ANALYTICS - Key Persons
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science
- Adjunct Professor in the Data Science and Analytics Program at Georgetown University
- Data Science Associate Director
Abhijit Dasgupta is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. Abhijit received his PhD in Biostatistics from the highly-ranked University of Washington in Seattle, and continued postdoctoral training at the National Cancer Institute, where he worked on biostatistical and bioinformatic analyses in cancer research. His primary interests lie in developing innovative modeling and visualization techniques to help understand and communicate insights about the data-generative process across various applications. Dr. Dasgupta has broad expertise in statistics and machine learning methods, data analytics, data visualization, operations research, clinical trials and signal processing. He is an expert and advocate in using R and Python for data science. Abhijit co-founded Statistical Programming DC and served on the board of Data Community DC, an an organization that promotes Data Science and Analytics practitioners in the Washington DC Metro area. Abhijit has worked as a data scientist for academia, government and industry, currently developing ML methods and better ways of working to support Oncology R&D at AstraZeneca in Gaithersburg, Maryland, as well as providing training and community leadership among R users in the AstraZeneca and pharmaceutical communities.
Abhijit Dasgupta is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. His interests lie in the confluence of statistics and machine learning, using tools from both to develop methods and solve problems in genomics, translational science, observational studies and clinical studies, primarily in lung cancer, in a statistically rigorous manner. He acknowledges that statisticians don't appreciate prediction, and computer scientists don't appreciate variability, and tries doing better at both. He received foundational training in statistics and biostatistics from the Indian Statistical Institute and the highly-ranked University of Washington in Seattle, where he earned a doctorate in quite a theoretical and mathematical area of biostatistics. Wanting to be more applied in his focus, Abhijit joined the National Cancer Institute in Bethesda, MD, where he learned statistical genetics, genetic epidemiology, and bioinformatics as applied to cancer research. He continued working in oncology research for a few more years at Thomas Jefferson University in Philadelphia. He spent the next decade supporting rheumatology research at the NIH, learning meta-analyses, machine learning, and Bayesian methods. He returned to his oncology roots as a Data Science Associate Director at AstraZeneca in Gaithersburg, MD, where he supports various aspects of molecular, translational, and clinical research as a member of the Oncology Data Science function. He uses R and Python every day for his work and finds excitement in deriving stories from data through data scientific analyses, visualization, and domain understanding. During the last decade, he co-founded the Statistical Programming DC meetup with Marck Vaisman, served on the board of Data Community DC, and continued evangelism of R and Python as the languages of data science. At Georgetown, he teaches Data Visualization, and Big Data & Cloud Computing. He has developed high-quality training in R and Python for various commercial, government, and educational entities. His passion outside of data science is aikido, which he has practiced for almost 30 years, holding a 4th-degree black belt.
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science
Adam Imran is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. Currently, Adam is a Data Scientist-Network Analysis & Control at the MITRE Corporation where his work is focused on leveraging large-scale analytical processes, analysis of spatio-temporal data, decision sciences, and cybersecurity to solve problems for a safer world. He received his Bachelors of Science in Statistics from the University of Wisconsin-Madison and his Masters from the Data Science and Analytics department at Georgetown University.
Job Titles:
- Adjunct Professor
- Lead
- Principal Solutions Architect at Amazon Web Services
Amit Arora is the Lead Data scientist and an Advisory Engineer at Hughes Network Systems. He has a Master's degree in Data Analytics from Georgetown University. He works on solving complex problems in the field of telecommunications, traffic engineering, network security and business systems using data science and AI. He also provides data science and ML leadership to multiple teams across the organization and leads a team of data engineers, ML experts and DevOps engineers. He is passionate about helping to create citizen data science teams throughout the organization and regularly presents seminars and conducts training sessions. He has have been granted multiple patents for his work in telecommunications and currently has several patents pending that are at the intersection of telecommunications and machine learning. Amit's current interests are in the area of real time analytics and preemptive fault detection for large telecommunication networks especially with the ubiquitous presence of IoT devices and building and deploying ML applications in hybrid cloud and multi cloud environments. Before transitioning to a data scientist role he has had more than 18 years of work experience leading software architecture and design for satellite communication networks, satellite modems as well as hub side gateways. He worked on several key technologies such as IPv6, HTTP/S acceleration, Compression, traffic shaping, encryption, routing, layer 2 protocols, FIPS 140-2 certification, diagnostics etc.
