We launched the first formal PhD program in Data Science in 2015.  Our program sits at the intersection ofcomputer science, statistics, mathematics, and business.  Our students engage in relevant research with faculty from across our eleven colleges.  As one of the institutions on the forefront of the development of data science as an academic discipline, we are committed to developing the next generation of Data Science leaders, researchers, and educators. Culturally, we are committed to the discipline of Data Science, through ethical practices, attention to fairness, to a diverse student body, to academic excellence, and research which makes positive contributions to our local, regional, and global community.   

Herman Ray, Director, Ph.D. in Data Science and Analytics

Sherry Ni

About the Doctoral Degree in Data Science and Analytics

This degree will train individuals to translate and facilitate new innovative research, structured and unstructured, complex data into information to improve decision making. This curriculum includes heavy emphasis on programming, data mining, statistical modeling, and the mathematical foundations to support these concepts. Importantly, the program also emphasizes communication skills – both oral and written – as well as application and tying results to business and research problems.

Because this degree is a Ph.D., it creates flexibility. Graduates can either pursue a position in the private or public sector as a "practicing" Data Scientist – where continued demand is expected to greatly outpace the supply - or pursue a position within academia, where they would be uniquely qualified to teach these skills to the next generation.

Information Sessions for Fall 2025 Admission

To be announced

Data Science and Analytics PhD Curriculum

Stage One: Pre-Program Requirements

Stage Two: Coursework

The Ph.D. in Data Science and Analytics requires 78 total credit hours spread over four years of study. Example Program of Study: 

Year 1

Year 2

  • 21 credit hours of electives in computer science, statistics, mathematics, information technology, or other area by permission. 
  • Research Proposal 

Year 3

  • DS 9700 Doctoral Internship/Research Lab
  • DS 9900 Dissertation
  • Teaching
  • Dissertation Proposal Defense

Year 4

  • DS 9900 DissertationFinal Dissertation Defense

Stage Three: Project Engagement and Research/Dissertation

Relevant, interdisciplinary research forms the foundation of the Ph.D. in Data Science and Analytics. While students are encouraged to engage in research from their first semester, the last two years of the program are structured to help students transition into becoming independent, lead researchers. In this last stage of the program, students will work with research faculty, including their advisor, in one of our data science research labs.

Program Student Learning Outcomes

At the end of the program, students will be able to:

  • Demonstrate their understanding of the research process
  • Demonstrate mastery of core concepts relevant to three key areas in mathematics, statistics and computer science
  • Develop themselves as professionals prepared for work as a doctoral-educated individual beyond graduation

Admission Requirements and Application

Requirements for Admissions Apply Now View Program Course Catalog

Frequently Asked Questions (FAQ)

  • This is a traditional Ph.D. Program. We expect that individuals will complete the program in 4-5 years. This will include completion of course work in years 1-3 and completion of Project work and Research/Dissertation work in Year 4-5.
  • This is a traditional, in-residence, STEM Ph.D. Program - not a professional doctorate. Therefore, qualified students will receive a tuition waiver and a research stipend.
  • Individuals who have an undergraduate/MS degree in a quantitative field (i.e. Engineering, Economics, Mathematics, Statistics, Finance) are particularly strong candidates. Successful applicants will have some previous experience with programming languages as well as have completed a calculus series.
  • The Ph.D. in Data Science and Analytics is a flexible degree which will enable graduates to work in the private sector as a senior executive in an analytics organization as well as pursue a career in academics - teaching the next generation of data scientists.
  • Successful completion of the program will require students to defend a doctoral research dissertation. Students, working with their faculty research advisor, will be expected to submit research papers to competitive conferences and to peer-reviewed journals. Student research projects should be aligned with their project engagement requirement.
    • Analytics
    • Applied Computer Science
    • Applied Economics and Statistics
    • Applied Statistics
    • Applied Mathematics
    • Bioinformatics
    • Business Analytics
    • Chemical Biology
    • Computer Science
    • Data Science
    • Forecasting & Strategic Management
    • Integrative Biology
    • Public Admin in Economic Policy Mgmt
    • Mathematics
    • Mechanical Engineering
    • Software Engineering
    • Statistics
  • Successful completion of the program will require students to complete a minimum of 9 credit hours in Project Engagement, which will take the form of a research project (as approved by the director) with an external sponsor in the private or public sector. Kennesaw State University has relationships with dozens of organizations across a wide range of application domains to ensure that individuals have the opportunity to participate in a project engagement aligned with their research interests.
  • No. The program is a full-time traditional Ph.D. program. Students will engage in substantive project-based work, research, teaching, and internship/practicums. Students receive a research stipend to cover living costs.
  • Yes. The university provides on-campus housing at both our Kennesaw and Marietta campuses. There is also off campus student housing within a mile of the campus - most of which is on the bus line for the university.
  • No. The courses are face-to-face and in-class. Most courses have a student-faculty ratio of less than 15 students per faculty. All Ph.D. students will have a faculty advisor.
  • Most applicants have already successfully completed a masters degree in a computational discipline (e.g., engineering, computer science, statistics). Applicants without a masters degree can apply to the MS in Computer Science or the embedded MS in Applied Statistics. 
    • Ajou University, South Korea
    • Albert-Ludwigs University of Freiburg
    • Auburn University
    • Bowling Green State University
    • Clemson University
    • Columbia University
    • Columbus State University
    • Florida State University
    • Georgia Southern University
    • Georgia State
    • Georgia Tech
    • Iran University of Science and Technology
    • Kennesaw State University
    • Marshall University
    • Michigan State University
    • Murray State University
    • North Carolina State University
    • St. Petersburg State University, Russia
    • University of KwaZulu-Natal, South Africa
    • University of Michigan
    • University of North Carolina
    • University of Toledo

