Doctoral Degree in Analytics and Data Science
Welcome Message
We launched the first formal PhD program in Data Science in 2015. Our program sits
at the intersection of computer 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.
Sherry Ni, Director, Ph.D. in Analytics and Data Science
About the Doctoral Degree in Analytics and Data Science
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.
ssi
Analytics and Data Science PhD Curriculum
Stage One
Pre-Program Requirements
Stage Two
Coursework
Stage Three
Project Engagement and Research/Dissertation
Stage One: Pre-Program Requirements
- Successful applicants will have completed a masters degree in a computational field (e.g., engineering, computer science, statistics, economics, finance, etc.)
- Applicants are expected to have deep proficiency in at least one analytical programming language (e.g., SAS, R, Python). SQL and Java are helpful but not required.
- Interested applicants who have earned an undergraduate degree are encouraged to apply to the Ph.D. Program with the embedded MS in Computer Science or with the MS in Applied Statistics.
Stage Two: Coursework
The Ph.D. in Analytics and Data Science requires 78 total credit hours spread over four years of study. Example Program of Study:
YEAR 1
- CS 8265 Big Data Analytics
- CS 8267 Machine Learning
- MATH 8010 Theory of Linear Models (optional)
- MATH 8020 Graph Theory
- MATH 8030 Applied Discrete and Combinatorial Mathematics
- STAT 8240 Data Mining I
- STAT 8250 Data Mining II
- Comprehensive Exam
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 Analytics and Data Science. 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.
Admission Requirements and Application
Requirements for AdmissionAPPLY TO THE PROGRAM
VIEW PROGRAM COURSE CATALOG
Frequently Asked Questions (FAQ)
Here are the most commonly asked questions regarding the Ph.D. in Analytics and Data Science program at KSU.
- How long will the program take?
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. - How much does the program cost?
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. - Who would be successful in the program?
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. - Where do these graduates work after graduation?
The Ph.D. in Analytics and Data Science 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. - What are the publication/research requirements?
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. - What is the Project Engagement requirement?
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. - Can I pursue the program part time while I am working full time?
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. - Can I live on campus?
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. - Are the courses online?
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. - Do I have to have a masters degree to apply?
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.
Student Cohorts
Ph.D. in Analytics and Data Science Cohorts
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2021 - 2022 Cohort
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.
Mallika Boyapati
Bachelor's Degree:
Master's Degree:
Work History:
Courses Taught:
Publications:
Service and Awards:
Professional Objective:
LinkedIn
Yang Fu
Bachelor's Degree: Central South University, Hunan, China
Master's Degree: Business Analytics, Michigan State University
Work History:
- Fafnir Lab, Research Associate/Data Scientist
- LHP Engineering Solutions, Software Intern
Professional Objective: To work as a data scientist in industry focusing on both research and practical application
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.
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:
- Ishmakhametov Namazbai, Abdygulov Tolkunbek, Jenish Nurbek. 2020. “Impact of 2014-2015 shocks on economic behavior of the households in the Kyrgyz Republic". Working Paper of the National Bank of the Kyrgyz Republic
- Sherrill W. Hayes, Jennifer L. Priestley, Namazbai Ishmakhametov, Herman E. Ray. 2020. “I’m not Working from Home, I’m Living at Work”: Perceived Stress and Work-Related Burnout before and during COVID-19”. PsyArxiv Preprints
- Ishmakhametov Namazbai, Arykov Ruslan. 2016. “Credit Risk Model on the Example of the Commercial Banks of the Kyrgyz Republic”. Working Paper of the National Bank of the Kyrgyz Republic
- Namazbai Ishmakhametov, Anvar Muratkhanov.2015. “Modeling strategy of the Bank of the Kyrgyz Republic”. National bank of Poland – Swiss National bank joint seminar. Zurich, Switzerland
Professional Objective: To apply my quantitative skills in the field of biotech either in corporate or government sector
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:
- Haskin, S., Kimitei, S., Chowdhury, M., Rahman, F., Longitudinal Predictive Curves
of Health-Risk Factors for American Adolescent Girls. Journal of Adolescent Health.
JAH-2021-00601R1 - Symon K Kimitei, Algorithms for Toeplitz Matrices with Applications to Image Deblurring. 2008. Georgia State University, Masters thesis. ScholarWorks
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.
