MASTER OF SCIENCE

Analytics

billie-anderson
Billie Anderson, Ph.D.
Professor of Analytics
Email

Education:

Ph.D. in Applied Statistics, University of Alabama, Tuscaloosa, AL, USA.
Masters in Mathematics & Statistics, University of South Alabama, Mobile, AL, USA.
Bachelors in Mathematics, Spring Hill College, Mobile, AL, USA.

Biography:

Dr. Billie Anderson started her statistical career at SAS in Research and Development. SAS is located in Cary, NC and is the largest privately-held statistical software company in the world. At SAS, she researched and implemented data mining algorithms. Her specific focus was implementing credit scoring and insurance data mining applications for industry.

Dr. Anderson has been teaching analytics and statistics courses since 2006. She has been a professor in Colleges of Arts & Sciences and Business. Before coming to Harrisburg University, Dr. Anderson held an Endowed Chair in Medical Informatics in a College of Pharmacy and was the founding member of a Biostatistics Core group.

In addition to her academic teaching, she is currently a Senior Analytical Trainer/Consultant for SAS. Dr. Anderson has taught courses in data mining and applied analytics to organizations such as Starbucks, Department of Homeland Security, State of California Pension Board, U.S. Department of Transportation and Safety, Ann Taylor, Lowes, State Farm Insurance, Dunn & Bradstreet, Suntrust Bank and many more Fortune 500 companies and government agencies.

Teaching and Research Interests:

Dr. Anderson's research is mainly focused on applying statistical and analytical techniques to business, healthcare, and government applications. She has over 30 peer-reviewed journal articles and book chapters. She has researched how big data is changing the healthcare landscape, how social media data can be incorporated into credit scores and how to apply data mining time series to retail data to gain insights into customer purchasing behavior.

Dr. Anderson is currently participating in the code4PA Hackathon which contains open-source government data related to the opioid crisis. Dr. Anderson is hoping to submit the results of her findings from the code4PA Hackathon to a peer-reviewed journal by the end of this year.

Courses Taught at HU:

Applied Multivariate Data Analysis
Data Visualization

Nathaniel Ashby, Ph.D.
Assistant Professor of Cognitive Analytics
Email

Phone Number:

717-901-5100 x1660

Education:

Ph.D. in Psychology – Universitat of Erfurt, Erfurt, Germany.
M.Sc. in Psychology – University of Oregon, Eugene, Oregon, USA.
BS w/honors in Psychology – University of Oregon, Eugene, Oregon, USA.

Biography:

Dr. Nathaniel Ashby is fascinated by human decision-making processes (i.e., why we do the things we do). Understanding these complex and often perplexing behaviors is what drew him to Psychology as an undergrad and what motivated him to pursue a Ph.D. Conducting studies and finding interventions that might assist people to make better decisions is both challenging and rewarding. He thinks engagement in research is something every graduate should experience.

Teaching and Research Interests:

Dr. Ashby is interested in the role individual differences play in judgement and decision making and how it can provide for efficient assessment in industry. For example, how does numeric ability and memory capacity influence decision making in complex analytic environments? His interest also spans in the way we collect information and use it to inform our decisions, as well as the biases we show during that process. To that end, he uses a large amount of eye-tracking and other process tracing methodologies to answer his research questions.

Courses Taught at HU:

Analytics II
Applied Experimental
Data Analytics
Qualitative Decision Making
Quasi-Experimental Design

Srikar Bellur, Ph.D.
Assistant Professor of Data Analytics
717-901-5100
Email
Erin Buchanan, Ph.D.
Professor of Cognitive Analytics
Email

Education:

Ph.D. in Experimental Psychology – Computational Linguistics and Statistics, Texas Tech University, Lubbock, TX, USA.
M.A. in Experimental Psychology – Cognitive, Texas Tech University, Lubbock, TX, USA.
B.S. in Psychology, Texas A&M University, College Station, TX, USA.

