Data Science Faculty - Office of Professional Programs

Ergun Simsek, Ph.D. | Data Science Graduate Program Director

Ph.D., Electrical and Computer Engineering, Duke University
M.S., Electrical and Computer Engineering, University of Massachusetts Dartmouth
B.S., Electrical and Electronics Engineering, Bilkent University (Ankara, Turkey)

Dr. Ergun Simsek earned his Ph.D. from Duke University in 2006 and worked as a post- doctoral research associate at Schlumberger Doll Research Center for the following two years. From 2008 to 2017, he was a faculty member at Bahcesehir University (Istanbul, Turkey) and the George Washington University (Washington, DC). In addition to teaching at both undergraduate and graduate levels, he also conducted research on scientific computing for different applications in electromagnetics, photonics, geophysics, material science, and data science. His research was supported by different agencies such as National Science Foundation, TUBITAK, and European Union Research Council. He has published more than 30 peer-reviewed journal papers and made more than 60 presentations at international conferences. He continues researching how to solve emerging engineering problems through efficient and robust computational techniques.

Before joining UMBC, Dr. Simsek was a manager for Exponent, where he teamed up with engineers, scientists, and regulatory specialists for solving challenging problems of consumer electronics, medical device, and IoT appliance manufacturers. Dr. Simsek is a senior member of IEEE and a licensed Professional Engineer.

Tony Diana, Ph.D. | Adjunct Instructor

Ph.D., Policy Sciences, UMBC
M.S., Policy Sciences, UMBC

Tony Diana is the Division Manager, NextGen Collaboration and Messaging at the Federal Aviation Administration. NextGen refers to advanced technologies supporting satellite-based navigation. As the Division Manager, NextGen Performance, he was involved in measuring and reporting operational outcomes from NextGen programs implemented throughout the National Airspace System. His main interests are machine learning applications to aviation, Natural Language Processing, performance evaluation and benchmarking. He received twice the Best Paper Award from the Transportation Research Forum. He is a member of the Aviation Economics and Forecasting subcommittee at the Transportation Research Board of the National Academies of Sciences, Engineering and Medicine. He is a Certified Lean Sigma Master Black Belt, a Certified Change Management Specialist, a Scrum Master, and a certified Project Management Professional.

Darin Johnson, Ph.D. | Adjunct Instructor

Ph.D., Mathematics, Southern Illinois University, Carbondale
B.S., Computer Science, Eastern Illinois University

Darin Johnson is an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering (CSEE). He works for the Department of Defense (DoD) as an applied mathematician, where he focuses on applying data science techniques to DoD specific problems. He’s particularly interested in large scale data analysis, streaming applications and anything related to graph theory. Prior to working for DoD, he was a professor at Delaware State University, where he taught mathematics and studied probabilistic combinatorics and random graphs.

Darin graduated from Eastern Illinois University with a B.S. in Computer Science. He completed a Ph.D. in Mathematics at Southern Illinois University, Carbondale.

Jim Kukla | Adjunct Instructor

M.S., Computer Science, UMBC
B.S., Computer Science, UMBC

Jim Kukla, an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering since 2014, has nearly 20 years of experience as a software developer, researcher, and educator. He co-founded and is the current CTO of RedShred, a software development company focused on helping business users extract critical information from unstructured text documents. In addition to years of experience with software engineering, he also has a strong background in management and leadership as well as a wide variety of development frameworks and languages (including reactjs, django, python, javascript, C++, C, java, lisp, mysql, postgresql, mongodb, elastic, and more).

He graduated from UMBC with a B.S. in Computer Science in 1997 and continued on in the department, earning his M.S. in 2000. His areas of focus included 3D graphics, visualization, and animation. In addition, he was an active member of Upsilon Pi Epsilon and the Computer Science Council of Majors. Jim brings a strong understanding of Machine Learning, Deep Learning, and NLP to the Data Science department at UMBC.

Adam Lippe, J.D. | Adjunct Instructor

J.D., University of Maryland Francis King Carey School of Law
B.S., Political Science, The Johns Hopkins University

Mr. Lippe is a career prosecutor who serves as the Chief of the Economic Cyber Crimes Unit, as well as the Animal Abuse Unit for the Baltimore County State’s Attorney’s Office (a jurisdiction of over 800,000 people). In this role he manages direct reports and personally works on complex embezzlements and frauds, including identity theft, internet scams, check and credit card frauds, large material thefts, organized retail crime, financial exploitation of vulnerable adults, entitlement fraud, animal cruelty, in addition to handling murders. He was a district and juvenile court prosecutor, before heading to violent crime and narcotics for many years before his current position. Mr. Lippe has been an adjunct faculty member at UMUC, as well as both the University of Maryland School of Law and University of Baltimore School of Law and several other local colleges and universities helping to teach undergraduate and graduates both on-campus and on-line. He also was a frequent lecturer at the National Advocacy Center in Columbia, South Carolina for the National District Attorney’s Association. Licensed in both the state of Maryland and New Jersey, Mr. Lippe is an alumni of the University of Maryland School of Law and The Johns Hopkins University in Baltimore, Maryland.