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
Rehma Razzak
Bachelor's Degree: Computer Science, Kennesaw State University
Master's Degree: Computer Science, Kennesaw State University
Publications:
- Sensor Fusion For Drone Detection: Aledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Gautam Srivastava. "Sensor Fusion for Drone Detection." In 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), pp. 1-7. IEEE, 2021.
- Multimodal Machine Learning for Pedestrian Detection: Aledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Gautam Srivastava. "Multimodal Machine Learning for Pedestrian Detection." In 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), pp. 1-7. IEEE, 2021.
- Machine Learning for Network Application Security: Aledhari, Mohammed, Rehma Razzak, and Reza M. Parizi. "Machine learning for network application security: Empirical evaluation and optimization." Computers & Electrical Engineering 91 (2021): 107052.
- Deep Neural Networks for Detecting Real Emotions using Biofeedback and Voice: Aledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Gautam Srivastava. "Deep neural networks for detecting real emotions using biofeedback and voice." In International Conference on Pattern Recognition, pp. 302-309. Springer, Cham, 2021.
- Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey: Tariq, Muhammad Usman, Muhammad Haseeb, Mohammed Aledhari, Rehma Razzak, Reza M. Parizi, and Fahad Saeed. "Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey." IEEE Access 9 (2020): 5497-5516.
- An Adaptive Segmentation Technique to Detect Brain Tumors Using 2D Unet: Aledhari, Mohammed, and Rehma Razzak. "An Adaptive Segmentation Technique to Detect Brain Tumors Using 2D Unet." In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2328-2334. IEEE, 2020.
- A Deep Recurrent Neural Network to Support Guidelines and Decision Making of Social Distancing Aledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Ali Dehghantanha. "A Deep Recurrent Neural Network to Support Guidelines and Decision Making of Social Distancing." In 2020 IEEE International Conference on Big Data (Big Data), pp. 4233-4240. IEEE, 2020.
- Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications: Aledhari, Mohammed, Rehma Razzak, Reza M. Parizi, and Fahad Saeed. "Federated learning: A survey on enabling technologies, protocols, and applications." IEEE Access 8 (2020): 140699-140725.
Awards:
- Project: Pedestrian Detection for darker skin-tones - Analyzed correlation between skin tone demographics and pedestrian-related fatalities. Nominated for best research project
- Project: Battling bots with Random Forest classifiers - Conducted analysis on how many fake accounts on Twitter currently exist via bot-detector made with the Random Forest classifier technique to detect fake accounts on Twitter. Nominated for best research project
Professional Objective: To work in the industry as a data scientist, such as working in Amazon
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
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
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2020 - 2021 Cohort
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
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
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
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.
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.
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2019 - 2020 Cohort
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
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.
Sudhashree Sayenju
Bachelor’s Degree: Computer Science, Jacobs University Bremen, Germany
Master’s Degree: Computer Science, Albert-Ludwigs University Freiburg, Germany
Work History:
- Research Assistant, Smart Grid Systems: Software Development and Improvement, Fraunhofer-Institut für Solare Energiesysteme, Freiburg, Germany, 2014
- Software Developer, Data Science: Data Analysis using Statistical Pattern Recognition and Machine Learning, Reservix GmbH, Freiburg, Germany, 2017-2018
Professional Objectives: I aim to work in a corporate environment where I can use the knowledge I acquired here in real world applications.
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.
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2018 - 2019 Cohort
Md Shafiul Alam
Bachelor’s Degree: Mathematics, University of Dhaka, Bangladesh
Master’s Degrees: Computational Mathematics, Western Kentucky University, and Applied Mathematics, University of Dhaka, Bangladesh
Work History:
- Graduate Research Assistant, Kennesaw State University, August 2018 to present
- Teaching Assistant, Western Kentucky University, August 2016 to May 2018
- Credit Analyst, Jamuna Bank Ltd, Bangladesh, June 2012 to July 2016
Courses taught: Calculus I and II, Western Kentucky University, Fall 2016 to Spring 2018
Professional Objective: To work as a researcher in the industry or as a faculty in a university. My research focus is broadly on Machine Learning and Artificial Intelligence.
Jonathan Boardman
Bachelor’s Degree: Physics, Occidental College
Master’s Degree: Applied Statistics, Kennesaw State University
Work History:
- Graduate Research Assistant, Kennesaw State University, May 2017 – July 2018
- Graduate Assistant, Kennesaw State University, August 2016 – May 2017
Courses taught: MATH 1107: Introductory Statistics, Kennesaw State University, Spring 2017
Selected Publications/Presentations:
- Jonathan Boardman, Kyle Biron, Ryan Rimbey; Mitigating the Effects of Class Imbalance Using SMOTE and Tomek Link Undersampling in SAS; SAS Global Forum Proceedings, 2018.