Biography:

Dr. Erin M. Buchanan received her Ph.D. from Texas Tech University in computational linguistics with a focus on statistics after attending Texas A&M University for her undergraduate degree. In her spare time, she likes to watch sports, play video games, go to National Parks, and travel the globe.

Teaching and Research Interests:

Dr. Erin M. Buchanan research focuses on modeling semantic memory and how it might understand the underlying language network by creating better measures of relationships between concepts.
She also examines statistical practices and how it might improve those practices through enhanced methodology and teaching (check her out on Datacamp!). Last, she collaborates with other investigators to improve their statistics and develop psychometrically sound measures of their concepts.

Courses Taught at HU:

ANLY 500
ANLY 520
ANLY 540

Pavlo (Pasha) Buryi, Ph.D.
Assistant Professor of Economics
Email

Phone Number:

717-901-5100 x1653

Education:

Ph.D. in Economics, Southern Illinois University, Carbondale, IL, USA, May 2015.
M.Sc in Economics, Southern Illinois University, Carbondale, IL, USA, May 2013.
B.A. in Economics, Southern Illinois University, Carbondale, IL, USA December 2010.

Biography:

Dr. Pavlo Buryi earned his Ph.D. in Economics, along with a Masters degree and Bachelors degree, from Southern Illinois University Carbondale. Prior to joining Harrisburg University of Science and Technology, he held faculty positions at the University of Tampa, and Northern Illinois University. His primary field of expertise is the Economics of Innovation and Technological Change.

Teaching and Research Interests:

Dr. Buryi is very passionate about teaching and takes pride in what he does. Most of his free time is spent searching for current examples of economic concepts in the real world. He uses these examples to initiate a discussion and engage students on the topic. After each class, Dr. Buryi makes all videos and lecture notes available on Moodle. It is a great tool as it allows students to learn at their own pace and keep track of their grades and feedback. However, in the classroom, he prefers a more traditional approach like writing notes on the board and explaining ideas/concepts without PowerPoint slides. When students rewrite the notes, they are physically engaged, and as a result, more attentive.

Dr. Buryi's research focuses on the importance of product R&D and the role of public support in promoting such R&D. He developed a microeconomic model of product R&D to provide a theoretical basis for optimal choices of private investment and matching public support, used in widely popular “matching grant” state programs. Moreover, by introducing international competition into the basic theoretical framework of the matching game, he considers public support for product R&D as an optional policy of import substitution. Finally, his research provides an optimal structure of public R&D support.

Courses Taught at HU:

Civic Mind
Economics of Innovation
Organizational Mind
Principles of Business Management

Rand Ford, Ph.D.
Professor of Analytics
LinkedInEmail

Phone Number:

717-901-5100 x5125

Education:
Ph.D., in Artificial Intelligence, Johns Hopkins University.
M.A. in Experimental Psychology, Johns Hopkins University.
B.A., Johns Hopkins University.

Biography:
Rand Ford came to Harrisburg University of Science and Technology from University of Maryland University College where he worked as the Director and Professor for the Data Analytics Program. Prior to that, he served as Chair of the Computer Science Department at Hood College and as President of their faculty.

Additionally throughout his career, he has held C-level positions at six different companies. Dr. Ford holds two patents and is active in both academic and applied research. His areas of expertise are in the analysis of unstructured data, natural language processing, and machine learning.

Philip Grim, II
Lecturer in Computer Science
Email

Phone Number:

717-901-5100 x1625

Education:

M.Sc. in Analytics, Harrisburg University of Science and Technology, Harrisburg, PA, USA.
B.Sc. in Computer Information Systems, St. Leo University, Tampa, FL, USA.
Associate of Applied Science, Computer Programming Technology: Metropolitan Community College, Omaha, NE, USA.

Biography:

Philip Grim, II is a veteran of the US Air Force, after which he became a Civilian Defense Contractor. His career as a software engineer has spanned more than twenty-five years in both military and civilian life. Philip Grim, II worked extensively in military intelligence, in modeling and simulation. He also worked with the Natural Language Understanding technologies and systems in support of military intelligence and other applications for over a decade.

