significant progress, co-authored with A. Karakhanyan at University of Edinburgh, when considering three-dimensions:

    Indrei, E.; Karakhanyan, A. On the Three-Dimensional Shape of a Crystal. Mathematics 2025, 13, 614.

     

    In the summer, Science Featured published a popular article on this progress:

    3D Mystery Hidden in Crystal Structures

     

    The undergraduate project will consider the minimization problem on a computer and code examples to illuminate the properties of optimizers. 

     

    2. The Polya-Szego conjecture involves the principal frequency of a domain, which is the frequency of the gravest proper tone of a uniform and uniformly stretched elastic membrane in equilibrium and fixed along the boundary. 

    Polya proved: (i) of all triangular membranes with a given area, the equilateral triangle has the lowest principal frequency; (ii) of all quadrilaterals with a given area, the square has the smallest principal frequency. In a recent paper, the PI explicitly constructed spaces of polygons having n sides for all large n such that the principal frequency with a fixed area constraint is minimized by the convex regular n-gon: 

    Indrei, E. On the first eigenvalue of the Laplacian for polygons

    J. Math. Phys. 2024, 65, 041506.

     

    Analogously to Almgren鈥檚 problem, the Polya-Szego conjecture investigates a minimization problem. This problem originates via the theory of sound instead of thermodynamics. In his article, the PI utilized a partial symmetrization. In particular, one may consider an evolution of polygons. The undergraduate project will investigate this evolution via an algorithm on MATLAB. 

  • The benefits related to this research activity will include a potential publication by the undergraduate in a refereed journal, plans to present the research to a broader audience, and a contribution by the undergraduate to a complicated research area via computer simulations. Thus, this facilitates a set of skills via analysis, inquiry, and teamwork, to conduct high quality scientific research.

    Ideally, the goal is to report all the results in a professional peer reviewed publication, but independently of achieving a publication, students can present progress at various undergraduate conferences. In addition, an undergraduate researcher would be serving as a role model to other undergraduates regarding how early one can get involved in mathematics research, thus expanding undergraduate research at KSU.

  • Undergraduate researchers will initially study the material needed from undergraduate mathematics courses (e.g. Vector Calculus) and grasp the important initial mathematical elements for coding. Then, researchers will learn how to work with computer programs, e.g. MATLAB, and code the algorithm for investigating several examples of optimizers in the problems mentioned in the project description. It is not necessary for undergraduates to have already taken Vector Calculus, however, a good understanding of Calculus I is helpful. During the semester, we will meet regularly (i.e. once per week or more) to make advances. The output of participating in the project for the remaining time involves data collection, scientific writing, and research presentations. 
  • Hybrid
  • Dr. Emanuel Indrei, eindrei@kennesaw.edu 

Molecular and Cellular Biology (Joanna Wardwell-Ozgo)

Sizing Up the Nucleus: Do Hormones Alter Nuclear Size?

  • Some tissues can copy their DNA without dividing their cellular content. These cells end up with mega-nuclei that have up to 400 times the amount of DNA compared to a tissue that can also divide its cellular content.  Our lab has collected data suggesting steroid hormones might alter the ability of cells to bulk up their nuclear DNA content.

    The student working on this project will gain experience in image analysis, microscopy, genetics, fly husbandry, and bioinformatics as they investigate whether hormones can change the size of a mega-nucleus.

  • Students will have the opportunity to gain fly husbandry skills. They will also develop a strong understanding of genetics through this project.

    Specific technical skills includes image analysis and bioinformatics.

  • Students will be expected to attend lab meetings and analyze their data. Students will need to spend around 10 hours in the lab to do so. 
  • Face-to-Face
  • Dr. Joanna Wardwell-Ozgo, jwardwel@kennesaw.edu 

Molecular and Cellular Biology (Chris Cornelison)

A Circular Economic Approach to Specialty Mushroom Cultivation

  • Specialty mushrooms are considered gourmet food items, nutraceuticals, and attributed with medicinal qualities. Many can grow on cellulosic biomass. This research project focuses on evaluating regional agricultural and industrial byproducts as substrates for specialty mushroom cultivation as well as novel cultivation methods that reduce single use plastics.

    Cumulatively, this project aims to develop novel substrates and approaches to mushroom cultivation that facilitate a more profitable and sustainable model for the production of a highly nutritious food supply and potential source of medicinal compounds.

  • Students will learn to work in a BSL-2 laboratory, general microbiological and chemistry skills, the cultivation of mushrooms including culture maintenance, spawn production, substrate production, substrate colonization, and mushroom fruiting.