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science and Analytics Program at Georgetown University
Anderson Monken is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. He is also a Data Science Manager at the Federal Reserve Board of Governors in Washington, D.C., where he leads a team of data scientists and application developers to champion cloud, big data, and machine learning initiatives. Anderson also contributes to a variety of internal and external data science teaching programs at the Fed which include serving as the instructor of record for an introduction to data analysis economics class at Howard University. His primary research focuses on analyzing and modeling non-traditional data to better understand the economic impacts of climate change, inflation risks, and international trade. You can find more information about his research and work from his personal website (new window) (new window). Anderson is an alumnus of Georgetown having earned an MS in Data Science and Analytics; he holds a BA in Chemistry, Economics, and Mathematics from Vanderbilt University in Nashville, TN.
Job Titles:
- Communications and Events Coordinator for the Data Science
Ashley Stowe is the Communications and Events Coordinator for the Data Science & Analytics Program at Georgetown University. Ms. Stowe supports the Data Science and Analytics program by managing all student and alumni events and maintaining our alumni network, as well as supporting and developing program communications channels. She holds a B.A. in Theater from the University of North Carolina at Wilmington, where directing plays helped her develop a knack for managing people and events. Prior to joining the DSAN team at Georgetown, she worked for several performing arts non-profits, most recently with Blumenthal Performing Arts in Charlotte, NC.
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science
Ben Houghton is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. He received his Bachelor of Science in Engineering from West Virginia University and Master of Science in Data Science and Analytics from Georgetown University. Ben also works in the Bioinformatics industry, focused on applying computer vision to biological images. Aside from computer vision, he has research interests in deep learning and financial time series modeling.
Job Titles:
- Adjunct Professor
- Learning Scientist at StormForge
Chris Larson is a machine learning scientist at StormForge, where he builds optimization tools for applications running in data centers. Chris received his PhD in Mechanical Engineering from Cornell University with a focus in robotics, human computer interaction, and machine learning. Prior to StormForge Chris worked at Capital One where he helped build the machine learning stack that powers their chatbot Eno.
Job Titles:
- Enterprise Account Executive
Dr. Jacobs received his Ph.D. in Political Science from Columbia University in 2022, with a dissertation on quantitative approaches to studying the history of political thought. During the Ph.D., I also worked as an Adjunct Instructor at NYU's Center for Data Science and Research Assistant in Columbia's Economics Department.
His research in political science mainly pertains to the history of political thought and what he calls "computational political theory" (Natural Language Processing + Network Analysis + Political Theory)
His research in economics focuses on empirical, text-analytic studies of monopsony and collective bargaining in modern and historical labor markets.
Before his Ph.D., he worked as a Research Economist at UC Berkeley. I received my MS in Computer Science from Stanford University, and as an undergraduate at the University of Maryland, I studied Mathematics, Computer Science, and Economics.
Job Titles:
- Assistant
- Program Director
- Program Director and Assistant Teaching Professor
Dr. Purna Gamage is Program Director, Assistant Teaching Professor, and Lead Student Advisor for the Data Science and Analytics program at Georgetown University. Dr. Purna received her PhD in Mathematics majoring in Statistics in 2018 and Master's Degree in Statistics from Texas Tech University for her research in Bayesian Hierarchical Modeling, Spatial and Temporal Data Analysis, and Ecological Statistics. Dr. Purna is currently engaged in research publications (new window) with her students applying machine learning and statistical learning tools in epidemiology; forecasting and comparing stock market behavior with social media influence using sentiment analysis and time series analysis (using Twitter data and NewsAPIs) and collaborative research with the Federal Reserve Board of Governors (FRB); harnessing AI methods to improve multi-country macroeconomic forecasting. Her research work has been presented at various local and international conferences.
Moreover, Dr. Purna actively teaches several graduate level classes, develops content, and engages in student-support activities, such as the career fair, the mock interview session, seminars, hackathons, and other data analysis competitions, workshops and organizing conferences. Moreover, she works with many companies bringing in collaborative opportunities for the Data Science program and the students. She was a first round judge and a quality analyst at the QED group / Center for Global Data Visualization (CGDV) (new window) data challenges.
She has devoted her time to the advancement of the program and creating a better experience for our students as well as advising and mentoring students. Prior to joining Georgetown University, she was a Visiting Assistant Professor at Wake Forest University and a Research Assistant at Texas Tech University.
