色界吧

Robert G. Alexander, Ph.D.

Assistant Professor | College of Arts & Sciences

Robert G. Alexander is a cognitive scientist using artificial intelligence to model visual expertise and transform education. He is Co-Founder and Chief Scientific Officer of Evidentia Analytics, LLC, an AI company developing evidence-based technologies for radiology and medicolegal analysis, where he leads scientific strategy and translational research and development. His NIH-funded collaboration with SUNY Downstate Health Sciences University uses neural networks to simulate how radiologists and laypeople scan medical images, supporting the development of training tools that teach novices to see like experts. Alexander鈥檚 broader research spans computational models of peripheral vision, attention-guiding visual features, and predictive modeling of viewer engagement in narrative media. Across these projects, he applies machine learning to high-dimensional eye-tracking data to uncover how humans interpret complex visual scenes and how that expertise can be assessed, taught, or enhanced through AI.

Natarajan Ganesan, Ph.D., M.B.A.

Assistant Professor & Assistant Director of Research | College of Osteopathic Medicine (NYITCOM)-Jonesboro

Natarajan Ganesan鈥檚 research explores the benefits and challenges of AI in healthcare and medical education, investigating the efficient utilization of large language models for data interpretation and summarization in precision medicine and genomics. Natarajan’s work highlights the potential of AI to transform healthcare and medical education, providing insights into the integration of AI in these domains.

Vidita Gawade, Ph.D.

Assistant Professor | School of Management

Vidita Gawade specializes in Explainable AI and physics-informed machine learning for smart manufacturing and 3-D printing. Her research aims to develop domain-based AI models for predicting quality in 3-D printing, enabling the additive manufacturing industry to adopt explainable predictive models. Her publications include papers on multimodal CNN-DNN model predictions, physics-informed loss functions, and layer-wise emission prediction in laser fusion, in collaboration with researchers from SUNY New Paltz, Rutgers University, and Cleveland State University. Gawade also participates in developing AI-infused courses and mentoring students in AI research. Current projects include exploring explainable AI in mental health research, contributing to the advancement of AI applications in various domains.

Jennifer Griffiths 

Professor | College of Arts & Sciences

Jennifer Griffiths examines artificial intelligence through humanistic and civic lenses, leading 色界吧鈥檚 Responsible Tech Ambassadors program. She teaches and develops undergraduate courses on AI ethics and social impact, advises students in relevant minors, and supports undergraduate research on responsible AI. Griffiths is 色界吧’s liaison to the Public Interest Technology University Network and serves on its New York regional steering committee.

Wenyao Hu, Ph.D., CFA

Assistant Professor | School of Management

Wenyao Hu focuses on Natural Language Processing (NLP) and the impact of AI incidents in the financial sector. His research analyzes AI-related incidents at major U.S. banks and financial services firms, revealing significant financial consequences, including short-term cumulative abnormal return losses and increased bankruptcy risks. Hu鈥檚 findings highlight the vulnerabilities AI introduces to financial institutions and provide insights into risk management and regulatory considerations. He has published his research in Finance Research Letters and collaborates with researchers from San Jose State University and Elon University.

Hu integrates AI tools into his courses, teaching students how to use applications like ChatGPT for risk assessment and portfolio construction. Current projects include examining the impact of AI incidents on crowdfunding performance, aiming to provide deeper insights into investor behavior and funding dynamics in the AI space.

Lise McCoy, Ed.D.

Assistant Professor & Director of Faculty Development | College of Osteopathic Medicine (NYITCOM)-Jonesboro

Lise McCoy specializes in AI and generative AI (GAI) for medical education. She has conducted surveys on AI experiences among faculty and students and collaborates with international AI committees. McCoy has published research on AI’s impact on medical education and is actively involved in validating AI frameworks. She mentors students in AI research and offers pre-conference workshops on AI applications. Her work contributes to the understanding and integration of AI in medical education, providing valuable insights into the future of AI in healthcare training.

John Misak, M.A., D.A.

Associate Professor | College of Arts & Sciences

John Misak is the architect of a forthcoming degree focusing on technical communications and artificial intelligence, designed to equip graduates with core competencies in AI ethics, implementation, and efficiency. Misak has published several articles on educational technology in the classroom. His current research investigates AI integration with education. In addition, he designed a human-machine communication course centered on AI interaction and teaches prompt engineering as a modern form of written composition. Beyond academia, Misak consults with corporate entities to design AI-driven automation suites and to train teams on ethical, effective AI implementation.

Rakesh Mittal, Ph.D.

Professor & Chair, Department of Quantitative & Analytics | School of Management

Rakesh Mittal specializes in machine learning and generative AI. His work has included employing generative AI for aspect-based sentiment analysis of customer reviews for a logistics company, helping the company identify critical service gaps and improve customer satisfaction by systematically addressing complaints. Mittal has published several papers on AI in business, actively collaborating with other researchers, and mentors students in AI-related projects, such as developing a dynamic AI-powered product recommendation system. He also conducts workshops and presentations on generative AI, contributing to the education and awareness of AI tools and their applications.

Maria Plummer, M.D., FASCP, FCAP

Associate Professor | College of Osteopathic Medicine (NYITCOM)

Maria Plummer鈥檚 work contributes to the integration of AI in medical education, providing valuable insights into the application of AI in healthcare. She is currently working on a grant for a project to advance the use of AI in pathology, enhancing educational outcomes in medical training.

Amba Sekhar, Ph.D. M.Sc.

Adjunct Professor | School of Management, Vancouver campus

Amba Sekhar works on constructing institutional investment portfolios using machine learning. His research focuses on developing AI-driven strategies for portfolio management and policy statement construction. His work contributes to the practical application of AI in financial decision-making and investment strategies. Sekhar integrates AI into his teaching, providing students with practical knowledge and skills in AI applications, mentoring them in AI-related projects, and fostering their growth and understanding of AI in finance.

Milan Toma, Ph.D.

Assistant Professor | College of Osteopathic Medicine (NYITCOM)

Milan Toma focuses on machine learning for medical diagnostics. He teaches an AI elective on AI-assisted medical diagnostics and conducts research on training machine learning models to classify diseases. Toma has published extensively on this topic and collaborates with various departments within NYITCOM and across the university, including the College of Engineering and Computing Sciences, along with other universities and international institutions. His work contributes significantly to the advancement of AI in medicine, providing valuable insights into the application of machine learning in disease classification and medical diagnostics.

Youhua Zhang, M.D., Ph.D.

Associate Professor | College of Osteopathic Medicine

Youhua Zhang uses AI for research and writing, leveraging AI tools to enhance the efficiency and accuracy of his research. His work focuses on integrating AI into biomedical research, contributing to the advancement of AI applications in the medical field. Zhang’s efforts demonstrate the practical benefits of AI in research and its potential to improve research outcomes.