    Students will learn about data collection and analysis as well as the development and drafting of posters, presentations, and figures related to their research. The students will be immersed in a culture of team science and learn to thrive in an interdisciplinary and innovative research environment.

  • Routine laboratory activities (3-6 hours), data collection (2 hours), 1 hour weekly lab meeting (1 hour).

    Specific duties vary based on the stage of the project and ongoing reserach objectives.

  • Face-to-Face
  • Dr. Chris Cornelison, ccornel5@kennesaw.edu

Molecular and Cellular Biology (Soon Goo Lee)

Structure-Guided Protein Engineering to Generate New Versions of Natural Sweeteners

  • Problem. The growing diabetes epidemic affected more than 30 million Americans in 2017; with a staggering economic cost of $327 billion in the United States alone. Among the many risk factors, studies have shown that excessive consumption of sugars is the main cause of type 2 diabetes and is implicated in many medical problems such as cardiovascular disease, obesity, and even some cancers.

    Rationale. Sweeteners derived from plant natural products have significant potential as dietary supplements because they are stable and non-caloric. More importantly, natural sweeteners could help patients who are diabetic, phenylketonuric (inability to break down an amino acid called phenylalanine), and/or obese reduce their sugar intake. Stevia is a natural high-intensity sweetener isolated from leaves of Stevia rebaudiana, a tender perennial herb native to semitropical regions of South America (e.g., Paraguay and Brazil). The leaves of this plant contain more than ten ent-kaurene diterpenoid glycosides composed of a steviol aglycone decorated with different numbers and types of sugars. Commercially available steviol glucosides have the characteristic bitter aftertaste of specific types of steviol glucosides, thus preventing widespread commercial use. The identification of new, natural, and low/non-calorie sweeteners and research of their biosynthetic pathways are essential to addressing numerous health issues.

    Goals & Activities. The research objective is to manipulate the pattern of glycosylation and to improve the yield of desirable stevia compounds using 3D structure-guided protein engineering and mutagenesis techniques. The First-Year Scholars Program will support our biochemical experiments to understand how Stevia plants form various natural products and to alter essential enzymes in Stevia to generate new versions of noncaloric sweeteners by employing structure-guided protein engineering techniques.

  • The First-Year Scholars Program will offer the potential for re-engineered pathways in Stevia to produce tailored variants of commercially viable noncaloric sweeteners. Once the First-Year Scholars Program research team obtains the 3D structural information, we can look ahead to expanding our atomic-level insights to possible applications. If the research project is successful, the First-Year Scholars Program-sponsored students will learn how to produce new versions of the noncaloric sweetener by altering the branched-chain glycosylation patterns and how to construct the Stevia biosynthesis pathway with improved yields of desirable steviol compounds. The First-Year Scholars Program students鈥� experimental results will be measured and analyzed, and their work will be published in peer-reviewed chemical and biological research journals. In the long run, the First-Year Scholars Program team will be able to acquire intellectual property rights for 3D structures of newly engineered Stevia UGT enzymes and functional studies. 
  • Students in the First-Year Scholars Program will carry out their own research project, Biochemical and Structural Characterization of UDP-glycosyltransferases (UGTs)in the Stevia Biosynthetic Pathway. As an independent researcher, each student will be responsible for performing the proposed molecular biology and biochemical experiments. Undergraduate students will also team up with a graduate student to conduct protein expression, purification, and crystallography experiments.
  • Face-to-Face
  • Dr. Soon Goo Lee, slee295@kennesaw.edu 

Molecular and Cellular Biology (Andrew Haddow)

Investigating the Role Environmental Stressors have on Mosquito Development

  • Anthropogenic changes to the environment and globalization continue to drive arbovirus emergence and reemergence, resulting in spillover events. These events often initiate new zoonotic transboundary transmission cycles between vector species and amplification hosts. However, the mechanisms underlying arbovirus maintenance, emergence, and spillover into human populations are poorly understood.

    My laboratory uses a multi-pronged approach that includes a combination of field and laboratory-based methods to identify and characterize emerging arboviruses (e.g., Zika, West Nile, and La Crosse viruses), determine the prevalence of virus infection in arthropods, vertebrate hosts and humans; investigate arbovirus vector infection and pathogenesis; investigate select aspects of vector biology in the context of mosquito development and fitness; and identify risk factors for acquiring arbovirus infection. The results of our investigations are used to inform mitigation strategies to help prevent the spillover of arboviruses into human populations and protect vulnerable populations from disease.