Ph.D. in Data Science and Analytics Student Cohorts

  • Md Shafiul Alam

    Md Shafiul Alam

    Graduation Date: Fall 2022

    Dissertation: Appley: Approximate Shapley Values for Model Explainability in Linear Time

    Dissertation Advisor: Dr. Ying Xie

    Current Position: AI Framework Engineer, Intel Corporation

    Jonathan Boardman

    Jonathan Boardman

    Graduation Date: Fall 2022

    Dissertation: Ethical Analytics: A Framework for a Practically-Oriented Sub-Discipline of AI Ethics

    Dissertation Advisor: Dr. Ying Xie

    Current Position: Data Scientist, Equifax

    Tejaswini Mallavarapu

    Tejaswini Mallavarapu

    Bachelor’s Degree: Pharmacy, Acharya Nagarjuna University, India

    Master’s Degree: Computer Science, Kennesaw State University

    Work History:

    • Graduate Research Assistant, Kennesaw State University, 2017-present
    • Research Analyst, Divis Laboratories, 2013-2014

    Selected Publications:

    • T. Mallavarapu, Y. Kim, J.H. Oh, and M. Kang, "R-PathCluster: Identifying Cancer Subtype of Glioblastoma Multiforme Using Pathway-Based Restricted Boltzmann Machine," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2017), International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics, Accepted, 2017.
    • M.R. Shivalingam, K.S.G. Arul Kumaran, D. Jeslin, Ch. MadhusudhanaRao, M. Tejaswini, "Design and Evaluation of Binding Properties of Cassia roxburghii Seed Galacto mannan and Moringa oleifera Gum in the Formulation of Paracetamol Tablets," Research Journal of Pharmacy and Technology(RJPT). 3(1): Jan.-Mar. 2010; Page 254-256.
    • M.R. Shivalingam, K.S.G. Arul Kumaran, D. Jeslin, Y.V. Kishore Reddy, M. Tejaswini, Ch. MadhusudhanaRao, V. Tejopavan, "Cassia roxburghii Seed Galacto manna— a potential binding agent in the tablet formulation," Journal of Biomedical Science and Research(JBSR), Vol 2 (1), 2010, 18-22

    Professional Objective: To be a data scientist in the field of health care or bioinformatics where I can leverage my analytical skills and knowledge towards the advancement of the research field.

    LinkedIn

    Seema Sangari

    Seema Sangari

    Graduation Date: Summer 2022

    Dissertation: Debiasing Cyber Incidents - Correcting for Reporting Delays and Under-reporting

    Dissertation Advisor: Dr. Michael Whitman

    Current Position: Principal Modeler, HSB 

    Srivarna Settisara Janney

    Bachelor’s Degree: Mechanical Engineering, Visveswaraiah Technological University, India

    Master’s Degree: Computer Science, Kennesaw State University

    Work History:

    • Graduate Research Assistant, Kennesaw State University, 2016-2018
    • Senior Software Engineer, Torry Harris Business Solutions (THBS), United Kingdom, 2010-2012 and India, 2012-2014
    • Software Engineer, Torry Harris Business Solutions (THBS), India, 2007-2010

    Selected Publications/Presentations:

    • S.S. Janney, S. Chakravarty, “New Algorithms for CS – MRI: WTWTS, DWTS, WDWTS”, One-page research paper, 40th International Conference of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Jul 2018
    • Master thesis presented at Southeast Symposium on Contemporary Engineering Topics (SSCET), UAH Engineering Forum, Alabama, Aug 2018
    • Master thesis poster is accepted to be presented at Biomedical Engineering Society (BMES) 2018 Annual Meeting, Oct 2018
    • Submitted draft copy for book chapter contribution on “Bioelectronics and Medical Devices”, Elsevier Publisher, May 2018
    • Showcased 3MT, Georgia Council of Graduate Schools (GCGS), Apr 2018
    • Master thesis presented in workshop for “Medical Signal and Image Processing” at Department of Biotechnology & Medical Engineering, NIT Rourkella, Feb 2018
    • S.S. Janney, I. Karim, J. Yang, C.C Hung, Y. Wang, “Monitoring and Assessing Traffic Safety Using Live Video Images”, GDOT project showcase, 4th Annual Transportation Research Expo, Sept 2016

    Service and Awards:

    • 1st Place Winner, Graduate Research Project, C-day Poster Presentation, Kennesaw State University, Spring 2018
    • People's Choice Award, 3 Minute Thesis (3MT), Apr 2018
    • CCSE Dean’s 4.0 Club, Jan 2018
    • 3rd Place Winner, Hackathon 2017 - HPCC Systems Big Data
    • Foundation of Computer Science, Certified by Kennesaw State University, Jun 2016
    • Fundamental of RESTful API Design, Certified by APIGEE, Nov 2014
    • Member of HandsOnAtlanta, since 2014
    • SOA Associate, Certified by IBM, Jun 2008

    Professional Objective: I would like to be a researcher in Data Science and Analytics in medical imaging technologies contributing to advancements that would help medical and healthcare professionals provide value-based and personalized health care. I would like to look at career opportunities in industry and academia that fuel my interest in research.

    LinkedIn

  • Trent Geisler

    Trent Geisler

    Graduation Date: Summer 2022

    Dissertation: Novel Instance-Level Weighted Loss Function for Imbalanced Learning

    Dissertation Advisor: Dr. Herman Ray

    Current Position: Assistant Professor, Department of Systems Engineering, United States Military Academy West Point

    Srivatsa Mallapragada

    Srivatsa Mallapragada

    Bachelor’s Degree:  Mechanical Engineering, Andhra University College of Engineering, India

    Master’s Degree: Mechanical Engineering, University of North Carolina at Charlotte

    Work History:

    Continuous Improvement Intern, Daimler Trucks North America at Cleveland, North Carolina, USA
    Computational Fluid Dynamics (CFD) Graduate Research Assistant, NC Motorsports and Research Laboratory
    Manufacturing Intern, Caterpillar India Pvt Ltd, Sriperambudur, India
    Selected Publications/Presentations:

    Mallapragada, S. (2017). Computational Investigations on the Aerodynamics of a Generic Car Model in Proximity to a Side Wall (Master’s thesis, The University of North Carolina at Charlotte).
    Uddin, M., Mallapragada, S., & Misar, A. (2018). Computational Investigations on the Aerodynamics of a Generic Car Model in Proximity to a Side-Wall (No. 2018-01-0704). SAE Technical Paper.
    Dimensionality Reduction of Hyperspectral Images for Classification, Srivatsa, M., Michael, W. & Hung, C. C. Ninth International Conference on Information ISSN: 1343-4500
    Bounds, C., Mallapragada, S., and Uddin, M., "Overset Mesh-Based Computational Investigations on the Aerodynamics of a Generic Car Model in Proximity to a Side-Wall," SAE Int. J. Passeng. Cars - Mech. Syst. 12(3):211-223, 2019, https://doi.org/10.4271/06-12-03-0015.
    Service and Awards: Base SAS Programmer V9
    Professional Objectives: I am currently working in unsupervised pattern recognition in high dimensional data sets. After I graduate, I would like to pursue a career in Data Science and Machine Learning in the corporate environment.

