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
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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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Jules Malin, MS M.S., Data Science
Faculty
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Jules Malin, MS

M.S., Data Science
Faculty

Degree Program

  • Master of Science Applied Artificial Intelligence

Academic Degrees

M.S., Data Science (formerly Predictive Analytics) – Northwestern University
B.A., Organizational Studies – University of California, Davis

Areas of Interest in Artificial Intelligence

Applications of Machine Learning and Deep Learning techniques in areas related to enhancing digital marketing efforts, understanding and predicting consumer behavior, and improving consumer products.

About

Jules Malin is currently involved in projects that apply Machine Learning and Deep Learning in a range of domains, including digital marketing, direct to consumer, and product development. Another area of exploration is leveraging computer vision techniques to better understand customer and market segments and to inform and support product development.

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Dr. Jeffrey Yau, MA PhD, Economics
Faculty
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Dr. Jeffrey Yau, MA

PhD, Economics
Faculty

Degree Program

  • Master of Science Applied Artificial Intelligence

About

Dr. Jeffrey Yau leads a data science and engineering team at Walmart Labs. He is also an adjunct professor at UC Berkeley, where he has designed, developed, and taught the advanced statistics course for the online Masters of Information and Data Science program. His former and existing students come from a wide array of companies and other organizations, such as Microsoft, Amazon, Apple, Cisco, Moody’s Analytics, Goldman Sachs, Bank of America, Disney, KPMG, and Singapore Military. Jeffrey appears frequently as a speaker in Data Science and A.I. conferences, such as Starta, Spark & AI Summit, and ODSC.

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Dr. Rajeev Jain PhD, Electrical Engineering
Faculty
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Dr. Rajeev Jain

PhD, Electrical Engineering
Faculty

Degree Program

  • Master of Science Applied Artificial Intelligence

About

Rajeev Jain is a Professor Emeritus in Electrical Engineering at UCLA, and a Senior Director of Technology at Qualcomm. He is also a Fellow of the IEEE. Rajeev received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology in 1978, and a Ph.D. degree in Electrical Engineering from the Katholieke Universiteit, Leuven (IMEC), Belgium, in 1985. Rajeev’s early industry experience was at Siemens AG in Munich (later Infineon), where he developed design techniques for embedded DSP based communication systems. As a postdoc at the University of California, Berkeley, he worked on AI and object-oriented techniques for DSP chip design. At UCLA, Prof. Jain created courses in DSP and VLSI design and pioneered R&D programs in the design of high-speed communication circuits and wireless multimedia networking systems. He was also Vice-Chair of the Department and served on the ABET approval committee.

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Dr. Som Shahapurkar, MS PhD, Computer Science
Faculty
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Dr. Som Shahapurkar, MS

PhD, Computer Science
Faculty

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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