College of Science and Mathematics 2020-2021 Projects

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  • 2020-2021 First-Year Scholar: Avery Moss, biochemistry

    2020-2021 First-Year Scholar: Sarah Fashinasi, biochemistry

    • Expression and purification of the SARS-CoV2 protein Orf8 for structure determination

      As part of this work, the student will produce a protein derived from the virus responsible for COVID-19. This protein material will then be analyzed in collaboration with the mentor and his graduate students to determine the three dimensional structure and function. This assignment of function may assist our understanding of this virus and how it causes disease.

    • The student will become familar with general laboratory techniques, such as preparing solutions and maintaining a sterile work environment. They will become proficient with microbiological and chemical methods required to express and purify a protein. As part of frequent laboratory presentations, they will hone their ability to explain their scientific experiments to their colleagues and non-scientists.

    • Prepare solutions. Grow lab-strains of bacteria engineered to produce the protein of interest. Harvest the protein via centrifugation and other chemical methods.

  • 2020-2021 First-Year Scholar: Chakayla Ashford, biology

    • Determining Genetic Conditions That Lead to Cancer Transformation

      Cancer is a disease of uncontrolled cell proliferation that receives intensive research but still poses lots of questions. For example, cell transformation in cancer involves multiple genetic mutations, but we don’t know which combinations are deadly and which are benign. To answer this question, we use fruit flies, Drosophila. By tinkering with Drosophila genome, we experimentally induce cancer in the fly gut to determine which mutations contribute to cancer aggressiveness. Help is needed with data collection and analysis. The participating student(s) will receive training in Drosophila husbandry, fluorescence microscopy and other useful lab techniques. We seek enthusiastic and highly motivated individuals, preferably majoring in Biology.

    •  Students will learn the following knowledge and skills: 

      • Fly husbandry and genetics
      • Microdissection
      • Working with binoculars
      • Fluorescence microscopy
      • Fluorescence imaging
      • Preparation and processing of frozen sections
      • Immunostaining
      • Preparing buffers and solutions
      • Discuss the research plan with the professor.
      • Perform experimental activities (such as setting up genetic crosses, obtaining samples, staining samples, making slide preparations, taking microimages, etc.) with minimum supervision, help with general lab routine by making solutions, fly food, passaging genetic fly lines.
      • The schedule is flexible, but not less than 5 hrs/week is expected.
  • 2020-2021 First-Year Scholar: Elohor Okoko, biology

    • Micro- and nano- plastic detection by SERS method

      In the present context, the microplastic problem is no longer a marine problem. Instead, it expanded to freshwater and terrestrial environment. Although microplastic or nanoplastic waste is a huge societal issue, there are no well-defined best practices for its identification in an aqueous environment. Baruah research laboratory has expertized in designing nanoparticle-based composite materials to detect molecules at sub-micromolar concentrations using Surface-Enhanced Raman Scattering (SERS) technique.

      In this work, Baruah laboratory will develop fiber-based nanocomposite materials containing metal-organic framework (MOF) and metal (gold and silver) nanoparticles. The clean cotton fabric (CF) will be modified with polydopamine (PDA) in the presence of Tris-HCl buffer to form cotton@PDA (Li et al., 2018). Cotton@PDA will be solvothermally treated with 2-aminoterephthalic acid, and ZrCl4 in N,N-dimethylformamide (DMF) to create immobilized UiO-66-NH2 (U6N) MOF (Bunge et al., 2018). Above created Cotton@PDA@U6N composite will be further treated with NaAuCl4 or AgNO3 in the presence of ascorbic acid to create Cotton@PDA@U6N-MNP (MNP = metal nanoparticles = AuNP or AgNP) (Baruah, 2016). Scheme 1 demonstrates the fabrication process.