    LinkedIn

    Sudhashree Sayenju

    Sudhashree Sayenju

    Graduation Date: Spring 2023

    Dissertation: Quantification and Mitigation of Various Types of Biases in Deep NLP Models

    Dissertation Advisor: Dr. Ramazan Aygun

    Christina Stradwick

    Christina Stradwick

    Bachelor’s Degree: Music Performance and Mathematics, Marshall University

    Master’s Degree: Mathematics with Emphasis in Statistics, Marshall University

    Courses Taught: Prep for College Algebra at Marshall University

    Selected Presentations:

    • Stradwick, C. Exploring the Variance of the Sample Variance. Spring Meeting of the Mathematical Association of America Ohio Section, University of Akron, 2019.
    • Stradwick, C., Vaughn, L., Hanan Khan, A. Data Modeling on Insurance Beneficiary Dataset. College of Science Research Expo 2018, Marshall University, 2018. Poster Presentation.
    • Stradwick, C. Disease modeling on networks. The 13th Annual UNCG Regional Mathematics and Statistics Conference, University of North Carolina at Greensboro, 2017. Poster Presentation.

    Professional Objectives: To work as a researcher in industry or in a laboratory setting. I would like to use my background in mathematics and statistics to develop novel solutions that address limitations in current data science techniques and to apply known data science methods to solve real-world problems.

    LinkedIn

  • Martin Brown

    Martin Brown

    Bachelor's Degree: Mathematics, Swansea University, United Kingdom

    Master's Degree: Mathematics, Murray State University

    Work History: 

    • Graduate Research Assistant, Kennesaw State University, August 2020 to present
    • Graduate Teaching Assistant, Murray State University, August 2018 to May 2020

    Course Taught: Problem Solving in Mathematics

    Publications: Brown, Martin K. W. "Evaluating an Ordinal Output using Data Modeling, Algorithmic Modeling, and Numerical Analysis" (2020). Murray State Thesis and Dissertations 168.

    Awards: David Pryce History of Mathematics Prize 2017-2018

    Professional Objective: To pursue a career in data science, machine learning, and predictive analytics to solve real-world issues 

     Inchan Hwang

    Inchan Hwang

    Bachelor’s Degree: Computer Science, Georgia Southwestern State University

    Master’s Degree: Software Engineering, Ajou University, South Korea

    Courses Tutored: Precalculus, College Algebra, Calculus I at Georgia Southwestern State University

    Work History:

    Tutoring College Algebra, Calculus I and II at Academic Skills Center, Georgia Southwestern State University
    Research Assistant at Intelligence of HyperConnected Systems Lab of Ajou University
    Fullstack web developer, windows system programmer in the cybersecurity industry
    Professional Objective: To work in big data analytics, and research and development of machine learning in engineering, and security

    Linkedin

    Duleep Prasanna Rathgamage Don

    Duleep Prasanna Rathgamage Don

    Bachelor's degree: Physics and Mathematics, The Open University of Sri Lanka

    Master's degree: Mathematics, Georgia Southern University

    Work History:

    • Graduate Teaching Assistant, Georgia Southern University, 2016 - 2018
    • Graduate Teaching Assistant, University of Wyoming, 2019 - 2020

    Courses Taught: Trigonometry, and Calculus I & II

    Publications/Presentations:

    • Don, R. D. and Iacob, I. E., ‘DCSVM: Fast Multi-class Classification using Support Vector Machines’, International Journal of Machine Learning and Cybernetics.
    • Rathgamage Don, D., Iacob, E., ‘Divide and Conquer Support Vector Machine for Multiclass Classification’, Research Symposium (2018), Georgia Southern University.
    • Rathgamage Don, D., Iacob, E., ‘Multiclass Classification using Support Vector Machines’, MAA Southeastern Section Meeting (2018), Clemson University.

    Professional Objective: To work in big data analytics, and research and development of machine learning in engineering, and medicine

    Linkedin

    Linglin Zhang

    Linglin Zhang

    Bachelor’s Degree: Biological Sciences, Hubei University, China

    Master’s Degree: Chemical Biology, University of Michigan and Bioinformatics, Georgia Institute of Technology

    Selected Publications: Rebecca Shen, Zhi Li, Linglin Zhang, Yingqi Hua, Min Mao, Zhicong Li, Zhengdong Cai, Yunping Qiu, Jonathan Gryak, Kayvan Najarian. (2018). Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 690-693, 2018.