- Kyle Biron, Jonathan Boardman; Proper Preprocessing Prevents Poor Profits: Mitigating Loss Due to Credit Card Fraud Using Xgboost and SMOTE + Tomek Link Undersampling; KSU Analytics Day, 2018.
- Jonathan Boardman, Kyle Biron, Ryan Rimbey; Which Classifier is Most Robust to Class Imbalance?; KSU R Day, 2017.
Awards:
- 2017-2018 Outstanding Graduate Student Award: Master of Science in Applied Statistics; KSU – College of Science and Mathematics
- Outstanding Graduate Award 2017-2018; KSU – Graduate College
- Top 8 SAS Global Forum 2018 Student Symposium Finalist
- KSU Analytics Day 2018 2nd Place Graduate Poster
- KSU R Day 2017 2nd Place Graduate Poster
Professional Objective: To work in predictive analytics, designing and implementing novel machine learning solutions to problems in science and business.
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.
Seema Sangari
Bachelor’s Degree: Computer Science and Engineering, Himachal Pradesh University, India
Master’s Degrees:
- MSc Investment Management, Cass Business School, City University of London, London, U.K.
- MSc Applied Statistics, Birkbeck College, University of London, London, U.K.
- Graduate Certificate in Data Mining and Applications, Stanford University, US.
Work History:
- Certified Graduate Statistician by Royal Statistical Society, London, UK.
- Senior Data Scientist, IBM Security for 3.5 years.
- Have also worked as a Senior Financial Engineer for more than a decade with financial regulatory bodies in India and the UK and private sector in finance, insurance and reinsurance domain in India, the UK and Bermuda.
Professional Objective: To apply data science skills to solve the real-world business problems
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.
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2017 -2018 Cohort
Sanjoosh Akkineni
Bachelor’s Degree: Computer Science, Jawaharlal Nehru Technological University, India
Master’s Degree: Computer Science (Concentration in Data Analytics), Kennesaw State University
Work History:
- Data Science and Analytics Graduate Intern, Equifax, 2017 – Present
- Graduate Research Assistant, Kennesaw State University, 2015-2017
Selected Publications/Presentations:
- KSU Analytics Day 2018
- Computing Showcase 2016, 2017
Service:
- President - Graduate Student Association (GSA) 2016-2018, Kennesaw State University
- Treasurer - IEEE Computer Society (IEEE-CS) 2016-2017, Kennesaw State University
- Secretary - Robotics & Automation Society 2017, Kennesaw State University
- Peer Leader - International Orientation (2016-2017), Kennesaw State University
- Law Enforcement Training, Citizens Police Academy, KSU Police Department 2017
Awards:
- Won 3rd Prize for Bert’s Big Adventure driving research project – KSU Analytics Day
2018
Awarded Udacity Google Developer Scholarship 2018 - Student of the Year - Division of Student Affairs, Kennesaw State University 2017
- Graduate Student Involvement Award - International Student Association, Kennesaw State University 2017
- Golden Key International Honor Society Member
Professional Objectives: To be a data scientist with a demonstrated ability to deliver valuable insights via data analytics and advanced data-driven methods. Primary research interests are in Machine learning, algorithms for massive datasets, large scale optimization, and recommender systems. I want to work in Health Care and Government (not finite to these as I am still exploring my research interests) to build an appropriate data framework that can utilize advanced analytic means to aggregate data effectively to gain in depth insights.