Dr. Qiwei (Britt) He will join Data Science and Analytics Program at Georgetown University in August 2023 as a tenured Associate Professor. Before joining Georgetown, Dr. He has been Senior Research Scientist in the Psychometric and Data Science Modelling Center at Educational Testing Service (ETS) for over nine years, managing research on innovative item type development, technology-based environment design, and process data analyses in national and international large-scale assessments such as PISA, PIAAC, and NAEP as well as in K-12 education assessments and learning projects. Her research focuses on advancing methodologies in process data analysis, sequence mining, text mining, psychometric modeling, large-scale assessments, and interactive item design in learning and assessments.
Dr. He was appointed OECD Thomas J. Alexander Fellow and served on the Psychometrics and Educational Evaluation Panel for UNESCO Institute for Statistics and USAID. She received the Annual Award of Exceptional Achievement in 2023, the Jason Millman Promising Measurement Scholar Award in 2019, and the Alicia Cascallar Outstanding Paper of Early-Career Scholar Award in 2017 from the National Council on Measurement in Education.
Dr. He has been leading multiple research projects funded by NSF, IES, IEA, NCES, and OECD in developing innovative methods to analyze complex new data sources (e.g., process data and textual data) in education that have the potential to understand students' learning behaviors and strategies thus to assist in improving students' achievement, especially for the underrepresented groups. In addition, Dr. He has been selected for the grant panel for NSF for many years and serves as an ad hoc reviewer for over 20 journals in the fields of education and psychology. She serves on the editorial board of the Journal of Educational Measurement and is the Lead Guest Editor for the Journal of Intelligence.
Dr. He got her Ph.D. in psychometrics and data science from the University of Twente, in the Netherlands. Her dissertation won the Dutch Abbas Foundation Best Dissertation Award in Psychology in 2013 and Outstanding Dissertation Award in American Psychological Association (APA) Division 5 (Quantitative and Qualitative Research Methods) in 2017. Dr. He is also affiliated with the Department of Mathematics and Statistics at Georgetown University and the Methodology Inquiry Program at the College of Education at Indiana University as an adjunct professor to teach data mining and multivariate statistics.
Job Titles:
- Director of Student Services for the Data Science
Heather Connor is the Director of Student Services for the Data Science & Analytics Program at Georgetown University. Ms. Connor serves as the primary contact for prospective students, current students, and alumni. With a focus on student services, she manages the Student Ambassador Program, Student Mentorship Program, and Writing Center, as well as overseeing the fellowship and assistantship programs, student recruitment, and admissions. She holds an interdisciplinary Master's degree in Humanities from the University of Chicago, where she began her career in graduate student services. Prior to joining Georgetown, she worked in graduate program administration at the University of Southern California and the University of Texas at Arlington.
Irina Vayndiner is a Senior Technical Staff at MITRE. She received her M.S. in Mathematics and Physics from Moscow University, specializing in space mechanics. Irina has 20 years of Industry and Government experience in a variety of projects related to Big Data. Irina teaches multiple classes in the area of Information Technology. She presented at numerous scientific and technology conferences, has multiple publications, and a patent in the area of database security.
Job Titles:
- Assistant
- Assistant Teaching Professor and Course Coordinator
James Hickman is an Assistant Teaching Professor in the Data Science and Analytics program at Georgetown University. He received his Ph.D. in Computational-Physics from George Mason University (GMU) in 2017, an M.S. in Engineering-Physics from GMU in 2014, and a double-major in Physics and Applied Mathematics from Shippensburg University in 2011. His graduate work focused on applying classical atomistic simulations to various material science and condensed matter physics problems. In 2018, he was awarded an NRC postdoctoral fellowship at the National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland. Dr. Hickman's post-doctoral research focused on improving interatomic bonding models for both metallic and covalent systems. This was done by combining the transferability of physically derived approaches with the flexibility of artificial neural networks. These perturbative hybrid models achieve near quantum accuracy in their training region while exhibiting physical extrapolation outside the training domain. Dr. Hickman continues at NIST as a guest researcher where he focuses on problems at the intersection of machine learning and material science.
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science
Jeremy Bolton is an Adjunct Professor in the Data Science and Analytics program at Georgetown University. His research interests are focused on Machine Learning, Computer Vision, Statistical Learning Theory, and various applications. Previous research applies these concepts for the purposes of remote sensing, pattern classification, and modeling.