    Professional Objective: To become a researcher in industry or academia. My background in Biology and Bioinformatics could provide me strong theoretical support on a research role in the health industry. The experience of doing an internship at Equifax equipped me of certain knowledge on business cases. 

    Linkedin

    Yihong Zhang

    Yihong Zhang

    Bachelor’s Degree: Psychology Mathematics Interdisciplinary, Chatham University

    Master’s Degree: Mathematics and Statistics Allied with Computer Science, Georgia State University

    Work History:

    • Research Assistant - Collaborated with biomedical department to analyze and visualize microarray gene expression data, Facilitated in data pre-processing and machine learning modeling of clinical liver cirrhosis image data, Assisted in feature engineering of image analysis in deep learning for pathology diagnosis with Mayo Clinic’s pilot project.
    • Graduate Lab Assistant - Tutored students with statistics and math subjects.

    Professional Objective: Make better use of data in healthcare and bioinformatic industry as a data scientist.

  • Sanad Biswas

    Sanad Biswas

    Bachelor's Degree: Statistics, Biostatistics and Informatics, University of Dhaka, Bangladesh

    Master's Degree: Statistics, University of Toledo, OH

    Work History: 

    • Research Assistant: US Army Research Lab, Kennesaw State University
    • Consultant, Statistical Consulting Service, University of Toledo
    • Graduate Teaching Assistant, University of Toledo

    Courses Taught: Calculus and Business Calculus, Facilitated students’ study of Statistics courses at the University of Toledo.

    Professional Objective: To work as a researcher in the industry or as a faculty. I am primarily interested in the application of machine learning in different fields.

    LinkedIn

    Mallika Boyapati

    Mallika Boyapati

    Bachelor's Degree: Electronics and Computer Engineering, K L University, India

    Master's Degree: Applied Computer Science, Columbus State University

    Work History: 

    • T-Mobile, Seattle, WA, USA: Sr. Data analyst, 2018- 2021
    • UITS, Columbus State University, Columbus, GA, USA: Data Analyst -Graduate assistant, 2016-2018
    • Menlo Technologies, India: Jr. Data Analyst, Intern, 2014- 2016

    Courses Taught: DATA 4310 - Statistical Data Mining

    Publications:

    • Anti-Phishing Approaches in the Era of the Internet of Things. In: Pathan, AS.K. (eds) Towards a Wireless Connected World: Achievements and New Technologies. Springer, Cham - https://doi.org/10.1007/978-3-031-04321-5_3
    • An empirical analysis of image augmentation against model inversion attack in federated learning - https://doi.org/10.1007/s10586-022-03596-1
    • M. Boyapati and R. Aygun, "Phishing Web Page Detection using Web Scraping," SoutheastCon 2023, Orlando, FL, USA, 2023, pp. 167-174, doi: 10.1109/SoutheastCon51012.2023.10115148.
    • M. Boyapati and R. Aygun, "Default Prediction on Commercial Credit Big Data Using Graph-based Variable Clustering," 2023 IEEE 17th International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, 2023, pp. 139-142, doi: 10.1109/ICSC56153.2023.00029.
    • Boyapati, M., Aygun, R. (2023) Explainable Machine Learning for Default Prediction on Commercial Credit Big Data Using Graph-based Variable Clustering. In Encyclopedia with Semantic Computing and Robotic Intelligence VOL. 0 https://doi.org/10.1142/S2529737623500119

    Service and Awards:

    • Winners of Dataiku March Madness Bracket-thon, 2021 in predicting the NBA bracket
    • Winners of 2021 Analytics Day Ph.D. level research poster presentation 

    Professional Objective: To leverage strong analytical and technical abilities to research and develop effective data models, visualize data, and uncover insights that makes an impact in field of data science

    LinkedIn

    Nina Grundlingh

    Nina Grundlingh

    Bachelor's Degree: Applied Mathematics and Statistics, University of KwaZulu-Natal, South Africa

    Master's Degree: Statistics, University of KwaZulu-Natal, South Africa

    Courses Taught: Introduction to Statistics, University of KwaZulu-Natal

    Publications:

    • Grundlingh, N., Zewotir, T., Roberts, D. & Manda, S. Modelling diabetes in South Africa. The 61st conference of the South African Statistical Association, 27-29 November 2019, Nelson Mandela University, South Africa.
    • Grundlingh, N., Zewotir, T., Roberts, D. & Manda, S. Modelling diabetes in the South African population. College of Agriculture, Engineering and Science Postgraduate Research & Innovation Symposium 2019, 17 October 2019, University of KwaZulu-Natal, Westville, South Africa (the award for best MSc presentation was also received for this).
    • Grundlingh, N., Zewotir, T., Roberts, D. & Manda, S. Modelling risk factors of diabetes and pre-diabetes in South Africa. IBS SUSAN-SSACAB 2019 Conference, 8-11 September 2019, Cape Town, South Africa.

