Industrial Collaboration

Industrial Advisory Board

Jason Barbour - Erias Ventures, Data Works MD

Jason Barbour is the President and Founder of Erias Ventures, a government contractor focused on data science, software engineering, and system engineering, and Founder of Data Works MD, an organization focused on data science education and learning. With a drive for success and a passion for technology, he has developed big-data analytics, enterprise automation products, and operational cyber tools for a number of clients. In his work with Data Works MD, he has built a community of enthusiasts working together to share and learn about the wonders and science of working with data.

Michael Carlin - Boardroom Alpha

Michael A. Carlin is VP of Analytics at Boardroom Alpha, where he leads analytic efforts towards objectively and quantitatively assessing the performance of all US public company directors and officers. His technical expertise spans time series analysis, machine learning, natural language processing, and ETL/data engineering. As a data scientist, he has applied himself in a variety of domains, including information security, regulatory surveillance and compliance, anti-money laundering, and noise-robust speech and audio signal processing. He holds B.S. and M.S. degrees from Temple University, and a Ph.D. from Johns Hopkins University, all in Electrical and Computer Engineering. He is passionate about Baltimore, City Schools, and his community, and strives to bake the best backyard pizzas in Maryland.

Edward Fortunato - Exelon Corporation

Edward J. Fortunato is the Chief Economist of Exelon Corporation. As the Chief Economist, he tracks global and domestic economic forces, forecasts future economic trends, and analyzes how these patterns and events impact the company. Over the last eighteen years at Exelon, Edward has managed the proprietary trading book and the short-term analytics group. He has led the implementation of trading strategies in both the proprietary and hedging books and has run the fundamental analysis group.  Prior to working at Exelon, Edward served as the Vice President of Natural Gas Trading at Merrill Lynch Global Commodities and was a Senior Energy Trader at Edison Mission Energy. He originally started out in the oil business, trading oil, natural gas, and other commodities. Edward has an MBA with high honors in finance from Boston University and a BBA from Baruch College. He is an active community member and has been involved with Catholic Charities and Our Daily Bread Hot Meal Program since 2012.  He also currently serves on the Board of Directors for Partners in Excellence Scholarship Program and Marian House, and is the Chair of the Loyola University Maryland’s Data Science/Science Board of Directors.  Although a native New Yorker, Ed now lives in historic Ellicott City, Maryland with his wife, Sarah, and dog, Dozer.

Franklin Hernandez - Synchrony Financial

Franklin Hernandez currently works as a VP - Data Science & Governance for Synchrony Financial. Synchrony Financial is the largest provider of private label credit cards in the country and much of his work involves working with large data sets to improve the outcomes for the customer and business. He has a decade of experience working in the financial services industry having worked for Guggenheim Investments, Citi, PNC Capital Advisors, and Freddie Mac. His roles have included Risk Forecasting Analyst, Investment Risk Analyst, Credit Risk Analyst, and Portfolio Credit Manager. He has a BA in Economics from UMBC, an MBA - Finance and MS of Data Science both from Loyola University and is currently pursuing an MS of Artificial Intelligence at Johns Hopkins.

Daniel Hood - ClearEdge

Scott Jachimski - Booz Allen Hamilton

Scott Jachimski has more than 21 years of experience in the intelligence community and DoD, delivering strategic software applications, data science and AI/ML solutions to federal clients. His areas of expertise include cloud and geospatial algorithm development, data enrichment, change management and strategy, and analytic tradecraft acceleration. Scott currently focuses on enhancing Booz Allen’s analytic workforce and its capabilities. He and his team are developing approaches to incorporate data science and artificial intelligence capabilities into future client environments and solutions. He works with clients across the Federal Government helping them develop data science training programs for their workforces and prepare their agencies for broader data literacy. Scott is actively involved in the U.S. Geospatial Intelligence Foundation where he serves as co-chair for the Machine Learning and Artificial Intelligence Working Group. Scott serves on the Loyola University Data Science Industrial Board and has worked with Virginia Tech’s College of Science and Computer Science Resources Consortiums. Scott holds a B.S in computer engineering from Virginia Tech.