His team also designed and built the first Big Data ecosystem for the Department of Defense. He began teaching at Harrisburg University of Science and Technology in the fall semester of 2014 as corporate faculty and became full-time faculty in the summer semester of 2016.

Teaching and Research Interests:

Philip Grim, II enjoys teaching topics in programming, software engineering, systems architecture, and natural language processing. He will enter HU’s new Ph.D. program in Data Science, where his research will focus on NLP.

His development and research work focuses on blockchain applications and on NLP research. He is currently researching techniques of mining formal argumentation from arbitrary text. He teaches a variety of topics including programming, software and systems engineering, and analytics.

Courses Taught at HU:

Big Data Architectures
Enterprise System Integration
Functional Programming Methods for Analytics
Game Theory, Simulation, and Gamification
Principles of Analytics II
Principles of Software Engineering and Systems Analysis
Project I
Sentiment Analytics

Kevin Huggins, Ph.D., CISSP
Professor of Computer Science and Analytics
LinkedInEmail

Phone Number:

717-901-5100 x1619

Education:
Ph.D. in Computer Science, Mines ParisTech, Paris, France.
M.S. in Computer Science, Naval Postgraduate School, Monterey, CA.
B.S. in Computer Science, US Military Academy, West Point, NY.

Biography:
Kevin Huggins, Ph.D., is Professor of Computer Science and Analytics at Harrisburg University of Science and Technology. He is also a retired military officer who spent the early part of his career in military intelligence, with extensive experience in Latin America. The remainder of his career was dedicated to academia, primarily as a faculty member in the Department of Electrical Engineering and Computer Science at the U.S. Military Academy. While there, Kevin served as the Director of Research in Network Science as well as the Director of the Information Technology Program.

Additionally, Dr. Huggins was a visiting scientist at the École de Techniques Avancées in Paris, France, where he studied parallel algorithms for multiprocessor system-on-chip (MPSoC) architectures. His current research interest lies at the intersection of data analytics and information security, exploring novel ways to leverage the enormous amounts of data available to make computing systems more secure.

Dr. Huggins has served as a consultant for computing curriculum development and for fostering international collaborative research efforts in technology and engineering. Over the past decade Kevin has also served as a program evaluator, team chair and commissioner for ABET, an internationally recognized accrediting agency for university programs in the engineering, science and technology domains.

Kevin holds a Ph.D. in computer science from the École des Mines de Paris.

Wei-Kang Kao
Assistant Professor of Statistics and Analytics

Phone Number:

717-901-5100 x1747

Education:

PhD in Research, measurement, statistics and evaluation, Oklahoma State University, Stillwater, OK
Master in Research, measurement, statistics and evaluation, Oklahoma State University, Stillwater, OK
Bachelor in Psychology, Kaohsiung Medical University, Kaohsiung, Taiwan.

Biography:

Kang is an assistant professor at the University. Before HU, he received his PhD degree in REMS from Oklahoma State University. His current area of focus, is consumer behavior with technology issues, especially on smartphone games, apps, data analytics, simulation modeling and digital marketing related studies such as social media and online marketing.

Teaching & Research Interests:

Consumer Behavior and Digital Marketing: Smartphone use, apps, games and technology/information/internet related issues
Statistics and Data Analysis: applied statistics in marketing field
Structural equation modeling: model building, multi-level/experimental/ multivariate SEM
International/Cross cultural study

Courses Taught at HU:

ANLY 510-90, Analytics II: Principles & Applications

Jonathan Korn
Lecturer of Analytics
Email

Phone Number:

631-210-4162

Education:

Doctor of Philosophy, Data Science – Harrisburg University of Science and Technology, Harrisburg PA, (May 2019 – Expected 2022)
• Doctorate in Data Science, Focus in Machine Learning.
Masters in Data Analytics – Southern New Hampshire University, New Hampshire CT, (August 2016 – September 2018)
• Masters in Data Analytics. Focus in R programming language & Python programming language.
Masters in Business Administration (International) – Southern New Hampshire University, New Hampshire CT, (August 2014 – July, 2016)
• International Masters in Business Administration (MBA) with a concentration in Marketing.
• GPA 3.4. Focus in International Marketing, Research, Strategy and Statistical Analysis.
BA in Political Science – Long Island University, CW Post, Brookville NY, (September 2009 – May 2013)
• GPA 3.6. Focus in International Relations

Biography:

Jonathan is currently a PhD. Candidate at HU to continue his education and better focus his research efforts into solving with Deep Learning.