    Service and Awards:

    • University of KwaZulu-Natal Postgraduate Research & Innovation Symposium 2019 – Best Masters oral presentation
    • South African Statistical Association Honours Project Competition 2018/2019 – 2nd place and special prize for best use of SAS

    Professional Objective: To work in a teaching position – sharing how data science can be applied to different fields and the positive impact it could have. I would like to use my theological background and passion to bring insight, clarity, and wisdom to data science problems. 

    LinkedIn

    Namazbai Ishmakhametov

    Namazbai Ishmakhametov

    Bachelor's Degree: Specialist in Mathematical Methods in Economics, Kyrgyz-Russian Slavic University

    Master's Degree: Analytics, Institute for Advanced Analytics at North Carolina State University

    Work History: 

    • Expert at the Centre for Economic Research, National bank of the Kyrgyz Republic
    • Consultant in World Bank project dedicated to strengthening the regulatory practices in Kyrgyz Republic
    • Consultant at Deloitte Consulting LLP, Science Based Services group, Analytics & Cognitive offering
    • Macroeconomic modeling expert in the Economic Department, National bank of the Kyrgyz Republic

    Courses Taught: Introductory statistics and econometrics (cross-sections, times series and panels) lecturer at Ata-Turk Alatoo International University, Kyrgyzstan

    Publications:

    Professional Objective: To apply my quantitative skills in the field of biotech either in corporate or government sector

    LinkedIn

    Symon Kimitei

    Symon Kimitei

    Bachelor's Degrees: Mathematics, Kennesaw State University, and Computer Science,  Kennesaw State University

    Master's Degree: Mathematics (Scientific Computing Concentration), Georgia State University 

    Work History: Senior Lecturer and Math Department Coordinator of Supplemental Instruction, Kennesaw State University

    Courses Taught: Calculus 1, Precalculus, Applied Calculus & College Algebra 

    Publications:

    Poster Presentations:

    • Kimitei, Symon & Sammie Haskin. "Nadaraya-Watson Kernel Regression Longitudinal Analysis of Healthcare Risk Factors of African American and Caucasian American Girls."
      Kennesaw State University R Day Presentation.  11 Nov. 2019. Poster presentation.
    • Kimitei, Symon. " Social Network Analysis in Supreme Court Case Rulings by Precedence Using SAS Optgraph/Python." 23rd Annual Symposium of Scholars. Kennesaw State University.  19 April. 2018. Poster presentation.

    Professional Objective: As a Ph.D. student in Analytics & Data Science, I hope to gain skills in the program that will propel me into a Data Scientist / Machine Learning Engineer with a specialization in the design and implementation of deep learning & machine learning algorithms.

    LinkedIn

    GitHub

    Jitendra Sai Kota

    Jitendra Sai Kota

    Bachelor's Degree: Computer Science & Engineering, Amrita Vishwa Vidyapeetham, India

    Master's Degree: Computer Science, Florida State University

    Work History: Teaching Assistant Professor in Computer Science at an Engineering College in India

    Courses Taught: Problem Solving & Program Design through C, Artificial Intelligence, Data Mining

    Publications: Kota, Jitendra Sai, Vayelapelli, Mamatha. 2020. "Predicting the Outcome of a T20 Cricket Game Based on the Players' Abilities to Perform Under Pressure". IEIE Transactions on Smart Processing and Computing 9(3):230-237. DOI: 10.5573/IEIESPC.2020.9.3.230

    Professional Objective: to work in Data Science in a Corporate Environment

    LinkedIn

    ResearchGate

    Catrice Taylor

    Catrice Taylor

    Bachelor's Degree: Economics, Clemson University 

    Master's Degrees: Applied Economics and Statistics, Clemson University, and Applied Statistics, Kennesaw State University 

    Professional Objective: To work as an industry data scientist in a corporate environment 

