Students

    • Md Shafiul Alam
    • Jonathan Boardman
    • Tejaswini Mallavarapu
    • Seema Sangari
    • Srivarna Settisara Janney

    Name: 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.

    LinkedIn

     

    Name: 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.

    LinkedIn

     

    Name: 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

     

    Name: 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

    LinkedIn

     

    Name: 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

    • Sanjoosh Akkineni
    • Andrew Henshaw
    • Liyuan Liu
    • Mohammad Masum
    • Lauren Staples

     Sanjoosh

    Name: 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.

    LinkedIn

      Andrew

    Name: 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

    LinkedIn

     

    Liu

    Name: Liyuan Liu

    Bachelor’s Degree: Human Resource Management, Nanjing University of Information Science & Technology

    Master’s Degree: Financial Economics, University of Detroit Mercy

    Master’s Degree: Analytics, J. Mack Robinson College of Business, Georgia State University

    Work History:

    • Intern, Equifax, 01/2018-present
    • Graduate Research Assistant, Georgia State University Institute for Insight, 09/2015-09/2016

    Selected Publications/Presentations:

    • Liyuan Liu, Meng Han, Yiyun Zhou, and Yan Wang; LSTM Recurrent Neural Networks for Influenza Trends Prediction; Proceedings in 14th International Symposium on Bioinformatics Research and Applications (ISBRA), 2018, Springer.
    • Liyuan Liu, Meng Han, Yan Wang and Yiyun Zhou; Understanding Data Breach: A Visualization Aspect; Proceedings in 13th International Conference on Wireless Algorithms, Systems and Applications, 2018, Springer.
    • Yiyun Zhou, Meng Han, Liyuan Liu, Jing (Selena) He, Yan Wang; Deep Learning Approach for Cyber-attack Detection; Proceedings in MiseNet of IEEE International Conference on Computer Communications, 2018. 
    • Bingchen Yu, Meng Han, Liyuan Liu, Yan Huang, Yi Liang, Liquan Bai; Data-driven Approach for Understanding the Mild Cognitive Impairment; Proceedings in 14th International Symposium on Bioinformatics Research and Applications (ISBRA), 2018, Springer.

    Professional Objective: To work in data science in a corporate environment

    LinkedIn 

     

    Masum

    Name: Mohammad Masum

    Bachelor’s Degree: Mathematics, University of Dhaka, Bangladesh

    Master’s Degree: Mathematical Sciences, East Tennessee State University

    Work History: Instructor at East Tennessee State University

    Courses taught: Probability and Statistics (non-calculus) at East Tennessee State University

    MS Thesis: Vertex Weighted Spectral Clustering

    Professional Objective: to work in data science in the Health sector, and to hold a faculty position at a university

    LinkedIn

     

    Lauren

    Name: Lauren Staples

    Bachelor’s Degree: Biosystems Engineering, Clemson University

    Master’s Degree: Statistics, University of New Hampshire

    Work History: Children’s Oncology Group, Clinical Statistician, 2016-2017

    Courses taught: STAT 8940 Applied Analysis Project with Nuesoft. Co-taught with Dr. Ni

    Selected Publications/Presentations: An Optimized Route for Q100’s Bert and Kristin to Visit all Jersey Mike’s Subs in Atlanta for Charity

    Service and Awards: 3rd Place at 4/20/2018 KSU Analytics Day

    Professional Objective: Healthcare Analytics

    LinkedIn 

    • Shashank Hebbar
    • Jessica Rudd
    • Yan Wang
    • Lili Zhang
    • Yiyun Zhou

     Shashank

    Name: Shashank Hebbar

    Bachelor’s Degree: Mechanical Engineering, Anna University

    Master’s Degree: Industrial Engineering, North Carolina State University

    Work History:

    • Analytics Intern, Cox Enterprises, Atlanta, GA
    • Machine Learning Research Intern, SAS Institute, Cary, NC

    Selected Publications/Presentations:

    • SAS Global Forum 2017- “Regularization techniques”
    • Journal of Risk Management (Under Review)– “Borrower default trees in bipartite network” (co-author)

    Professional Objective: To make the best use of my data science and machine learning skills in a corporate environment and contribute to the field of applied research.  