Amen Ra Mashariki, Ph.D. | Adjunct Instructor

Ph.D., Information Engineering, Morgan State University
M.S., Computer Science, Howard University
B.S., Computer Science, Lincoln University

Amen Ra Mashariki, an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering, leads Urban Analytics at Esri. Esri is a digital mapping pioneer that builds big data and analytics software that provides location intelligence and insights for almost every industry.

As the head of Urban Analytics at Esri, Dr. Mashariki is responsible for the messaging and strategy for applying data science principles to urban challenges, ensuring that data-driven decision makers will realize impactful and positive outcomes in urban policy and operations. Previously Dr. Mashariki was Chief Analytics Officer for the City of New York and the Director of the Mayor’s Office of Data Analytics. He ran the civic intelligence center that allowed one of the largest cities in the world to aggregate and analyze data from across agencies.

In 2012, Dr. Mashariki was one of eleven individuals appointed by the President of the United States to the 2012-2013 class of White House Fellows. Immediately after the Fellowship he was appointed the Chief Technology Officer for the Office of Personnel Management.

Dr. Mashariki currently serves as a Fellow at the Harvard Ash Center for Democratic Governance and Innovation.

Selim Mimaroglu, Ph.D. | Adjunct Instructor

Ph.D., Computer Science, University of Massachusetts Boston
M.S., Computer Science, University of Massachusetts Boston
B.S., Electrical and Electronics Engineering, Hacettepe University

Dr. Selim Mimaroglu is a Data Science Manager at Oracle. He earned a PhD degree in computer science from University of Massachusetts Boston in 2008. Dr. Mimaroglu has published peer reviewed articles on frequent item set detection, clustering, combining multiple clusterings, sequential pattern mining, genetic algorithms, automated valuation models, churn management, text mining, and recommender systems. In recognition of his work, he received: “Award of Excellence” from the US Federal Government and “Outstanding Achievement in Computer Science” from University of Massachusetts. Dr. Mimaroglu received funding from private organizations and government bodies for conduction research and building proof of concept implementations in the areas of bundling, pricing and churn management. Dr. Mimaroglu worked as an Associate Professor at Bahcesehir University and Okan University in Istanbul.

Ben Payne, Ph.D. | Adjunct Instructor

Ph.D., Physics, Missouri University of Science and Technology
M.S., Physics, Missouri University of Science and Technology
B.Sci., Applied Mathematics, Engineering, and Physics, University of Wisconsin at Madison

Ben Payne, an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering (CSEE), is a scientist focused on applications of data science to challenges in the Department of Defense (DoD) where he is a computer systems researcher in the area of High Performance Computing (HPC).

At the DoD, Ben’s focus is on identifying new technologies and opportunities in HPC to enhance mission capabilities. This includes evaluating technical proposals for research investment, establishing baseline system requirements, as well as writing mission related software (he particularly enjoys creating Python code and Bash scripts for data analysis). Prior to working at the DoD, Ben developed software for Physics simulations and utilized large scale computers for those calculations. In addition to his extensive computational experience, Ben was an aircraft mechanic in the Air National Guard, deploying overseas twice.

Edward Raff, Ph.D. | Adjunct Instructor

Ph.D., Computer Science, UMBC
M.S., Computer Science, Purdue University
B.S., Computer Science, Purdue University

Dr. Edward Raff is an adjunct instructor of Computer Science at the University of Maryland, Baltimore County. Edward is currently working as a Senior Lead Scientist at Booz Allen Hamilton.

He received his Ph.D. in Computer Science from UMBC in 2018, and a M.S. and B.S. from Purdue in 2013 and 2012. Dr. Raff’s research includes work in new methods for malware detection and similarity analysis, high-performance machine learning, biometric fingerprint recognition, and algorithmic fairness. In his spare time, he is also the author of the JSAT machine learning library.

Patty Stanton | Adjunct Instructor

Patty Stanton, an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering (CSEE), is a Data Scientist with over twenty years of database engineering, business intelligence, and analytics experience.