Job Titles:
- Adjunct Professor
- Adjunct Professor in the Data Science
Marck Vaisman is an Adjunct Professor in the Data Science and Analytics program at Georgetown where he teaches ANLY502 (Massive Data Analytics) and ANLY503 (Scientific and Analytical Visualization). Marck is a Technical Solutions Professional at Microsoft and helps customers adopt the Azure platform and use it for Data Science, Advanced Analytics and Artificial Intelligence workloads. Marck designs data-driven computing solutions to help clients make better business decisions, recognize opportunities, experiment, gain insights, and solve difficult problems using large datasets and a combination of tools. His expertise lies in making data work for the problem at hand, drawing from experience in multiple industries including Internet, telecommunications, and high tech. Marck is an experienced R programmer and advocate. He founded Data Community DC, an organization that promotes Data Science and Analytics practitioners in the Washington DC Metro area. He holds a B.S. in Mechanical Engineering from Boston University and an MBA from Vanderbilt University.
Job Titles:
- Assistant Teaching Professor
Nakul Padalkar is an Assistant Teaching Professor at Georgetown University. Dr. Padalkar has a Ph.D. in Management Information Systems with a focus on Machine Learning, Explainable AI, and Blockchain, an MS in Technology Management focused on Project and Quality Management, an MS in Physics with a focus in Optics and Color Science, and an MS in Industrial Engineering focusing on Stochastic Processes. Dr. Padalkar has spent over eight years actively teaching, developing new courses and curriculums, supporting faculty, and engaging in research focused on technologies' social and business applications. He has considerable industrial experience and worked as an operations engineer and project manager. Dr. Padalkar's doctoral research focuses on Disruptive technologies' industrial application and adoption.
Nate Strawn holds joint appointments in Analytics and in the Department of Mathematics and Statistics. Dr. Strawn's research draws on probability, optimization, geometry and topology to advance theory and algorithms in data science. He also uses tools from algebraic geometry in signal processing via frame theory. Strawn received his PhD in Mathematics in 2011 from the University of Maryland, College Park for his work on geometry and optimization in finite frame theory. Prior to joining Georgetown University in 2015, he was Senior research Engineer at the Johns Hopkins University Applied Physics Laboratory, an FDA ORISE Fellow, and a postdoctoral research associate and Visiting Assistant Professor of Math at Duke University.
Nicola Hobby is an international development and public health practitioner who made the unlikely leap to a startup technology consulting firm in 2015. She is an executive leader with 20 years of experience across a variety of roles and functions, she has supported a diverse set of clients in the international development digital sector, US Government agencies and tech start-up space. She has eleven years of experience in field based public health and health system strengthening initiatives and has worked in over 20 countries across Asia, Africa, and South America. Between 2011-2020 she led multiple institutional efforts to deploy DHIS 2 as an enterprise level MIS including acting as the Product Owner for PEPFAR's DATIM system. After working in roles across research, monitoring and evaluation, information systems and analytic services, she has a wide perspective about how to harness the power of data and is devoted to empowering data consumers with skills and systems for impact. She is currently working as an independent consultant, supporting digital strategies for international development organizations.
Job Titles:
- Adjunct Professor
- Professor
Dr. Zahadat is a professor of security, digital forensics, and data science. He is also a professional consultant in the IT security industry and has worked extensively within the public and private sectors throughout the years.
Dr. Zahadat has taught at University Systems of Maryland and Virginia in the fields of forensics, data science, information systems, web development, systems engineering, and security. He received his undergraduate degree in Mathematics from George Mason and received his graduate degree in Information Systems, and Ph.D. in Systems Engineering and Engineering Management from George Washington University. Dr. Zahadat's research interests are mobile security, information security, digital forensics, risk management, data mining, and information visualization.
Job Titles:
- Adjunct Professor
- Natural Language Processing Researcher
Trevor Adriaanse is a Natural Language Processing researcher within the Department of Defense. His work applies deep learning methods to human language technology problems, such as named entity recognition, cross-language information extraction, and others. Trevor received his undergraduate degree in Mathematics from Bucknell University and his Master's degree in Linguistics (computational linguistics) from Georgetown University.
Amit Arora (new window)
Adjunct Professor
Amit is a Principal Solutions Architect at Amazon Web Services in Strategic Accounts. He received his Bachelor's in Tech from the Netaji Subhas University of Technology and his MS in Data Science and Analytics from Georgetown University.