Kevin McMahon - Department of Defense

Ed Mullin - Think

Stephanie Poisson - MasterPeace Solutions

Stephanie L. Poisson is a highly talented technical expert with skills across the spectrum of artificial intelligence, including natural language processing, deep learning, and reinforcement learning. Both a hands-on programmer and a technical leader, she has not only created new methods in machine learning for autonomous cyber defense and complex language problems, but also, through leading a diverse team consisting of interns, senior researchers, and software engineers, built a multi-language event processing and reasoning system from a fledgling research project to a full-scale analytical processing engine used by customers. Ms. Poisson holds both a Bachelor’s of English Literature from the University of Illinois at Chicago as well as a Master’s of Science in Computational Linguistics from Georgetown University. After completing her M.S., she furthered her graduate studies at Georgetown , expanding her knowledge of both linguistics and machine learning, and conducted novel research in creating deep semantic-based natural language processing tools. A researcher and lifetime learner at heart, she is always searching for new methods of solving tough problems and constantly keeps her knowledge fresh by keeping up with the latest tools and technologies.

Elizabeth Rhoades - National Cryptologic School

Elizabeth Rhoades is the Data Science Curriculum Manager for the Department of Defense. She has over 15 years of experience in education and training, specifically in the areas of teaching methodology, language instruction, second language acquisition, and more recently, data literacy and data science.

Amit Kumar Singh - Asymmetrik

Amit Singh is the CTO and Co-Founder of Asymmetrik Ltd., a Maryland based technology firm focused on delivering high-impact software and analytic solutions to the Intelligence Community and major healthcare organizations.  Mr. Singh earned his B.S. Electrical Engineering degree from the University of Virginia after which he has served as a technical leader at a number of agencies to include NASA, White House, DARPA, and the Intelligence Community.

Joseph Warfield - The Johns Hopkins University Applied Physics Laboratory

Joseph D. Warfield is currently a principal statistician and Chief Scientist of the System Performance Analysis group in the Force Projection Sector at the Johns Hopkins Applied Physics Laboratory (JHU/APL). The work in the group focuses on testing and evaluation for Naval and Air Force programs. In addition, the group provides statistical consulting to programs across the Laboratory and to various government and defense agencies in the areas of experimental design, response surface methodology, nonlinear regression analysis, predictive analytics, and reliability-related methods. His current research areas focus on optimal design approaches for generalized linear model applications, Bayesian estimation of system reliability and risk quantification, and predictive analytics using structured and unstructured data sources. Dr. Warfield has taught courses on design of experiments and regression analysis through the Strategic Education program at JHU/APL. Dr. Warfield received a B.S. in mathematics from Loyola University, an M.S. in statistics from Virginia Polytechnic Institute, and a Ph.D. in statistics from University of Maryland, Baltimore County.

Data Science Projects from Spring 2024

• Predicting Bank Failure Using FDIC Bank Data by Vijay V.

• Data Science for Patient Safety—Never Event Response by Emma D.

• Bylaw Change Detection by Jason S.

• Decision Tree Predictive Analysis for Fault and Maintenance Log in Air Vehicle Sustainment by Leslie C

• Predicting Traffic Accident Severity in Montgomery County, Maryland by Jacob R.

• Assessing Predictability of a Composite Fatigue Score Using Linear Models by Derek D.

• The First Tee Greater Philadelphia—Understanding and Predicting Participant Retention by Catherine B.

• Targeting of Diabetes Prevention Programs—A Case Study for Supplementing NPO Strategic Decision-Making by Brian C.

• Product Category Classification and Recommendation System by Courtney R.

• Application of Random Forest Models to Detect Price Manipulation in Petroleum Import Markets – Cody R.

• Identifying Advantages in the Organic Certification Process Using Machine Learning Models – Christina R.

• Differentiating LLM and Student Authorship in Long-Form Text by Nolan C.

• Data Science for Community Solar—Predicting Net Revenue and Subscriber Allocations by Grace A.

• Credit Card Fraud Detection by Alex H.

• NBA Player Value—Evaluating Performance and Salary by Brendan W.

• Classification Comparative Analysis—Predicting Eye State Using Electrode Measurements from Electroencephalogram Signals – Vanessa G.

• Policy Analytics for Food System Challenges – Na’ol K.

Data Science Projects from Spring 2022

• Practical Data Analytics for Federal Financial Offices by Amanda M.
• Analyzing and Predicting NHL Games by Kyle L.
• Using Predictive Modeling to Estimate Individual Enrollment Outcomes by Clayton M.
• Predicting Successful Productive Trials by Eric R.
• Data Triage-Improving Searchability of Transcribed Nixon Tapes by Michelle B. and April C.
• Detection, Ranking, and Reporting of Material Changes to S-1 & S-1/A Filings by Tyler P.
• Query Expansion and Topic Modeling with Professional Biographies by Joseph S.
• On the Feasibility of a 1D Exocomet Transit Classifier for Time-Series Stellar Observations by Andrew C.
• An Investigation of Consumer Behavior Modeling Strategies for High-Dimensional Data by Erik W.

Data Science Project from Spring 2020

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