  • 1) Define the terminology associated with research and theory in their field
    2) Describe past research studies in their field of study
    3) Articulate how their research study makes a contribution to their academic field
    4) Locate primary and secondary sources related to their field of study
    5) Develop a hypothesis
    6) Collect data for a research study
    7) Analyze, synthesize, organize, and interpret data from their research study
    8) Work effectively as part of a team
    9) Present their research/creative activity to an audience (e.g., poster, oral presentation, performance, display)
    10) Develop time management
    11) Develop self-confidence/self-esteem
    12) Develop independent thinking
    13) Develop problem-solving
    14) Develop organizational skills
    15) Develop leadership skills
  • 1) Complete KSU safety training needed to conduct laboratory activities, including but not limited to General Lab Safety, Compressed Cylinder Safety, and Biological Hazards and Autoclave Safety
    2) Aid graduate students in areas of their research projects, including literature searches, experimental design, data collection, and data analysis
    3) Conduct individual research projects to present at KSU symposiums
    4) Maintain colonies of mosquitoes by providing sucrose to adult mosquitoes, blood-feeding female mosquitoes, collecting and storing mosquito eggs, hatching eggs, and rearing larvae to adults
    5) Conduct occasional field work to collect wild adult and larval mosquitoes
    6) Identify wild-caught mosquitoes to genus and species
    7) Pin wild-caught mosquitoes for future use
    8) Assistance with the maintenance and cleaning of laboratory facilities
    9) Attend laboratory meetings
  • Face-to-Face
  • Dr. Andrew Haddow, ahaddow@kennesaw.edu 

Molecular and Cellular Biology (Scott Nowak)

What Can a Fruit Fly Tell Us About Your Heart? Apparently, Quite a Lot.

  • The heart is one of the earliest organs to form in metazoans.  Formation of the heart involves a number of genes, genetic pathways, and cellular mechanisms that all have to work together to build the finished heart.  Congenital cardiac defects, diagnosed at birth, are the most highly prevalent birth defects in the human population, yet the identities of the genes, genetic pathways, and cellular mechanisms that govern this process in mammals remain poorly studied.  Fortunately, the genetics of heart formation is highly conserved among animal species, enabling us to use the fruit fly, Drosophila melanogaster, as a model system to study heart development.  The Nowak Lab has identified a number of these genetic pathways involved in heart formation.  We will use a variety of techniques, from forward genetics to high-resolution imaging, to study heart formation and development in Drosophila.  This work will then inform future studies aimed at looking at heart formation in mammals.
  • The student will use a variety of techniques that are routinely used in the Nowak Laboratory.  These include insect husbandry, immunohistochemistry, conventional light and confocal microscopy techniques, molecular biology, and possibly some biochemistry techniques.  Additionally, students will learn scientific presentation skills and learn the proper way to present and disseminate the results of their research.
  • The student will participate in lab meetings with the Nowak lab.  Drosophila genetic crossing will require daily visits to the lab (less than an hour in most cases) during the week, as well as some more time-intensive techniques, all of which can be easily adapted to a student鈥檚 schedule.
  • Face-to-Face
  • Dr. Scott Nowak, snowak@kennesaw.edu 

Molecular and Cellular Biology (Masafumi Yoshinaga)

Search for Novel Arsenic-Containing Antibiotics

  • Arsenic is one of the most persistent and ubiquitous environmental toxins. To overcome this problematic element, life has evolved and acquired a number of arsenic detoxifying mechanisms. Bacteria, due to the immense environmental adaptability and biochemical versatility, have even flexibly devised various ways to utilize arsenic for biological functions such as energy production, osmotic adjustment, phosphate sparing, etc. Our recent studies indicate a new way of bacterial arsenic utilization 鈥� offensive weapons. Notably, bacteria wage 鈥渁rsenic warfare鈥�, where some members weaponize environmental arsenic, synthesizing arsenic-containing antibiotics to kill neighboring competitors, while others develop countermeasures against the arsenic weapons. This new emerging 鈥渂acterial arsenic warfare鈥� concept provides a new dimension to understanding the arsenic biogeochemical cycle and brings new perspective to environmental arsenic biochemistry, as well as leads to discovery and development of new and potent antimicrobials.

    In this project, students will explore novel arsenic-containing antibiotics using 1) prospective bacterial strains that possess novel gene(s) involved in arsenic metabolism/transformation, 2) a genetically manipulatable bacterial strain (Escherichia coli) engineered with the novel gene(s), and/or 3) purified protein(s) encoded by the novel gene(s). The expected outcomes are identification and characterization of 1) novel arsenic-containing antibiotics, and/or 2) novel genes/proteins that carry out novel arsenic biotransformation.