Andrew M. Henshaw
Bachelor’s Degree: Electrical Engineering, Georgia Tech
Master’s Degree: Electrical Engineering, Georgia Tech
Master’s Degree: Business Administration, Georgia State University
Work History:
- Georgia Tech, School of Electrical Engineering, Research Engineer I, 1986-1990
- Georgia Tech Research Institute, Research Engineer II, 1990-1999
- APower Solutions, Vice President, 1999-2001
- Georgia Tech Research Institute, Sr. Research Engineer, 2001-
Courses taught: Software-Defined Radio Development with GNU Radio: Theory and Application, Georgia Tech Professional Education
Selected Publications/Presentations: Python Cookbook, Vol 1, 2002, “Sorting Objects Using SQL’s ORDER BY Syntax”
Service and Awards:
- International Test and Evaluation Association (ITEA) Atlanta Chapter, President, 1995
- Georgia State Soccer Association, Information Technology Committee Chair, 2009-2014
- Georgia State Soccer Association, Recreational Committee, 2007-
Professional Objectives: Enhance GTRI’s capabilities in data science and analytics
Liyuan Liu
Graduation Date: Summer 2021
Dissertation: Incentive-based Data Sharing and Exchanging Mechanism Design
Dissertation Advisor: Dr. Meng Han
Current Position: Assistant Professor, St. Joseph's University - Erivan K. Haub School of Business
Mohammad Masum
Graduation Date: Summer 2021
Dissertation: Integrated Machine Learning Approaches to Improve Classification Performance and Feature Extraction Process for EEG Dataset
Dissertation Advisor: Dr. Hossain Shahriar
Current Position: Postdoctoral Fellow, Emory University School of Medicine
Lauren Staples
Graduation Date: Fall 2021
Dissertation Advisor: Dr. Joseph DeMaio
Current Position: Team Lead Data Scientist, Inspire Brands
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2016 - 2017 Cohort
Shashank Hebbar
Graduation Date: Fall 2021
Dissertation: Tree-BERT - Advanced Representation Learning for Relation Extraction
Dissertation Advisor: Dr. Ying Xie
Current Position: Data Scientist - Risk Modeling, Credigy
Jessica Rudd
Graduation Date: Summer 2020
Dissertation: Quantitatively Motivated Model Development Framework: Downstream Analysis Effects of Normalization Strategies
Dissertation Advisor: Dr. Herman Ray
Current Position: Data Scientist, A42 Labs
Yan Wang
Graduation Date: Spring 2020
Dissertation: Data-Driven Investment Decisions in P2P Lending: Strategies of Integrating Credit Scoring and Profit Scoring
Dissertation Chair: Dr. Sherry Ni
Current Position: Statistician, Credigy
Lili Zhang
Graduation Date: Spring 2020
Dissertation: A Novel Penalized Log-likelihood Function for Class Imbalance Problem
Dissertation Advisor: Dr. Herman Ray
Current Position: Data Scientist, Hewlet Packard Enterprise
Yiyun Zhou
Graduation Date: Spring 2020
Dissertation: Attack and Defense in Security Analytics
Dissertation Advisor: Jing (Selena) He
Current Position: Data Analyst, U.S. Express Ventures
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2015 -2016 Cohort
Edwin Baidoo
Graduation Date: Spring 2020
Dissertation: A Credit Analysis of the Unbanked and Underbanked: An Argument for Alternative Data
Dissertation Advisor: Dr. Stefano Mazzotta
Current Position: Assistant Professor of Business Analytics, Tennessee Technological University
Sergiu Buciumas
Bachelor’s Degree: Economic Cybernetics and Informatics, Academy of Economic Studies of Moldova
Master’s Degree: IT, Southern Polytechnic State University
Work History:
- Senior Systems Engineer Windows, RHEL/AIX, SunTrust Bank
- Data Engineer Intern, Advanced Analytics, Coca-Cola European Partners
- Integration Engineer (Co-op), Cox Communications, Systems Engineer, SunTrust Bank.
Professional Objectives: Research position in a corporate environment or research faculty position at a university. Research – Interested in the algorithmic aspects of Artificial Intelligence, particularly focusing on Deep Learning, Natural Language Processing and Reinforcement Learning agents.
Bogdan Gadidov
Graduation Date: Summer 2019
Dissertation: One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles
Dissertation Advisor: Dr. Mohammed Chowdhury
Current Position: Data Scientist, U.S. Xpress Ventures
Jie Hao
Graduation Date: Summer 2019
Dissertation: Biologically Interpretable, Integrative Deep Learning for Cancer Survival Analysis
Dissertation Advisor: Dr. Mingon Kang
Current Position: Postdoctoral Fellow, Perelman School of Medicine at the University of Pennsylvania
Linh Le
Graduation Date: Spring 2019
Dissertation: Deep Embedding Kernel
Dissertation Advisor: Dr. Ying Xie
Current Position: Assistant Professor of Information Technology, Kennesaw State University
Bob Vanderheyden
Graduation Date: Fall 2019
Dissertation: Ordinal HyperPlane Loss
Dissertation Advisor: Dr. Ying Xie
Current Position: Principal Data Scientist, IBM
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