She performs as a lead Data Scientist to support analytic and machine learning efforts in the Advanced Data Analytics Lab at the Social Security Administration. She holds a Master of Science in Analytics from Texas A&M University and a Bachelor/Master of Science in Information Systems from American Sentinel University. She has numerous IT certifications to include Microsoft Certified Application Developer and Microsoft Certified Database Administrator. She is a frequent guest speaker at community data science related events.

In 2017, she was awarded the Texas A&M Margaret Sheather Memorial Award in Analytics for her Capstone Project, “Using Decision Trees to Analyze Patterns in Disability Fraud.”

Her interests are machine learning, text mining, and using GPUs/distributed processing to improve the performance of analyzing and processing big data. She is proficient in SQL, C#, SAS, R, and Python. She has worked with a variety of database systems to include SQL Server, Oracle, DB2, Hadoop, and Sqlite.

Jared Sylvester, Ph.D. | Adjunct Instructor

Ph.D., Computer Science, University of Maryland
M.S., Computer Science, University of Maryland
B.S., Computer Science, University of Notre Dame

Jared Sylvester, an adjunct instructor with UMBC’s Department of Computer Science and Electrical Engineering (CSEE), has been programming computers for almost two dozen years and conducting scientific research for the last fifteen. Jared is currently a data scientist with Booz Allen Hamilton’s Strategic Innovation Group. His work at Booz Allen focuses on machine learning research, which has lead him to publishing papers on deep learning for non-traditional data types including malware detection as well as the development of new machine learning algorithms to mitigate bias.

Prior to joining Booz Allen, Jared got his doctorate in AI at the University of Maryland. He worked in the Computer Science department doing neural network cognitive modeling, and in the Marketing department doing social network analytics. His dissertation focused on bridging the gap between traditional, symbolic cognitive modeling techniques and neurally-inspired, biologically grounded techniques.

When he is not doing research, Jared enjoys creating algorithmic art, and when he is not in front of a computer he likes to practice calligraphy.

Chaojie (Jay) Wang, D.Sc. | Adjunct Instructor
D.Sc., Information Systems & Communications, Robert Morris University
MBA, Finance, Loyola University Maryland
M.S., Statistics, M.A., Economics, The University of Toledo
B.E., Management Information System, Tsinghua University (Beijing, China)

Dr. Chaojie (Jay) Wang is a seasoned software engineer, systems architect, data scientist, researcher, and project manager with over thirty-year experience in industry, government, and academia. Dr. Wang currently works for The MITRE Corporation, an international thinktank and operator of several Federally Funded Research and Development Centers (FFRDC). In his capacity as a principal systems engineer, Dr. Wang advises the federal government on Health IT & Interoperability, Machine Learning & Data Analytics, IT Modernization & Acquisition, and Knowledge Management & Organizational Learning. Previously, Dr. Wang worked for Lockheed Martin Corporation and participated in the design and development of multiple large- scale IT systems for the federal government in various capacities including Chief Designer, Integrated Product Team (IPT) Lead, Scrum Master, and Chief Engineer.

Dr. Wang is a certified Java Programmer, certified Project Management Professional (PMP), and a certified SAFe Agilist (SA). Dr. Wang’s peer-reviewed publications cover diverse and interdisciplinary subjects including Data Analytics, Knowledge Management, Health IT, Big Data, Healthcare Analytics, and Artificial Intelligence. Dr. Wang currently serves on the Editorial Review Board for the International Journal of Patient-Centered Healthcare (IJPCH) by IGI Global and the Issues in Information System (IIS) by the International Association for Computer Information Systems (IACIS).

Waleed Youssef, Ph.D. | Adjunct Instructor

Ph.D., Computer Science, UMBC
M.S., Computer Science, The Pennsylvania State University
B.S., Engineering, Alexandria University

Waleed Youssef is an adjunct instructor in the UMBC’s Department of Computer Science and Electrical Engineering (CSEE). He joined UMBC as an adjunct instructor teaching graduate level data science classes. He uses his 20+ years of experience in the IT industry to provide students with professional engineering experience and hands-on experience in the field. Dr. Youssef works at IBM, as a Chief Architect. He joined IBM in 2008 after earning his Ph.D. degree from UMBC in Computer Science. Dr. Youssef also has a Master’s degree in Computer Science from Penn State University. His undergraduate studies were in Computer Engineering.

Dr. Youssef has many published research papers in cognitive computer and wireless sensor networks. His current work areas include cloud architecture, data science, AI, and IoT. His areas of expertise include Cognitive Computing, Data Science, and Artificial Intelligence.

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