Master of Science in
Data Analytics (Big Data)

Mainak Chatterjee is an Associate Professor in the Department of Computer Science with secondary joint appointment in the Department of Electrical and Computer Engineering at the University of Central Florida. He received his Ph.D. from the department of Computer Science and Engineering at the University of Texas at Arlington. He received his M.E. degree in Electrical Communication Engineering from the Indian Institute of Science. Prior to that, he did his B.Sc. in Physics from Presidency College, University of Calcutta.

His primary research interests are in the broad areas of computer networking and mobile computing, particularly economic issues in wireless networks, applied game theory, cognitive radio networks, dynamic spectrum access, and mobile video delivery.

He co-founded the ACM Workshop on Mobile Video (MoVid). He serves on the editorial board of several journals. He has served on the executive and technical program committee of several international conferences. He is the recipient of the AFOSR sponsored Young Investigator Program (YIP) award.

He is one of the Director's for the Networking and Mobile Computing Lab (NetMoC) at UCF.

Dr. Ivan Garibay earned his PhD degree at the Computer Science Department at the University of Central Florida, Orlando, where he is currently Director of Research Information Systems and Chief Information Officer at the Office of Research and Commercialization, Assistant Professor at the Institute for Simulation and Training, and Joint Faculty at the Department of Electrical Engineering and Computer Science. He received his MSc in Computer Science degree also from the University of Central Florida. He earned his BS degree in Electronic Engineering in 1994 from the Ricardo Palma University with the highest honors and ranked first in his class. He currently directs the UCF complex adaptive systems research group. Dr. Garibay has a multidisciplinary research agenda focused on novel biologically inspired models of computation that includes the fields of evolutionary computation, artificial life, artificial intelligence, machine learning, self-organization, and its application to economic and social phenomena with focus on economic impact of innovation ecosystems on regional economies. He has received the Hillman Award for excellence in PhD research from the University of Central Florida in 2003. He has organized four international workshops as part of the GECCO conference: "complexity through development and self-organizing representations" (2006), and "self-organization in representations for evolutionary algorithms" (2005,2004).

He has co-chaired and hosted at UCF the Foundation of Genetic Algorithms international conference, FOGA (2009) and will be chairing and hosting Swarmfest 2013 (one of the oldest agent-based modeling communities). Dr. Garibay has more than fifteen years of experience in consulting in computer and information systems for higher education with seven copyrighted software systems for research administration. He is a committee member of the largest conference in the field of genetic and evolutionary computation, the Genetic and Evolutionary Computation Conference (ACM-SIGEVO) since 2002, and of the International Symposium of Innovation and Technology since 2010. He is a member of AAAI, AAAS, IEEE, ACM and SIGEVO. He has served as a reviewer for the journal of Genetic Programming and Evolvable Machines (Springer), the Evolutionary Computation Journal (MIT), the IEEE Transactions on Evolutionary Computation (IEEE Press), IEEE Transactions on Parallel and Distributed Systems (IEEE Press), and Neural Networks Journal (Elsevier) and for the Fundamental Research on Matter (FOM), the largest government-supported physics organization in the Netherlands.

Dr. Glinos holds a B.S. degree in Physics and Mathematics from Trinity College (Connecticut), a J.D. (law) degree from Georgetown University, and both M.S. and Ph.D. degrees in Computer Science from the University of Central Florida, with a research specialization in natural language processing, a branch of artificial intelligence. Dr. Glinos is currently the managing member of Advanced Text Analytics, LLC, and has previously worked as a simulation and software engineer for Martin Marietta (now Lockheed Martin), a research scientist for Science Applications International (SAIC), and also managed his own solo law practice in Orlando, Florida. He is currently a member of the Association for Computational Linguistics (ACL), the Association for the Advancement of Artificial Intelligence (AAAI), and American Mensa, Ltd., and is a member of the bar (inactive) in New York, Colorado, Washington, D.C., and Florida.

Haiyan Hu is an associate professor in the Department of Electrical Engineering and Computer Science. Her research focuses on bioinformatics, computational biology, data mining, machine learning and pattern recognition. One of her areas of expertise is combining data mining and developing computer algorithms to help biologists solve human health problems. She has more than $1 million in grant funding from the National Science Foundation and was awarded an NSF Career Award in 2012. She has published dozens of research papers applying informatics to health care questions.

Dr. Kien A. Hua received a B.S. degree in Engineering Computer Science from the University of Illinois at Urbana-Champaign, in 1982, where he wasranked in the top one percent of his graduating class. In the summer of 1983, he designed and implemented for International Business Machine (IBM) Corporation a logic synthesis system for VLSI circuits. As a result of this work, the company granted him a $75,000 monetary award to support Ph.D. research on the topic of his choice. Upon returning to the University of Illinois, he completed the M.S. and Ph.D. degrees in Electrical Engineering in 1984 and 1987, respectively.