      Polymethylmethacrylate (PMMA), polyethylene (PE), and polystyrene (PS) micro and nano plastic will be created using a rotary tool and will be detected using Cotton@PDA@U6N-MNP composite material with SERS techniques (Wright et al., 2019). This method will be further extended to detect mico- and nanoplastics in various environmental samples. Fabricated nanocomposite materials will be characterized utilizing in-house and external facilities (Georgia Institute of Technology and Emory University)

    •  The student will learn:

      • Hands-on nanocomposite material synthesis and fabrication
      • Spectroscopic characterization of nanocomposite materials
      • Electron microscopic imaging experience
      • Scientific data processing and chemical structure drawing experience
      • Scientific writing, preparation of presentation and communication skills
      • Laboratory safety and waste management  
    • Depending upon the day and progress of the project, a student in the Baruah laboratory will do the following:

      • literature search
      • wet synthesis
      • fabrication of composite
      • characterization of nanomaterials using spectroscopic techniques
      • electron microscopic imaging
      • data collection
      • data processing
      • waste management
      • etc.
  • 2020-2021 First-Year Scholar: Isabel Ouko, mathematics

    • Environmental Impact on Decision Making in Ecological Communities

      Evolutionary game theory (EGT) is a mathematical framework through which we can study decision making in ecological communities. As the name suggests, EGT borrows ideas at the heart of game theory, which can be very generally defined as the study of decision making in competitive situations. By considering interactions between individuals occupying the same ecological niche as games, we can utilize the extensive toolset offered by classical game theory to understand when these individuals should cooperate or when they should "defect" as the terminology goes. Researchers have made great strides over the past 50 years both expanding the mathematical understanding of EGT, and applying it to study a wide range of biological systems, from bacterial communities to social vertebrates to cancer cells.

      This project will focus on a recent branch of EGT that couples game theoretic decision making with a simple model of the surrounding environment. These so-called "ecol-evolutionary" models allow us to study environmental impact on ecological interactions, and helps address important questions related to environmental uncertainty due to climate change, over-harvesting or overgrazing, or simply environmental effects of the seasons. Students will help develop mathematical models, study systems of differential equations both analytically and using computer software (MATLAB), and possibly study simple stochastic systems (if interested!).

    • In addition to learning to read scientific literature (and eventually write it), students will learn how to:

      • develop mathematical models
      • analyze systems of differential equations
      • interpret mathematical results in the context of a real-world problem
      • study simple stochastic systems (if interested!)
    • I expect students to spend time working on the current state of the project (model development, analysis, writing, etc). We will have weekly meetings to touch base, discuss results, and determine next steps of the project. Work on this project can be done remotely and will not require any special software or machinery,

  • 2020-2021 First-Year Scholar: Ayomikun Akin-David, biology

    • In our own image:  Do images of endangered apes with humans, and human artifacts, negatively impact perception regarding their conservation status?

      This project will seek to identify if images of Great Apes in "human" contexts impact perceptions regarding their conservation status.  All four nonhuman Great Ape species, bonobos, chimpanzees, gorillas, and orangutans, are endangered in the wild.  Their greatest threat is human activity - habitat destruction and fragmentation, poaching, and the illegal pet trade.  Zoological gardens and animal sanctuaries outside range countries aim to promote conservation of Great Apes by supporting in situ conservation projects as well as by raising awareness through public outreach.  However, a major challenge faced by those interested in endangered species conservation is inspiring people to care.  Social media platforms provide these organizations with a fast and effective method for disseminating information to a large number of individuals.  Photographs and videos of Great Apes are used to promote awareness of the species.  However, recent evidence suggests that the context of these images may have a significant impact on these conservation efforts.  Specifically, research has shown that viewing nonhuman primates alongside humans, or with human artifacts, actually leads viewers to believe that the animals are not endangered  and even make good pets.  This is particularly unfortunate, given that organizations often depict Great Apes in these contexts to promote engagement with the content on social media - after all, who can resist images of a baby chimpanzee taking a bath, or an orangutan brushing her teeth.

      This project aims to determine if people’s perceptions of the conservation status of Great Apes are influenced by the images of Great Apes that they see. This question is of critical importance as conservation organizations seek to expand their audience through social media platforms amidst an increasingly dire need for conservation efforts.

    • Students participating in this program will assist with all aspects of the study including experimental design and setup, preparation of study materials, participant enrollment, data cataloguing, data analysis, and presentation of the results. Skills and techniques students will learn include web-based survey design and interface, image processing and preparation, as well as statistical design and analyses.  In addition, students will gain knowledge in Great Ape behavior and ecology.

    • This project will be completed online/virtually.  Students will be required to attend weekly virtual lab meetings, prepare stimuli, manage participant enrollment, collect and catalogue data, and assist with data analysis and preparing the results of publication.