Teaching & Research Interests:

Interested in Deep Learning Models

Courses Taught at HU:

Principles of Analytics (ANLY 500), Natural Language Processing (ANLY 520), Human Language Processing (ANLY 540), Machine Learning I (ANLY 530), Data Visualization (ANLY 512), and Experimental Design (ANLY 510).

Andre L'Huillier
Assistant Professor of Computational Social Science
Stephen Penn, DM, PMP
Associate Professor of Business Analytics & MEBA Program Lead
Email

Phone Number:

717-901-5100 x1617

Education:

D.M. in Management, University of Maryland, Adelphi, Maryland, USA.
Master of Business Administration, Frostburg State University, Frostburg, Maryland, USA.
B.A. in Russian, the University of Texas in Arlington, Arlington, Texas, USA.
B.A. in Mathematics, the University of Texas in Arlington, Arlington, Texas, USA.

Biography:

Stephen Penn has worked in Information Technology for more than 20 years, specializing in database development and analytics. His experience in analytics includes projects focused on student achievement in higher education, insurance fraud, and workforce optimization. Dr. Penn is certified in project management.

Teaching and Research Interests:

Stephen Penn's research is in the field of data-driven decision-making. His approach to research, balances qualitative and quantitative methods, as most business transactions are social interactions with a quantitative component. Most of his projects include the collection, analysis and evaluation of management-related activity artifacts, ranging from project plans, and budgets to even emails and meeting notes. His particular area of focus is data analytics, which is a very exciting and growing area of information technology.

Courses Taught at HU:

Analytics I: Principles and Applications
Analytics II: Principles and Applications
Analytics Tools and Techniques
Business Intelligence and Decision Support
Categorical Data Analysis
Data Visualization
Introduction to eBusiness Management
Quantitative Decision Making
Research Design and Methodology

Kevin Purcell, Ph.D.
Program Lead for Data Analytics and Associate Professor of Data Science
Email
Roozbeh Sadeghian, Ph.D.
Associate Professor of Data Analytics
Email

Phone Number:

717-901-5100 x1645

Education:

Ph.D. in Electrical Engineering, State University of New York at Binghamton, Binghamton, NY, USA.
M.Sc. In Electrical Enginieering, Shiraz University, Shiraz, Iran.
B.Sc. In Electrical Engineering, Isfahan University of Technology, Isfaha, Isfahan, Iran.

Biography:

Upon graduating with a degree in electrical engineering (control field), Dr. Sadeghian worked for seven years in several industries as a Senior Industrial Automation Engineer. He decided to continue his education in the signal processing field which gave him the motivation for obtaining a Ph.D. During his Ph.D. research, he began familiarizing himself with Machine learning with a focus in diagnosing human health disorders.

Dr. Sadeghian worked on speech features as the baseline to diagnose the delay in speech in children and Alzheimer's disease in elderly people. To address the issues properly, he has worked with several tools such as DNN and RNN networks and has published several papers that proved his hypothesis of using speech recognition in diagnosing health disorders in early stages.

Teaching and Research Interests:

Dr. Sadeghian's teaching interests include graduate courses such as Analytics, Data Visualization, Signal Processing, Automatic speech recognition, Pattern recognition, Machine learning, Power systems, Convex optimization,and Modern Control.
His undergraduate courses include any undergraduate course related to signal processing (signals and systems, digital signal processing) and applied mathematics (linear algebra, probability theory).