     

    Rudd

    Name: Jessica Rudd

    Bachelor’s Degree: Anthropology, Emory University

    Master’s Degree: Public Health, Emory University

    Work History:

    Leidos, Contracted to CDC Division of Viral Diseases, Analysis and Data Management Activity Team, 2010-2017
    Rwanda Zambia HIV Research Group, Research Project Coordinator, 2007-2010

    Poster Presentations:

    • Predicting Systolic and Diastolic Blood Pressure from Time Variant Parametric Models with Longitudinal Data. Presented poster at R Day (Nov. 2016).
    • Utilizing SAS(R) to Estimate Rates of Disease from Nationally Representative Databases. Scholarship winning poster for the SAS Global Forum (April 2017).
    • A Comparison of Decision Tree with Logistic Regression Model for Prediction of Worst Non-Financial Payment Status in Commercial Credit. First place poster at SAS Day (April 2017).
    • Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification. SAS Analytics 2017 Poster Winner (September 2017)
    • Nonparametric Estimation of Time-Variant Quantiles and Statistical Models. Conference on Statistical Practice (February 2018)

    Session Presentations:

    • Evaluation of Nonparametric Smoothing Estimation Methods Using Time-Variant Longitudinal
    • Data. Presented at Joint Statistical Meeting (August 2017).
    • Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease
    • Classification. Presented at Conference on Statistical Practice (February 2018)
    • Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease
    • Classification. Presented at SAS Global Forum 2018 (April 2018)

    Peer Review Publications:

    • Rudd J. (in press). Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification. Model Assisted Statistics and Applications.
    • Rudd, M. P. H., GStat, J. M., & Priestley, J. L. (2017). A Comparison of Decision Tree with Logistic Regression Model for Prediction of Worst Non-Financial Payment Status in Commercial Credit.
    • O’Hagan, J. J., Carias, C., Rudd, J. M., Pham, H. T., Haber, Y., Pesik, N., ... & Swerdlow, D. L. (2016). Estimation of severe Middle East respiratory syndrome cases in the Middle East, 2012–2016. Emerging infectious diseases, 22(10), 1797.
    • Assiri, A., Abedi, G. R., Saeed, A. A. B., Abdalla, M. A., al-Masry, M., Choudhry, A. J., ... & Rudd, J. (2016). Multifacility outbreak of Middle East respiratory syndrome in Taif, Saudi Arabia. Emerging infectious diseases, 22(1), 32.
    • Schneider, E., Chommanard, C., Rudd, J., Whitaker, B., Lowe, L., & Gerber, S. I. (2015). Evaluation of patients under investigation for MERS-CoV infection, United States, January 2013–October 2014. Emerging infectious diseases, 21(7), 1220.
    • Rha, B., Rudd, J., Feikin, D., Watson, J., Curns, A. T., Swerdlow, D. L., ... & Gerber, S. I. (2015). Update on the epidemiology of Middle East respiratory syndrome coronavirus (MERS-CoV) infection, and guidance for the public, clinicians, and public health authorities-January 2015. MMWR. Morbidity and mortality weekly report, 64(3), 61-62.
    • Al-Abdallat, M. M., Payne, D. C., Alqasrawi, S., Rha, B., Tohme, R. A., Abedi, G. R., ... & Haddadin, A. (2014). Hospital-associated outbreak of Middle East respiratory syndrome coronavirus: a serologic, epidemiologic, and clinical description. Clinical Infectious Diseases, 59(9), 1225-1233.
    • Payne, D. C., Iblan, I., Alqasrawi, S., Al Nsour, M., Rha, B., Tohme, R. A., ... & Jarour, N. (2014). Stillbirth during infection with Middle East respiratory syndrome coronavirus. The Journal of infectious diseases, 209(12), 1870-1872.
    • Cortese, M. M., Immergluck, L. C., Held, M., Jain, S., Chan, T., Grizas, A. P., ... & Gautam, R. (2013). Effectiveness of monovalent and pentavalent rotavirus vaccine. Pediatrics, peds-2012.

