Master of Science in Applied Artificial Intelligence Applied Artificial Intelligence Faculty

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Online M.S. in Applied Artificial Intelligence Faculty

The faculty for the M.S. in Applied Artificial Intelligence program is composed of education and industrial experts who possess significant background and experience that spans across technology, engineering, and computer science. All courses in the masters in artificial intelligence degree program are taught by these real world experts, who will work with students and ensure that learning in the courses is contextualized for individualized development. Their expertise, experience and insight about this burgeoning field provides students with valuable information and expectations about careers in AI.

Dr. Ramesh Rajagopalan

PhD, Electrical Engineering
Program Director

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

PhD, Electrical Engineering – Syracuse University

Areas of Interest in Artificial Intelligence

Genetic algorithms, optimization, internet of things

About

Ramesh Rajagopalan is currently a Professor of Practice in Electrical Engineering and Program Director of the Masters in Applied Artificial Intelligence program at the Shiley-Marcos School of Engineering. He earned a PhD in Electrical Engineering from Syracuse University, Syracuse, New York. He was awarded the Graduate School Masters Prize and the all university Doctoral Prize at Syracuse University in recognition of his outstanding research and scholarship. Prior to joining University of San Diego, he was an Associate Project Scientist at the Institute for Neural Computation, University of California, San Diego (2019-20). He has over eleven years of strong teaching and research experience in electrical engineering and computer science. He was a faculty member at Florida State University from 2008 to 2009 and a Professor of Electrical Engineering at University of St. Thomas, Minnesota from 2009 to 2019. Professor Rajagopalan’s research interests include genetic algorithms, optimization, artificial intelligence, wireless communications and networks, internet of things, mobile health care, and signal processing. He has authored and co-authored numerous conference and journal papers in these areas. He is passionate about pedagogical approaches and practices to promote diversity and inclusion in higher education.

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Edwin Addison, JD, LLM, MS, MBA

JD, LLM, MS, MBA

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

JD, LLM, Concord Law School at Perdue University
MBA, Global Management and Healthcare Focus – Duke University
MS, Biomedical and Electrical Engineering – Johns Hopkins University
Certificate of Advanced Engineering Studies (Artificial Intelligence) – MIT

About

Ed Addison is a serial entrepreneur who has applied AI to multiple companies: ConQuest Software, PoweriZe.com, Lexxle Inc., and Cloud Pharmaceuticals. He was previously Director of the AI Lab at Booz, Allen and Hamilton. Throughout his career, Ed has been a member of the adjunct faculty of several universities where he has taught AI, Computer Science, Signal Processing and Entrepreneurship. He lives in Raleigh NC with his wife Karen and is the father of 4 and grandfather of 10.

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Dr. Ying Lin

PhD, Computer and Information Science

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

Ph.D., Computer and Information Science – University of Delaware

About

Dr. Ying Lin is a seasoned Artificial Intelligence and Machine Learning researcher with extensive
experience harnessing power of AI and Big Data across a range of sectors from Higher Education to
Healthcare, Pharmaceutical and Marketing industries. Prior to academia, Dr. Lin worked for a global
pharmaceutical company in multiple data and analytics driven functions, such as bioinformatics,
biostatics and latest marketing analytics as an advanced analytics manager in Consumer and
Business Insights. Dr. Lin received his Ph.D. in Computer and Information Science from University of
Delaware in 2005 with specialization in statistical data mining and machine learning.

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Amit P. Manghani, MS, MBA

MSc, Computer Science

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

MBA, SC Johnson School of Business – Cornell University
MSc, Computer Science – Southern Methodist University
BSc, Computer Science – Southern Methodist University

About

Amit P Manghani, M.S., MBA has more than a decade of experience in the Information Technology domain dealing with Enterprise Information Management, Data Science, Business Intelligence, and Cloud Computing technologies. Currently at Microsoft Corporation, Amit heads the end-to-end development efforts of a Data Science platform built on Azure that mines passive collaboration signals from Microsoft Office 365 to provide deep insights into work patterns so that effective organizational structures can be instituted to support business strategy and better business process workflows. Prior to joining Microsoft Corporation, Amit has led data management-oriented efforts at leading Information Management companies such as Oracle and SAP.
Outside of work, Amit likes to hike with family/friends and regularly explores one of many trials present in the California Bay Area. As an avid trekker, one of his goals is to trek to the Everest Base Camp which he plans to undertake within the next few years after a lot more practice hikes.

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Dr. Kahila Mokhtari

Faculty

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

PhD, Petroleum Engineering – Louisiana State University
MSc, Petroleum Engineering – Middle East Technical University
BSc, Applied Physics – Urmia University

About

Dr. Kahila Mokhtari is currently a senior data/ML scientist with IBM. She received her Ph.D. in Petroleum Engineering from Louisiana State University and her Master’s degree in Petroleum Engineering from Middle East Technical University. Dr. Mokhtari has 6 years of experiences in analyzing and interpreting data, supervised and unsupervised algorithms, demand forecasting, time series analysis, hypothesis testing, classification, clustering, and regression analysis. Her passion is centered in statistical modeling, machine learning, and deep learning methods. She has worked in Halliburton Corporation as a data science consultant. She focused on implementing Natural Language Processing (NLP) solutions for clients. Dr. Mokhtari has extensive experience in developing recurrent neural network models using Keras. She leverages her background as a researcher and scientist to provide high quality data science solutions.

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Dr. Som Shahapurkar

PhD, Computer Science

Degree Program

Master of Science Applied Artificial Intelligence

Academic Degrees

Ph.D., Computer Science – Arizona State University, Tempe, AZ
M.S., Electrical Engineering – University of Arizona, Tucson, AZ
B.E., Instrumentation and Electronics – Bangalore University, Bengaluru, India

Areas of Interest in Artificial Intelligence

Applications of AI to the Internet of Things (IoT), manufacturing, autonomous vehicles, and financial systems. Research interests include robust AI, explainable AI, ethical AI, causal AI, and biometrics.

About

Dr. Som Shahapurkar is an Adjunct Professor of Artificial Intelligence (AI) at the University of San Diego’s Shiley-Marcos School of Engineering. He is also an AI instructor for the Executive Perspective for Scientists & Engineers (EPSE) program at the University of California, San Diego (UCSD). Som is the Director of AI Products at FICO (formerly Fair Isaac), where he heads intrapreneurship programs to turn AI innovations into revenue-generating products.

Som has built and operationalized AI, ML, and advanced analytics for all of his 20-year career. For Intel, he led design and deployment of AI and machine learning systems for high volume manufacturing, Internet of Things (IoT), retail, smart-homes, communications, and self-driven cars. At Verizon, Som led a team engineers to enhance the telematics SAAS platform with advanced analytics. Som co-founded a startup in AI for energy management which won several competitions including the southwest Clean-Tech Open.

Som holds two patents, one on the application of AI to semiconductor manufacturing and another on the application of AI for Energy Management. His first patent is cited by 11 of the earliest Google patents on AI/ML. Som is a Lean Six Sigma black-belt in applied statistics and prides in his ability to solve real-world problems with compassion, data, and choice. He loves to teach technical and non-technical classes that include the ‘7-habits of highly effective people’ leadership program. Som likes mountain biking, 4×4 off-roading, riding his motorcycle, and bicycling for charitable causes.

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