    The dramatic increase in bacterial resistance to antibiotics is a grave threat to global health. A dearth of new antibiotics has fostered the emergence and spread of drug-resistant bacteria, resulting in an increase of serious infections with high mortality rates. To overcome this serious health concern, discovery and development of new antibiotics are urgently needed. The future and long-term goal of this project is to demonstrate the potentials of arsenic-containing antibiotics to establish a new pipeline for our shrinking antibiotic arsenal.

  • Students will learn various lab techniques in microbiology, molecular biology, biochemistry and analytical chemistry from basics, such as pipetting skills, buffer/media preparation, transformation, to advanced, including western blot, column chromathography and the state-of-the-art research instrumentation such as inductively-coupled plasma mass spectrometry (ICP-MS, arsenic detection), high performance liquid chromatography (HPLC)-coupled with ICP-MS (HPLC-ICP-MS, arsenic speciation), etc.

    During the program, each student will be assigned to work under the supervision of one of the graduate students in the PI's lab, who has been working on the above-mentioned project. The new first-year students will first shadow their supervisor, gradually learn knowledge and skills required for the project, and eventually start conducting experiments to generate data for the project. 

  • Students' weekly duties include, but not limited to, learning and complying with laboratory rules and work ethics, mastering basic lab skills, performing experiments, reading scientific papers/books related to their projects, collaboratively working with other students in the lab, maintaining a laboratory notebook as a record of their research, maintaining lab space and equipment, participating in biweekly laboratory meetings (where students will present their project results or share research articles that they are assigned to read).
  • Face-to-Face
  • Dr. Masafumi Yoshinaga, myoshina@kennesaw.edu 

Physics (Andreas Papaefstathiou)

Particle Physics on a Raspberry Pi: Machine Learning in Action

  • Machine learning and artificial intelligence have become central tools in particle physics research. At the CERN Large Hadron Collider (LHC), these methods are widely used to interpret the vast and complex data produced by particle collisions. In this project, we will build a Raspberry Pi computer equipped with an AI Kit and use it to design analyses that apply machine learning techniques to explore the rich structure of LHC data.

  • Students in this project will learn to:

    • Build and configure a computer from scratch using Raspberry Pi hardware.
    • Operate within the Linux environment, including installing and managing essential software.
    • Grasp the fundamentals of particle collider physics and how data is generated at the LHC.
    • Understand and apply the core principles of machine learning to scientific data analysis.

  • Each week, students will meet with the faculty mentor to talk about progress, ask questions, and plan next steps. Between meetings, they will spend time reading short materials to learn the basics of particle physics, scientific computing, and machine learning.

    Weekly work will include building and using the Raspberry Pi computer, practicing with the Linux operating system, and installing software. Students will also try out simple coding tasks, run small simulations, and explore how machine learning can be used to study physics data.

    In the beginning, the focus will be on learning the tools and concepts. Later, students will use what they鈥檝e learned to test basic machine learning models on real physics problems. Each week combines hands-on practice with guidance, making the project both fun and educational.

  • Face-to-Face
  • Dr. Andreas Papaefstathiou, apapaefs@kennesaw.edu 

Physics (Kiran Prasai)

Computer Simulations of Advanced Optical Coatings for Gravitational-Wave Detectors

  • Gravitational-wave (GW) detectors, such as LIGO and Virgo, which led to the Nobel Prize-winning discovery of gravitational waves in 2015, require ultra-high-precision optical coatings. Developing increasingly precise optical coatings will enable scientists to detect signals from ever greater distances in the universe. This project will involve students in aspects of the computational research that underpins the development of ultra-high-precision mirror coatings for future gravitational-wave detectors. In particular, students will perform atomic simulations of selected optical coating materials and analyze their suitability for next-generation gravitational-wave detectors.

  • At the end of the project, students will learn the following:

    • some aspects of physics research
    • basic coding in python, including data input/output and basic computation
    • data analysis, graphing and visualization
    • skills in presenting scientific results as poster and/or talk
  • The student researcher will meet with the PI mentor at least once a week. During these meetings, the mentor will discuss the assignment and provide guidance on completing it. The student will then work independently on the project using a provided Mac workstation. The student and mentor will review the outcomes of the assignment in the following week鈥檚 meeting, and the cycle will continue. Students are encouraged to reach out if they need additional guidance in completing the assignment.
  • Face-to-Face
  • Dr. Kiran Prasai, kprasai@kennesaw.edu