Robert Finn, Ph.D.
Assistant Professor, Data Science Institute
Office: Loyola Hall, Room 11, Jersey City Campus
Professor Finn is a published researcher specializing in Data Science, Machine Learning, Statistical Modeling, and Stochastic Processes. He received his Ph.D. in Mathematics and is on track to receive his Ph.D. in Computer Science in 2018. Prior to joining the faculty at Saint Peter’s University in 2016, he spent over a decade in industry as a quantitative analyst concentrating in algorithmic trading and portfolio construction. He has consulted for hedge funds and major brokerages and exchanges, as well as for institutional investors. Professor Finn has extensive experience designing, developing, and implementing customized distributed algorithmic equity trading software in Java, C++, and C. He was a lead researcher in charge of concept development, design, statistical testing, implementation, and daily performance analysis of proprietary algorithmic trading solutions deployed on multiple platforms. In addition, he has led quantitative portfolio management and algorithmic trading programs for multi-billion dollar institutional investors.
Office: Loyola Hall, Room 10, Jersey City Campus
John Wang, Ph.D.
Professor Wang received his Ph.D. in Operations Research from Temple University, prior to which he received an M.S. in Systems Engineering from Harbin Institute of Technology in China and worked at Beijing University of Science and Technology. At Montclair State University, he obtained tenure and was promoted to full professor. Dr. Wang has also developed computer software based on his research findings.
Dr. Wang has made many contributions in the constantly-evolving field of Data Science. Serving as Editor-in-Chief for several peer-reviewed academic journals, he has fostered the development and dissemination of research. These journals include the International Journal of Business Analytics, International Journal of Data Science, International Journal of Data Mining, Modeling and Management, International Journal of Data Analysis Techniques and Strategies, and International Journal of Information Systems and Supply Chain Management.
Dr. Wang is also the Editor of several scholarly publications, such as the Encyclopedia of Business Analytics and Optimization (five volumes), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (six volumes), Encyclopedia of Data Warehousing and Mining, 1st edition (two volumes) and 2nd edition (four volumes). His long-term research goal focuses on the synergy between data mining, operations research and business intelligence.
Gerardo Menegaz, M.S.
Professor Menegaz is a Chief Architect within IBM’s Global Technology Services, Financial Service Sector business. Professor Menegaz brings with him over twenty years IT leadership experience formulating strategies and exploiting proprietary technologies in fast-paced, challenging environments. In addition, he is a published author who comprehends evolving business strategies across multiple industries as well as emerging technologies (e.g., Cloud Computing, Mobile (BYOD), Big Data, Analytics, Social Media), as well as Data Center topics (e.g. Server Consolidation, Virtualization, and Optimization technologies, methodologies, application rationalization, and logical consolidation techniques). He is a graduate of the University of California, Santa Barbara and is fluent in Spanish.
Jane Cheng, M.S.
Professor Cheng received her double masters in Electrical and Computer Engineering and Physics in NJIT. Prior to teaching, she worked for Wall Street companies including Merrill Lynch, Barclays Capital, Wells Fargo, Credit Swiss as well as MetLife Insurance. Professor Cheng has extensive industrial experience in software programming such as .net, Java, Perl and Unix as well as in application design and development. Additionally, she has strong expertise in database and data warehousing. She most recently led the boarding of option regulatory bridge data from Chicago Board of Trade to FINRA using cloud computing. Her interests also include mobile technology and she is the founder of innovation.com, which helps people design websites and use Apple products.
Hakan Gogtas, Ph.D.
Professor Gogtas has over ten years of progressive banking and consulting experience in financial risk management, credit risk, model validation, fraud detection, statistical modeling and simulations. He has leadership experience in managing professional teams, advisory engagements, and cross-functional working groups. He has a PhD degree from University of Pittsburgh and an MS degree from University of Michigan.
Dr. Gogtas is currently leading the Model Risk Governance team in American Express. Prior to joining American Express, he led a PD and CCAR modeling team in State Street, where he was responsible for building and maintaining over 30 different models and interacting with the internal and external regulators. Prior to this role, he was a manager with PricewaterhouseCoopers where he was leading advisory and audit engagements for Financial Institutions.
Jennifer Woods Burke, J.D.
Professor Woods Burke has extensive experience representing and providing legal and compliance guidance to financial service firms throughout the continental United States. She has worked for large and small financial institutions on internal investigations, regulatory examinations, drafting policies and conducting risk assessments. She received a Bachelor in Political Science from Providence College and a law degree from New York Law School. Her interests include data law and data ethics.
Sase Govindan, M.S.
Professor Govindan earned his BSc in Computer Science from Coventry University, UK and MSc in Information Management from Stevens Institute of Technology. He is a highly accomplished system and infrastructure engineering professional, who has designed, implemented and supported critical business applications and infrastructure and is leading the Infrastructure Engineering Department at Verisk Analytics. He is currently focusing on real-time infrastructure analytics, problem identification and resolution with traffic-based intelligence and infrastructure visualization. Under his leadership, the infrastructure team has successfully implemented real-time network maps and traffic analytics infrastructure utilizing open source and vendor based products and services.
Nigel DeFreitas, M.S.
Professor DeFreitas specializes in a wide variety of GIS enabled Insurance Risk Management, and Fraud Prevention Systems deployed on technologies ranging from Mainframe (zOS/zLinux), to distributed systems (Windows/Linux). His most recent areas of exploration include Amazon Cloud services, DataRobot, Entity & Relationship Resolution, and Elastic Search. His education includes a BFA in Graphic Design from the Rochester Institute of Technology and a MSIS from Stevens Institute of Technology. He also enjoys competing in sprint distance Triathlons, playing competitive Foosball and building Apple iOS applications.
Douglas Bedard, MBA
Professor Bedard received an MBA in Management Information Systems from the Lubin School of Business, Pace University and a BBA in Finance from Hofstra University.Professor Bedard led the Enterprise Information Management COE for Avon Products, a global function supporting over 70 countries in the areas of architecture, governance, master data, data warehousing and business intelligence. He directed a team in implementing a leading edge warehouse appliance platform.
Additionally, he was instrumental in establishing and running data management organizations at Vertrue Inc and Bristol Myers Squibb. He started his IT career at Dun & Bradstreet where he gained experience in all aspects of Information technology including operation support, architecture, web development, as well as IT process and project management office.
One common thread throughout his career has been supporting and managing data assets in dynamic environments.
Advisory Board Members
The Data Science Advisory Board exists to advise, assist, support and advocate for the graduate program in Data Science With a Concentration in Business Analytics. Members are volunteers who share an expert knowledge and will serve as a sounding board for senior University executives and as a body that can inspire change. Advisory Board responsibilities include:
- Provide general guidance and advice relevant to industry trends surrounding Big Data and business intelligence.
- Review and, when appropriate, recommend updates to our Data Science curriculum.
- Develop and recommend “best practice” technology approaches.
- Provide introductions to possible strategic partners and sources of funding, and participating in meetings with such individuals or entities.
- Contribute ideas and information about the use of Big Data in various industry verticals.
- Develop global program marketing concepts, in concert with University marketing team.
- Develop internship and career opportunities for University students and graduates.
- Suggest possible Data Science conference or webinar concepts.
Ray Chiu ’86
former Vice President Software Development, ISO
Vice President of Corporate Repositories and Architecture portfolio, UPS
Engineering Manager, Oracle America Inc.
Financial Services Sector CTO, IBM
Chief Scientist, Dstillery
Vice President Health Value Analytics and Development, Pfizer Inc.
Director of Analytics, Quanttus
Vice President, Weather Analytics, The Weather Channel