Dr. Sadeghian's research is founded at the nexus of science and engineering of clinical diagnosis and early notice of assessments and also analytics and data science. Specific topics include:
– Analytics, Big data and data science, Data visualization
– Modeling, detection and tracking of paralinguistic information, such as health state, and traits from human speech signal
– Machine learning applications in speech processing
– Acoustic and Language Modeling and analyzing the speech signals with applications to recognition and clinical assessments of speech
– Developing new and improving the current speech features to improve ASR accuracy.

Courses Taught at HU:

ANLY 500
ANLY 530
Analytics I
Analytical Methods II
Machine Learning I
Principles and Applications

Doaa Taha, Ph.D.
Assistant Professor of Analytics
LinkedInEmail

Phone Number:

717-901-5100 x1647

Education:
D.Sc. In Engineering Management, the George Washington University, Washington, D.C., USA.
M.Sc. in Operations Research and Management Science, the George Washington University, Washington, D.C., USA.
B.Sc. in Electrical Engineering and Telecommunications, Zagazig University, Egypt.

Biography:
Dr. Doaa Taha teaches Analytics & Data Science at Harrisburg University. Dr. Taha is an entrepreneur who led a number of diversified global business development portfolios, successively, as Senior VP, Managing Director and Board Co-Chair of global boutique Strategic Advisory Services firm Grey Matter International (GMI), and its sister company, Grey Matter LLC, based in Washington D.C. Doaa is also a respected Civil Society Leader and is the Founding Chair of the American Arab Women’s Empowerment Forum, the leading Non-Profit Women’s Organization within that Community; she is also the National Board Secretary General of the ADC, the oldest, largest and foremost civil rights organization of the American Arab Community, promoting and defending the values embodied in the United States Constitution, where she is a Board Director, a Member of its Executive Committee and the Chair of its Nominations Committee. Doaa was previously Senior Advisor, for its Middle East & North Africa Program, to the International Women’s Media Foundation (IWMF), leading its assignments in Turkey, Lebanon and the United Arab Emirates, raising full funding of the translation in all 4 Middle Eastern languages of the development of its Journalism Smartphone Security App, including its Testing and Training Workshops, and leading the IWMF delegation to the Arab Media Forum in Dubai. A George Washington University Doctoral Alumnus in Engineering Management and Systems Engineering (School of Engineering & Applied Sciences), with a background in Operations Research (Major in Management Science) and Electrical Engineering (with specializations in Telecommunications & Electronics / Chip Design & Testing / VLSI), Doaa was the Senior Research Coordinator at the GWU Center for Risk, Crisis, Disaster & Emergency Management, for the Research Grant Program funded by the National Science Foundation (NSF) on Post-9/11 Corporate and Institutional Risk, Crisis, Disaster and Emergency Preparedness, Response and Management, after having led, as a Software Engineer, the Hardware Engineering Electronic Chips Testing Lab & Automated Bench for Axcelis, within the Eaton Corporation, her remediation of the testing protocols there having improved quality to the point that Axcelis went from securing 15% to 50% of the world market share in Chip Wafer Matrix Production. Before that, Doaa taught at The George Washington University’s School of Engineering and Applied Sciences, and was previously a Teaching Assistant while she was also a Customer Engineer at Giza Systems for Computers, then Egypt’s leading private IT Company, reporting directly to its CEO on Customer Needs Analysis and Network Solutions. Doaa is a published researcher, author and co-editor, on a number of Academic and Professional areas of endeavor, including Corporate Disaster Preparedness, E-Government, Public-Private Partnerships, Bringing Technology to the Market and Women’s Leadership in Engineering, Science & Technology, an area for which she advised the U.S. Assistant Secretary of State for Global Affairs, during an USG-cosponsored Arabian Gulf Conference focusing on these issues in the Middle East & North Africa, and for which she led a research program promoted by the European Union and The World Bank, where her work on Soft Skills and Early Childhood Learning & Cultural Awareness were retained as best practices. Doaa is married and has two daughters.