  • 2020-2021 First-Year Scholar: Genevieve Doxakis, biology

    • How to make a brain in three easy steps

      The Hudson lab at Kennesaw State University is broadly interested in: (1) understanding how cells in the body become neurons; and (2) how neurons connect to one another to make neural circuits and how those circuits control an animal's behavior. To do this, we primarily use the nematode Caenorhabditis elegans as a model for these studies. Nematode worms have many advantages for studying the nervous system. First, they have an invariant cell lineage, which means that whenever a cell divides, we know exactly what its daughter cells are going to be. Second, they're see-through, which means that we can actually see neuronal cell bodies and axon bundles without having to dissect the animals. Third, we can use fluorescent reporter genes to label individual cells in the worm's brain. Finally, we can use genetics to change the underlying genes required for nervous system development and function. By creating mutations that change the fate of a neuron or the shape of an axon, we can figure out which genes are required for making the nervous system and how that affects behavior. Is this relevant to humans and human neurological disorders? Oh yes! The genes required for shaping the worm's nervous system are the same genes required to shape the human nervous system. As such, we can look at the worm version of human disease genes and understand what the consequences are for mutating that particular gene and how it affects nervous system development and function. We have two main projects on-going in the lab. The first one is to examine a class of proteins called transcription factors to figure out how they affect whether a cell becomes a neuron or something else. Second, we are examining how sensory neural circuits connect together, and whether defects in nervous system connectivity lead to behavioral defects.

    • A first-year student joining the lab would work with a master's student and contribute to one or more of the projects described above. Having learned how to handle worms, they'd use those worm-picking skills and basic genetics to build worm strains, examining those strains using a fluorescence microscope, then imaging those strains and looking for nervous system defects. As an adjunct to this, they would learn additional transferrable skills including polymerase chain reaction assays, automated image analysis coding and strain freezing. Students will maintain a lab notebook and be trained in how to archive data on cloud-based servers and other back-up devices. They will present their data in weekly lab meetings, culminating with a poster presentation at the KSU Student Research Symposium. If schedules permit, they will also be invited to attend weekly research seminars in the College of Science and Mathematics, and monthly Worm Club (12 noon, third Monday of the month at Emory University), where they can see research presentations from other worm-based labs in the Atlanta metro area including labs at Emory University, Georgia Tech, and Georgia State. Students making exceptional progress will be encouraged to present their data at the regional Society for Developmental Biology meeting. 

    • In addition to the research approach described above, a first-year student would be expected to contribute to lab maintenance by making growth media, cleaning lab glassware, and maintaining instruments.

  • 2020-2021 First-Year Scholar: Stephanie Sam, biology

    • Molecular cargo delivery into bacteria; Delivering the goods

      Common bacteria are very easy to grow and study in a research lab.  They are interesting because many have useful abilities such being able to degrade toxic waste products, producing antibiotics or for food production, such as yogurts and cheese.  It is also relatively easy to manipulate bacteria to do even more useful things we want them to through genetic engineering.  Of course, there are also some bacteria that are harmful to humans.  Our lab is investigating a molecular approach that may allow us to modify good bacteria or selectively target harmful ones for destruction.
      The Griffin lab has recently demonstrated that a cell-penetrating molecule called TAT-CaM, developed in the lab of Dr. Jonathan McMurray at KSU for mammalian cells, can be used to deliver cargo proteins into eukaryotic fungal cells.  We want to now determine if this molecule can also be used in bacterial cells.  We seek to determine the diversity of the cargoes accepted for delivery and the limitations of what can be moved that are both beneficial and toxic.  This is of particular importance if this system is to be used for industrial and biotechnology processes as well as for the potential therapies against medically-relevant bacteria.

    • The student will join a microcommunity in my lab with other novice and advance scientific proteges, all of whom will be mentored by myself, a tenured faculty member.  The student will have hands on experience in routing lab maintenance and experimental staging.  The student will share in coauthoring protocols and experimental design, setting the stage for future data analysis and research preparation.  The student will also receive social support in the culture of research and professional science as a career choice.

    • Weekly duties will vary according to the needs of the lab and the advancement of the student.  Some weekly duties may include; media and culture preparation, cell culturing and sterilization of experiment supplies, general lab maintenance, and basic molecular procedures (DNA extractions and PCR).

