Mustafa Hajij is an assistant professor of data science at the department of Mathematics and Computer Science at Santa Clara University. He received his masters in Computer Science, PhD in Mathematics from Louisiana State University and postdoctoral training at the computer science departments at University of South Florida and Ohio State University. Before joining Santa Clara University, he spent a year as an AI research scientist at KLA Corporation. He has published papers in NeurIPS, IEEE TVCG, IEEE Pacific Visualization Symposium, TRB, and Transaction of the AMS. His research interests lie at the intersection of machine learning, topological data analysis, and geometric data processing, with a current emphasis on the geometric representation learning, graph neural networks and their generalizations.

Rahul Paul currently works at the Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, as a Postdoctoral Research Fellow. During his doctoral thesis, he worked on lung nodule malignancy prediction 2 years in the future and multimodal neonatal pain analysis. His current research is focused on using machine learning and deep learning to analyze early diagnosis, and prognosis of head and neck cancer using imaging and clinical data.

Ghada Zamzmi works as a research fellow in the National Institutes of Health, where she is applying her expertise in Computer Vision and Machine Learning in developing computational tools to advance healthcare of vulnerable populations and people in rural settings. Her research interests include medical images analysis, biomedical engineering, and affective and cognitive computing. She has published papers in NeurIPS, IEEE FG, ICPR, SMC, EMBS, T-BIOM, TAC, TBME. She served in the program committee in several top conferences in Computer Vision, chaired several academic workshops and events in her area of interests, and participated in several mentoring and leadership programs.

Lokendra Thakur is a research scientist at Broad Institute of MIT and Harvard. He obtained his PhD in Mathematics from Louisiana State University. In his doctoral thesis he worked on Reduced Order Models for Beam-Wave Interaction in High Power Microwave Sources. Lokendra's areas of interest include the Mathematics of Material Sciences, Statistical Genetics, Computational Biology, Machine Learning and Topological Data analysis. Currently focused on developing models, algorithms, and analysis tools for identifying genes and/or biomarkers of type 2 diabetes and the developed model can be generalized for other diseases such as Schizophrenia, Dementia and Cancer.