AI Experts
From schools and colleges throughout New York Tech, our interdisciplinary faculty experts are approaching and leveraging AI through a range of professional and academic lenses, from scholarly research to hands-on projects with students.
Natarajan Ganesan, Ph.D., M.B.A.
Assistant Professor & Assistant Director of Research | College of Osteopathic Medicine (NYITCOM)-Jonesboro
Natarajan Ganesan’s 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.
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’s 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.
Frank Lorne, Ph.D.
Professor | School of Management, Vancouver Campus
Frank Lorne has created AI bots to assist students in understanding materials and conducts research on digital dialogues, driverless cars, and digital marketing. Using Intellectus Statistics software, Lorne analyzes digital dialogues on the internet and explores the implications of AI in various industries. His work highlights the diverse applications of AI and its potential to transform various sectors. He has published research on ecosystem competition and digital marketing and is currently considering interdisciplinary applications of AI in energy management and cybersecurity.
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.
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’s 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.
Associate 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.