    Professional Objective: To work in data science building analytics pipelines for extraction of meaning from large-scale data

    LinkedIn

     

    Wang

    Name: Yan Wang

    Bachelor’s Degree: Pharmacy, China Pharmaceutical University

    Master’s Degree: Statistics, University of Georgia

    Work History: Data Scientist Intern at Hexaware Technologies and Ernst & Young, May-Aug, 2017

    Courses taught: STAT 4210, Spring 2017 and Fall 2017, Kennesaw State University

    Selected Publications/Presentations:

    • SAS Global Forum 2017: Binary Classification on Past Due of Service Accounts using Logistic Regression and Decision Tree
    • SAS Global Forum 2016: Survival Analysis of Lung Cancer Patients using PROC PHREG and PROC LIFETEST.

    Professional Objective: To work in data science in a corporate environment

    LinkedIn

     

    Zhang
    Name: Lili Zhang

    Bachelor’s Degree: Electronic Information Science and Technology, Central South University, China

    Master’s Degree: Industrial Engineering, University of Tennessee-Knoxville

    Work History: Research Associate at Hong Kong Polytechnic University, Hong Kong, China

    Courses taught: STAT 8030 Programming in R, Fall 2017, Kennesaw State University

    Conference and Journal Publications:

    • Lili Zhang, Ying Xie and Guoliang Liu. “A Sentiment-change-driven event discovery system.” Proceedings of the International Conference on Web Intelligence, Leipzig, Germany, August 23-26, 2017, pp. 1035-1041. ACM. DOI: 10.1145/3106426.3109038
    • Lili Zhang, Jennifer Priestley and Xuelei Ni. “Comparison of Bankruptcy Prediction Models with Public Records and Firmographics”. Computer Science & Information Technology: Proceedings of the International Conference on Data Mining & Knowledge Management Process, Melbourne, Australia, February 17-18, 2018, Vol 8(3), pp. 97-109. DOI: 10.5121/csit.2018.80309
    • Lili Zhang, Jennifer Priestley and Xuelei Ni. “Influence of the Event Rate on Discrimination Abilities of Bankruptcy Prediction Models”. International Journal of Database Management Systems 10.1 (2018): 1-14. DOI: 10.5121/ijdms.2018.10101

    Poster Presentations:

    • Shashank Hebbar, Lili Zhang. “Linear Model Regularization.” SAS Global Forum 2017.
    • Bogdan Gadidov, Lili Zhang, Yiyun Zhou. “Reducing Traveling Times for Cobb County Fire Department.” 10th Annual Analytics Day at Kennesaw State University 2017.
    • Lili Zhang. “Implementing a sentiment-change-driven event discovery system on HPCC Systems.” 2017 HPCC Systems Summit Community Day.

    Professional Objective: My professional goal is to be a data scientist to generate actionable insights for various real-world problems from the data. I also would like to help young generations with my knowledge and skills. I am interested in working in both industry and academia after graduation.

    Personal Website

    LinkedIn

     

    Zhou

    Name: Yiyun Zhou

    Bachelor’s Degree: Computer Science, Chongqing University of Posts and Telecommunications

    Master’s Degree: Analytics, J. Mack Robinson College of Business at Georgia State University

    Master’s Degree: Financial Economics, University of Detroit Mercy

    Work History: Equifax Data Science and Analytics Graduate Intern

    Selected Publications/Presentations:

    • Yiyun Zhou, Meng Han, Liyuan Liu, Jing(Selena) He, Yan Wang, Deep Learning Approach for Cyber-attack Detection, proceedings in MiseNet of IEEE International Conference on Computer Communications, 2018.
    • Yiyun Zhou, Meng Han, Liyuan Liu, Yan Wang, Yi Liang, Ling Tian, Improving IoT Services in Smart-home Using Blockchain Smart Contract, IEEE International Conference on Internet of Things,2018 (Pending)
    • McGrath, R. J., Priestley, J. L., Zhou, Y., & Culligan, P. J. (2018). The Validity of Online Patient Ratings of Physicians: Analysis of Physician Peer Reviews and Patient Ratings. Interactive journal of medical research, 7(1), e8-e8.
    • Liyuan Liu, Meng Han, Yiyun Zhou, and Yan Wang, LSTM Recurrent Neural Networks for Influenza Trends Prediction, proceedings in 14th International Symposium on Bioinformatics Research and Applications (ISBRA), 2018, Springer.
    • Liyuan Liu, Meng Han, Yan Wang and Yiyun Zhou, Understanding Data Breach: A Visualization Aspect, proceedings in 13th International Conference on Wireless Algorithms, Systems and Applications, 2018, Springer.