  •  2019-2020 First-Year Scholar: Jordyn Burman, mathematics

    • Public transportation influences the daily life of a large population. Any improvement of public transportation services will benefit a large number of users and have broad impacts. Due to the wide usage and high operational cost, it is generally infeasible to conduct large scale experiments. In practice, one important solution to develop new public transportation policies is via simulations based on various models, which require high model accuracy, reliability, and efficiency. With the rapid growth of data science, data-driven modeling with machine learning has become an active research area. Meanwhile, traditional mathematical modeling is still a popular choice in many scenarios. Both modeling methodologies have their own pros and cons.

      The objective of this project is to develop a new modeling approach combining the superiorities of above two modeling methodologies and investigate two public transportation problems leveraging real-world data: (i) highway traffic pattern recognition, and (ii) bike share station inventory prediction. Despite the fact that these two problems arise from different areas, exploratory data analysis has demonstrated that the collected data from these two problems share many common patterns. This finding enlightens us to develop a universal data-driven modeling solution to investigate both problems.

      Under the guidance of the faculty mentor and senior student investigators, the first-year student will implement two classic machine learning solutions and be involved in the development of a new type of generic data-driven models by combining statistical and pattern-recognition-based algorithms, machine learning, as well as the virtue of dynamic equations. The models will be implemented with Matlab/Python and will be applied to study the following problems:

      • identify the highway traffic patterns for workdays versus holidays;
      • detect highway traffic incidents;
      • identify the bike share usage patterns for weekdays versus weekends; and
      • predict the changes of bike share station inventory.

      By participating in the project, the first-year student researcher will understand the mathematical principles of machine learning, learn fundamental mathematical modeling techniques, and develop hands-on data analytic and programming skills needed for data science industry. This experience will be a good reference for students’ career planning.

      The faculty mentor, Dr. Min Wang, is an applied mathematician with both academic and industrial experience. He has built a successful track record of research and student mentoring. He has published over 50 research papers in peer-reviewed journals and has given 35 presentations on his research. His work has been supported by 2 NSF awards. Thus far, he has mentored 10 undergraduate students. Those student research projects have led to 6 research papers and several oral or poster presentations. His experience will ensure the success of the proposed project. More information on Dr. Wang’s experience and qualification may be found at his webpage: 


      • Develop hands-on Matlab/Python programming skills on data analytics and machine learning.

      • Develop the ability to implement mathematical formula/flowchart/pseudo code with Matlab/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.

      • A paper based on the project outcomes will be submitted for publication by the end of the academic year.

      • 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 Matlab/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. Analysis and Applied Math Seminars, KSU R Day, etc.

  • 2020-2021 First-Year Scholar: Vanessa Phan, biochemistry

    • Stress reaction system modeling study

      In this project, the student will be able to learn the human stress reaction system hypothalamica pituitary adrenal(HPA) axis from scratch. We will first introduce the biology background of this system, and then we will move to the math modeling analysis part. Common ordinary differential equations knowledge and necessary programming skills will be introduced along with the project.

    •  Upon completing this project, students will be able to:

      • Understand the biological background of the stress reaction system and standard compartment modeling process.
      • Construct the standard HPA axis model through the ordinary differential equation.
      • Use mathematical software to simulate the model and test the hypothesis.
      • The student needs to work on the reading assignment and conduct a weekly report to the advisor.
      • The student will meet with the advisor weekly to discuss the project progress.
  • 2020-2021 First-Year Scholar: Daniel Reyes, physics

    • Double Crescent Moon Reflection in Coffee Mugs

      When a coffee cup is put under some light source (not directly above), a double crescent moon reflection is formed at the bottom. In this project, we try to understand this phenomenon, derive a mathematical equation for the double crescent and give justification for it. We also study what happens if the shape of the coffee mug is changed.

      • Develop problem solving skills.
      • Learn to apply basic calculus and physics principles to real life situations.
      • Use computer to do visualization and experimentation.
      • Learn to typeset mathematical paper in LaTeX.
      • Prepare to do presentations.
      • Read assigned readings.
      • Work on preparatory and research problems.
      • Discuss ideas and progress with mentor.