    LinkedIn

    Sahar Yarmohammadtoosky

    Sahar Yarmohammadtoosky

    Bachelor's Degree: Applied Mathematics, Sheikh Bahaei University, Isfahan, Iran 

    Master's Degree: Applied Mathematics, Iran University of Science & Technology, Tehran, Iran

    Courses Taught: Numerical Analysis and Linear Algebra, Iran University of Science & Technology

    Publications: Noah, G., Sahar, Y., Anthony P. & Hung, C.C. "ISODS: An ISODATA-Based Initial Centroid Algorithm". Accepted to: 10th International Conference on Information, March 6 - 8, 2021, Hosei University, Tokyo, Japan

    Professional Objective: My goal is to become a competent Data Science specialist capable of using my skills to bring meaning to data, getting a faculty position at a university

    LinkedIn

  • Ayomide Isaac Afolabi

    Ayomide Isaac Afolabi

    Bachelor's Degree: Chemical Engineering, Ladoke Akintola University of Technology 

    Master's Degree: Data Science, Auburn University 

    Work History: Graduate Research Assistant, Auburn University 

    Courses Taught: Python Programming 

    Publications: Larson EA, Afolabi A, Zheng J, Ojeda AS. Sterols and sterol ratios to trace fecal contamination: pitfalls and potential solutions. Environ Sci Pollut Res Int. 2022 Jul;29(35):53395-53402. doi: 10.1007/s11356-022-19611-2. Epub 2022 Mar 14. PMID: 35287190

    Professional Objective: To work as a research data scientist in the industry

    Dinesh Chowdary Attota

    Dinesh Chowdary Attota

    Bachelor's Degree: Computer Science, Jawaharlal Nehru Technological University Kakinada (JNTUK), India

    Master's Degree: Computer Science, Kennesaw State University

    Work History: Associate Consultant, SL Techknow Solutions India Pvt Ltd, India  2018 - 2020

    Publications: 

    Professional Objective: I'd like to be a faculty member at a university so that I can continue to do research.

    LinkedIn

    Nzubechukwu Ohalete

    Nzubechukwu Ohalete

    Bachelor's Degree: Mathematics,University of Nigeria, Nsukka

    Master's Degree: Applied Statistics, Bowling Green State University

    Work History: Graduate Assistant/Data Analyst, Federal University of Technology, Owerri - Mathematics Department

    Courses Taught: Elementary Mathematics, Mathematical Methods

    Awards: James A. Sullivan Outstanding Graduate Student Award, Applied Statistics and Operations Research Department, April 2022

    Professional Objective: To use data science techniques to solve problems which makes our lives better and also makes our world a better place

    LinkedIn

    Ryan Parker

    Ryan Parker

    Bachelor's Degree: Microbiology, University of Tennessee - Knoxville

    Master's Degree: Integrative Biology, Kennesaw State University

    Work History: Instructor of Biology, Kennesaw State University

    Courses Taught: Nursing Microbiology Lectures and Labs, Introductory Biology Labs, Biotechnology Lectures and Labs

    Publications: 

    • Parker RA, Gabriel KT, Graham K, Cornelison CT. Validation of methylene blue viability staining with the emerging pathogen Candida auris. J Microbiol Methods. 2020 Feb;169:105829. doi: 10.1016/j.mimet.2019.105829. Epub 2019 Dec 27. PMID: 31884053.
    • Parker RA, Gabriel KT, Graham KD, Butts BK, Cornelison CT. Antifungal Activity of Select Essential Oils against Candida auris and Their Interactions with Antifungal Drugs. Pathogens. 2022 Jul 22;11(8):821. doi: 10.3390/pathogens11080821. PMID: 35894044; PMCID: PMC9331469.

    Awards: Best Graduate Poster: Symposium for Student Scholars hosted by Kennesaw State University (Fall 2018) for Poster: "Antifungal Activity of Select Essential Oils and Synergism with Antifungal Drugs against Candida auris"

    Professional Objective: To apply Data Science techniques to large scientific datasets, such as genomic and astronomical data, and to help bridge the gap between disparate fields by working in an interdisciplinary space to offer integrative and data-driven solutions to the increasingly complex problems presented to the traditional Sciences.