    Professional Objective: Working as a dynamic data scientist utilizing advanced analytics to help the private and public sectors achieve artificial intelligence goals

    • Edwin Baidoo
    • Sergiu Buciumas
    • Bogdan Gadidov
    • Jie Hao
    • Linh Le
    • Bob Vanderheyden

     Edwin

    Name: Edwin Baidoo

    Bachelor’s Degree: Mathematics, Brooklyn College

    Master’s Degree: Quantitative Finance, Rutgers University

    Work History:

    • Data Science Intern, Equifax, Alpharetta, GA
    • Market Analyst, InterContinental Exchange, Atlanta, GA
    • Summer Analyst Intern, Assurant Specialty Property, Livingston, NJ
    • Data Parsing Consultant, Citadel Investment Group, New York, NY

    Courses taught: Business Calculus, Fall 2016

    Professional Objective: Apply data science techniques in financial services sector

    LinkedIn

     

     Sergiu

    Name: 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.

    LinkedIn

     

     Bogdan

    Name: Bogdan Gadidov

    Bachelor’s Degree: Industrial and Systems Engineering, Georgia Institute of Technology

    Master’s Degree: Applied Statistics, Kennesaw State University

    Work History:

    • Adjunct Faculty, University of New Hampshire, May 2017 - Present
    • Graduate Teaching Assistant, Kennesaw State University, August 2013 - May 2015
    • Model Validation Intern, SunTrust, May 2014 - August 2014
    • Implementation Engineer, Noble Systems, July 2012 - July 2013

    Courses taught:

    • Math 1111, Fall 2013, Kennesaw State University
    • Math 1107, Spring 2014, Fall 2014, Spring 2015, Spring 2016, Kennesaw State University
    • Data 801 Foundations of Data Analytics for the Master of Science in Analytics & Data Science program,
    • Summer 2017, University of New Hampshire (UNH)
    • 3 online courses in Graduate Certificate in Data Science program offered at UNH, Spring
    • 2018Data 800 (Introduction to Analytical Statistics)
    • Data 820 (Programming for Data Science)
    • Data 822 (Data Mining and Predictive Modeling)

    Selected Publications/Presentations:

    • Gadidov B., & Priestley J. L. (2018). Does Yelp matter? Analyzing (and guide to using) ratings for a quick serve restaurant chain. In Srinivasan S. (Eds.), Studies in Big Data: Vol. 26. Guide to big data applications (pp. 503-522). Cham, Switzerland: Springer International Publishing. doi: https://doi.org/10.1007/978-3-319-53817-4_19
    • Gadidov, B., Le, Linh. (2018, April). A case study of mining social media data for disaster relief: Hurricane Irma. Paper presented at SAS Global Forum 2018, Denver, CO. Retrieved from here.
    • Gadidov, B., Zhang, L., & Zhou, Y. (2017, September). Reducing traveling times for the Cobb County Fire Department. Poster session presented at SAS Analytics Experience 2017, Washington, DC.
    • Gadidov, B., & Ray, H. E. (2017, April). Analyzing residuals in a PROC SURVEYLOGISTIC model. Paper presented at SAS Global Forum 2017, Orlando, FL. Retrieved from here.
    • Gadidov, B., & McBurnett, B. (2015, September). Population stability and model performance metrics replication for business model at SunTrust Bank. Paper presented at SouthEast SAS Users Group 2015, Savannah, GA. Retrieved from here.

    Service and Awards: SAS Analytics Student Poster Competition, October 2014; Recognized as one of six SAS Analytics Student Poster winners.

    Professional Objective: My short term goal after completing my studies would be to apply my knowledge in a data science team in an industry setting. My longer term goal is to have a faculty position at a university to continue teaching.

    LinkedIn

     

     Jie

    Name: Jie Hao

    Bachelor’s Degree: Statistics, North China University of Technology

    Master’s Degree: Mathematics, East Tennessee State University (ETSU)

     Work History:

    • Math tutor at ETSU
    • Research assistant at the department of Biostatistics and Epidemiology at ETSU.