Facing the severe downturn in the mainframe business, the Exploratory Systems Group at IBM hired Dr. Hua in 1987 to conceptualize and to design a future-generation mainframe computer. His design later became a series of IBM products. When the product was announced in 1991, it was called InPAC (Integrated Parallel Accelerator). This was a precursor to the series of products known as SPx (e.g., SP1, SP2, etc.) which are the most successful commercial MPP (Massively parallel processor) product line on the market. While with IBM. Dr. Hua was also involved in designing high-performance processors. His work led to an important patent for IBM and earned him a Best Paper Award from 1990 IEEE International Conference on Computer Design. Besides conducting several successful research and development projects at IBM, Dr. Hua organized, and served as the Program Chair, the IBM Internal Symposium on Cache Design for Mainframe Computer Systems held in Kingston, New York, in 1988. In the same year, he was selected to the IBM Executive Resource Program.

In 1990, Dr. Hua was recruited by the Univeristy of Central Florida (UCF) to head-up its database program. Last year, he was appointed the first Director of a newly created Database Systems Laboratory. Ten graduate students, mostly Ph.D. candidates, are currently working in this laboratory under his supervision. Their work primarily focuses on multimedia servers, parallel database systems, and object-oriented databases. This group is currently prototyping a parallel database management system on a 64-processor nCUBE/2 computer. They are also designing a large-scale video-on-demand server using a technology they developed called HOPE. These students, with Dr. Hua, have authored more than 30 refereed articles. Among them was a paper submitted to the International Conference on Parallel and Distributed Information Systems which was selected as one of the four best papers and appeared in a special issue (July 1993) of VLDB Journal.

Besides being a highly productive researcher, Dr. Hua is very active nationally as a reviewer, referee and consultant. He served in the program committee of the ACM SIGMOD 1995 International Conference on Management of Data. He is currently serving in the programming committee of the IEEE 1996 International Conference on Parallel and Distributed Information Systems. He is also involved in the planning for the 1998 IEEE International Conference on Data Engineering. Dr Hua is also an excellent speaker and instructor. He received, by an audience vote, the Best Presenter Award at the 1990 IEEE International Conference on Computer Design. These skills carry over into instruction in classrooms. In 1993, he was selected for a Teaching Incentive Award at UCF.

Dr. Hsin-Hsiung is an Assistant Professor in the Department of Statistics at University of Central Florida (UCF). Dr. Huang received his Ph.D. in Statistics from the University of Illinois at Chicago and two MS degrees from the Georgia Institute of Technology and National Taiwan University as well as BA and BS from National Taiwan University. His scholarly interests and expertise include Bayesian clustering, classification, genome comparison, robust dimension reduction, and text categorization. His research addresses challenges in analyzing big data in bioinformatics and cybersecurity by developing and evaluating new statistical methods. Examples of his research projects include classifying multiple-segmented viruses, discovering the association of biomarkers and hypertension, as well as business intelligence classification. Dr. Huang has been awarded the 2013 Taiwanese study-abroad student research award when he was a doctoral student at UIC, and the 2016 In-House grant at UCF.

Dr. Sumit K. Jha is the Charles N. Millican Assistant Professor of Computer Science at the University of Central Florida, Orlando. His research interests include high-performance computing, data analytics, algorithms, formal methods, hybrid and stochastic systems. He has applied his fundamental research on these topics to applied problems in computational systems biology, cyber-physical systems, cyber-security, and computational finance.

Dr. Jha received his Ph.D. in Computer Science with Dr. Christopher James Langmead at Carnegie Mellon University. Before joining Carnegie Mellon, he graduated with B.Tech (Honors) in Computer Science and Engineering from the Indian Institute of Technology Kharagpur. Dr. Jha holds a Certificate in Quantitative Finance and is a member of the Alpha Quant Club - a network of academicians and industry leaders interested in mathematical finance.

Dr. Jha has worked on R&D problems at Microsoft Research, General Motors and INRIA, France. His research has been supported by the Oak Ridge National Laboratory and the US Air Force Research Laboratory. He is an elected full member of the Sigma Xi and is a recipient of the IEEE Orlando Engineering Educator Excellence Award.

Daoji Li is an Assistant Professor in the Department of Statistics at the University of Central Florida. He was a postdoctoral research associate in the Marshall School of Business at the University of Southern California from 2012 to 2015. His research interests include big data analytics, data mining, machine learning, precision medicine, high-dimensional data analysis, longitudinal data analysis, and survival analysis. He is also interested in developing statistical tools to solve practical problems. He was the winner of SAS 2017 Analytical Shootout Competition. He has received the UCF In-House grant in 2017 and the Overseas Research Scholarship from UK Secretary of State for Education and Sciencein 2006.

Dr. Fei Liu is an assistant professor of Computer Science at the University of Central Florida. Dr. Liu’s research areas are in natural language processing, machine learning, and data mining, with special emphasis on automatic summarization and social media. From 2013 to 2015, Dr. Liu was a postdoctoral fellow at Carnegie Mellon University, member of Noah's ARK. From 2011 to 2013, she worked as a senior research scientist at Bosch Research, Palo Alto, California, one of the largest German companies providing intelligent car systems and home appliances. Dr. Liu received her Ph.D. in Computer Science from the University of Texas at Dallas in 2011. Prior to that, she obtained her Bachelors and Masters degrees in Computer Science from Fudan University, Shanghai, China. Dr. Liu has published over twenty peer reviewed articles, and she serves as a referee for leading journals and conferences.