    LinkedIn

    Askhat Yktybaev

    Askhat Yktybaev

    Bachelor's Degree: Forecasting and Strategic Management, Saint-Petersburg State University of Economics and Finance, Russia

    Master's Degree: Forecasting and Strategic Management, Saint-Petersburg State University of Economics and Finance, Russia; Public Administration in Economic Policy Management, School of International and Public Affairs, Columbia University

    Work History:

    • from Data Analyst to Head of Research Unit, Central Bank of Kyrgyz Republic
    • Sr. Data Scientist in OJSC, Aiyl Bank, Kyrgyzstan
    • Consultant, The World Bank, Washington D.C.

    Courses Taught: Financial Programing in the Central Bank, Monetary Policy Transmission Mechanism

    Service and Awards: Winner of the Joint Japan/World Bank Graduate Scholarship Program, National Bank Silver Medal for Best Forecast

    Professional Objective: I want to found a successful Fintech startup one day.

    LinkedIn

  • Royce Alfred

    Royce Alfred

    Bachelor's Degree: Psychology, Kennesaw State University

    Master's Degree: Applied Statistics and Analytics, Kennesaw State University

    Work History: 4 years as a Data Scientist at Equifax

    Professional Objective: Work as a research data scientist in the corporate environment

    LinkedIn

    Venkata Abhiram Chitty

    Venkata Abhiram Chitty

    Bachelor's Degree: Mathematics, Statistics and Computer Science, Osmania University, Telangana, India

    Master's Degree: Data Science, VIT-AP University, Amaravati, Andhra Pradesh, India

    Professional Objective: To apply my Data Science skills in public health domain and help the society

    LinkedIn

    Caleb Greski

    Caleb Greski

    Bachelor's Degree: 

    Master's Degree: 

    Work History: 

    Courses Taught: 

    Publications: 

    Professional Objective: 

    LinkedIn

    Moukthika Kadaparthi

    Moukthika Kadaparthi

    Bachelor's Degree: Electrical and Electronics Engineering, SASTRA Deemed University

    Master's Degree: Computers and Information Science, Cleveland State University

    Work History: 

    • Business Intelligence Analyst, Philips Healthcare, Georgia
    • Graduate Research Assistant, Cleveland State University, Ohio 

    Professional Objective: My objective is to enter academia with the aim of sharing the practical applications of data science in diverse domains and its potential positive impacts. With my unique blend of academic rigor and industry experience, I am driven to analyze complex data sets using cutting-edge data science techniques, to provide actionable insights and support data-driven decision-making.

    Qiaomu Li

    Qiaomu Li

    Bachelor's Degree: Civil Engineering, Huazhong University of Science and Technology, China

    Master's Degree: Business Analytics, Syracuse University

    Work History: 

    • Credit Modeling Analyst, Agricultural Development Bank of China
    • Research Assistant, Changjiang Securities
    • Graduate Assistant, Syracuse University

    Courses Taught: Calculus I, Marketing Analytics, Data Mining

    Awards: Merit-Based Scholarship, Syracuse University

    Professional Objective: To secure a challenging position in a reputable organization to expand myself within the field of Artificial Intelligence.

    LinkedIn

    Kausar Perveen

    Kausar Perveen

    Bachelor's Degree: Bachelor in Engineering Software Engineering, National University of Sciences and Technology, Pakistan

    Master's Degree: Masters in Data Science, Illinois Institute of Technology, Chicago

    Work History: 

    • Fullstack Developer at ItRunsInMyFamily, Charleston, South Carolina
    • Software Engineer II , Xgrid Pakistan
    • Senior Research Coordinator, Aga Khan University Pakistan
    • Machine Learning Engineer, Agoda Thailand

    Publications: National cervical cancer burden estimation through systematic review and analysis of publicly available data in Pakistan 

    Service and Awards:

    • Fulbright Scholarship award for Master’s degree in Data Science
    • Aga Khan Education Service Pakistan, merit cumulative need based scholarship for Bachelors in Software Engineering 

    Professional Objective: My main motivation behind getting a degree in Data Science is to receive and perform qualified research experience in Data Science and public health

    LinkedIn

    Github

    Promi Roy

    Promi Roy

    Bachelor's Degree: Statistics, University of Dhaka, Dhaka, Bangladesh

    Master's Degree: Mathematics (Statistics Concentration), University of Toledo, Ohio

    Work History: 

    • Analytics Engineer Intern, Cooper Smith, Toledo, Ohio
    • Business AnalystAkij Food and Beverage Limited, Dhaka, Bangladesh

    Courses Taught: Introduction to Statistics

    Professional Objective: I am interested to work as a data scientist in the industry

    LinkedIn

    Github