    Courses taught: STAT 8030 Programming in R (graduate level), Fall 2016, Kennesaw State University

    Publications:

    • Shah, Lisa; Hao, Jie; Schneider, Jeremy; Linenberger, Kimberly; Ray, Herman; Rushton, Gregory. (2017) Repairing Leaks in the Chemistry Teacher Pipeline: A Longitudinal Analysis of Praxis® Chemistry Subject Assessment Examinees and Scores. The Journal of Chemical Education. Under review.
    • Lisa Shah, Jie Hao, Christian A. Rodriguez, et al. (2017) Analysis of Praxis physics subject assessment examinees and performance: Who are our prospective physics teachers? Physical Review Physics Education Research. Under review.
    • Le, L., Hao, Jie. , Xie, Y. and Priestley, J. (2016) Deep Kernel: Learning Kernel Function from Data using Deep Neural Network. BDCAT’16, December 06-09, 2016, Shanghai, China. doi: http://dx.doi.org/10.1145/3006299.3006312.
    • Godbole, A. and Hao, Jie. (2016) Telescoping Sums, Permutations, and First Occurrence Distributions. The Mathematical Scientist, 41, 75-83.
    • Hao, J. and Godbole, A. (2016) Distribution of the Maximum and Minimum of a Random Number of Bounded Random Variables. Open Journal of Statistics, 6, 274-285. doi: 10.4236/ojs.2016.62023.

    Presentations: Presented a breakout session at SAS Global Forum 2017, Orlando, Florida

    Service and Awards: SAS Base and Advanced Certification

    Professional Objectives: Personal career goal is to find a data scientist position in a high-tech company. My research interests are machine learning, and deep learning in bioinformatics

     

     

     Linh

    Name: Linh Le

    Bachelor’s Degree: Engineer Degree in Information Technology, Focus on Computer Network and Telecommunication, Hanoi University of Science Technology

    Master’s Degree: Master of Science in Information Systems, Marshall University

    Courses taught: STAT 3010 Computer Application of Statistics, Fall 2016, Kennesaw State University 

    Selected Publications/Presentations:

    • Ying Xie, Linh Le, Yiyun Zhou, Vijay Raghavan, Deep Learning for Natural Language Processing, Computational Analysis and Understanding of Natural Languages, 2018
    • Bogdan Gadidov, Linh Le, A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma, In Proceedings of SAS Global Forum 2018
    • Ying Xie, Linh Le, Jie Hao, Unsupervised Deep Kernel for High Dimensional Data, In Proceeding of the 30th IEEE International Joint Conference on Neural Networks
    • Linh Le, Jie Hao, Ying Xie, Jennifer Priestley, Deep Kernel: Learning the Kernel Function from Data Using Deep Neural Network, In Proceedings of the Third IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
    • Ying Xie, Chenna Pooja, Linh Le, Visualization of High Dimensional Data in a Three Dimensional Space, In Proceedings of the Third IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
    • Linh Le, Jennifer Priestley, Using the OPTGRAPH Procedure: Transformation of Transactional Data into Graph for Cluster Analysis, In Proceedings of SAS Global Forum 2017

    Service and Awards:

    • Best Paper in Research Track, Southern Data Science Conference 2018
      Ph.D. Research and Publication Award, Analytics and Data Science Institute, Kennesaw State University, 2017
    •  Winner in the student poster competition – SAS Analytics Experience 2016 Conference
      First Place in the HPCC Systems 2016 Poster Presentation Competition – HPCC Systems Engineering Summit in 2016
    • Xie, Y., Le, L., and Zhou, Y. (2017) Dual Deep Learning Framework for Big and Unstructured Data. US Patent Application No. 62562898

    Professional Objectives: I like doing research in an academic environment, so I plan to find a faculty position in a university.

    LinkedIn

     

     Bob

    Name: Bob Vanderheyden

    Bachelor’s Degree: Applied Mathematics, San Diego State University

    Master’s Degree: Mathematics, Virginia Tech

    Work History:

    • 25+ years at various companies, providing Analytic Support to Marketing efforts.
      Current employer: IBM

    Professional Objectives: Faculty position at a university

    LinkedIn

     

 

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