Sumanta N. Pattanaik is an associate professor of computer science at the University of Central Florida. His research interests include real-time realistic rendering using programmable graphics hardware. Pattanaik received a PhD in computer science from Birla Institute of Technology & Science, India. He is a member of the IEEE.

Dr. Nizam Uddin earned his Ph.D in Statistics in 1989 at Old Dominion University. He enjoys research and consulting including, design and analysis of experiments, linear/nonlinear models, analysis of variance/covariance, regression analysis and categorical data analysis.

I am an assistant professor at Department of Electrical Engineering and Computer Science in University of Central Florida. I received Ph.D. at the Beckman Institute and the Department of Electrical and Computer Engineering in the University of Illinois at Urbana-Champaign. My current research interests include machine learning and data mining. In particular, I am interested in developing highly reliable knowledge and information acquisition, processing and analysis systems involving data sources of multiple modalities. Such systems are able to effectively aggregate and leverage knowledge in an open connected environment (e.g., social, sensor and mobile networks). My research seeks to develop computational model and theory for such general-purpose knowledge and information systems.

Varadraj Gurupur, Ph.D., is currently working as an assistant professor in the Department of Health Management and Informatics at the University of Central Florida. He was previously employed with the School of Medicine, University of Alabama at Birmingham as a data manager, and later as an information systems specialist, for its Alzheimer's Disease Research Center.

His main area of research is improving information systems for health and biomedical informatics. He has developed innovative prototypes that present new methodologies that can be used in the development of these information systems. Based on these prototypes, he has published articles that have been indexed in PubMed. Gurupur's articles have been published in the Journal of Medical Systems, Expert Systems with Applications, Advances in Engineering Software and IEEE Transactions on Learning Technologies. He received his Ph.D. in computer engineering from the University of Alabama at Birmingham in 2010.

Dr. Gita Sukthankar received her Ph.D. in 2007 from the Robotics Institute at Carnegie Mellon, an M.S. in Robotics, and an A.B. in psychology from Princeton University. From 2000-2003, she worked as a researcher at Compaq Research/HP Labs (CRL) in the handheld computing group. In 2009, Dr. Sukthankar was selected for an Air Force Young Investigator award, the DARPA Computer Science Study Panel, and an NSF CAREER award. She is a UCF Charles N. Millican faculty fellow, the 2011 CECS Distinguished Researcher (asst professor), and a 2015 recipient of UCF's Reach for the Stars research award. Her dissertation research proposed the first framework for dynamic multi-agent plan recognition (MAPR), extending on work from her AAMAS 2005 best student paper on cost minimization methods for human behavior recognition. She is the lead editor of Plan, Activity, and Intent Recognition: Theory and Practice.

Morgan C. Wang received his Ph.D. in 1991. Since then he has been with University of Central Florida, where he is the Director of Data Mining Program and Professor of the Department of Statistics. He is an elected member of International Statistical Association and a member of American Statistical Association and International Chinese Statistical Association.

He has published one book (Integrating Results through Meta-Analytic Review Using SAS Software, SAS Institute, 1999), and over 80 papers in referee journals and conference proceedings on topics including interval analysis, meta-analysis, computer security, business analytics and data mining. He won the best conference award in the First Annual Conference on Engineering and Technology Innovation in 2008. He was the first prize-winner in Data Mining Competition of the 11th SIGMOD KDD conference in 2004 and the first prize winner in Data Visualization Contest of SUGI 25 conference in 2000, and was given invited talks for more than eighty times for American Statistical Association, SIGKDD International Conference, SAS Global Forum, and many universities around the world.

Dr. Wang received many grants from National Science Foundation (NSF), NASA, Florida Department of Transportation, Disney, Sodexho Food Services, BlueCross & BlueShield of Florida, Everbank, MD Anderson Cancer Research Center and many local and international businesses.

Liqiang Wang received his Ph.D degree in Computer Science from Stony Brook University in 2006. Prior to joining the Department of Computer Science at the University of Central Florida as an Associate Professor in 2015, he was an Assistant Professor and Associate Professor in the University of Wyoming during 2006-2015. He also was a visiting Research Scientist in IBM T.J. Watson Research Center during 2012-2013.

He is currently the director of Big Data Computing Lab. His research interest is the design and analysis of big data systems. For the aspect of design, he is currently working on optimizing performance, scalability, and resilience of big data systems, especially on Cloud, GPU, and multicore platforms. For the aspect of analysis, he focuses on using program analysis to detect programming errors and performance defects in large-scale parallel computing systems. He also works on distributed machine learning. He received an NSF CAREER Award in 2011, Castagne Faculty Fellowship (2013-2015), and Overseas Scholars Collaborative Research Award by Natural Science Foundation of China in 2014.