KEYNOTE 1

Yang C. Fann

National Insitute of Neurological Disorders and Stroke (NIH), USA

• Biography
  Prof. Yang C. Fann earned his Ph.D. in Computational Chemistry from Temple University. Currently, he holds the position of Director for the Intramural IT and Bioinformatics Program at the National Institute of Neurological Disorders and Stroke (NINDS), which is part of the National Institutes of Health (NIH). Additionally, he serves as Clinical Informatics for the Office of Intramural Research. In these roles, he plays a pivotal role in addressing specific clinical informatics challenges and issues within the NIH Intramural Research Program (IRP). Prof. Fann has also overseen the development of numerous IT systems and extensive biomedical databases to facilitate data sharing, foster collaboration, and support innovative research endeavors.
  
  Between2010 and 2015, Prof. Yang C. Fann received several prestigious awards recognizing their outstanding contributions to biomedical research and administrative innovation. In 2014, he earned two notable accolades: the HHS Green Champion Leadership Award and the NIH Director Award for the operation of the Porter Neuroscience Building. In 2015, he was recognized with the NIH CIT Director Award for his innovations in biomedical research systems.

KEYNOTE 2

Building predictive models with AI in radiology and digital pathology

Anne Martel

University of Toronto, Canada

• Biography
  Dr Anne Martel is a Professor in Medical Biophysics at the University of Toronto and a Senior Scientist at Sunnybrook Research Institute where she holds the Tory Family Chair in Oncology. She is also a Faculty Affiliate of the Vector Institute, Toronto and the CSO of  Pathcore, a digital pathology software company, that she co-founded in 2006.
  
  Dr Martel is a fellow of the MICCAI Society, a senior member of SPIE and currently serves as a senior editor for the journal Medical Image Analysis.
  
  Her research program is focused on medical image and digital pathology analysis, particularly on applications of machine learning and artificial intelligence for detection, diagnosis, and prediction/prognosis.

KEYNOTE 3

Computational Medicine for Mental and Physical Health

Rose T. Faghih

New York University, United States

Abstract:

As new physiological sensing technologies become available for continuous monitoring of physiological signals, the dynamic response to external influences such as environmental inputs, medication, and surgery can be quantified. This research focuses on developing mathematical algorithms for dynamically tracking health states related to mental and physical health in the presence of different interventions. (1) Mental Health Focus: We design algorithms for a closed-loop neural wearable architecture called MINDWATCH for mental and cognitive well-being. We first infer arousal-related autonomic nervous system (ANS) activations. Then, we model and decode cognitive arousal and performance brain states where the inferred ANS activations and behavioral data are used as cognitive arousal and performance observations, respectively. We use neurofeedback to close the loop and modulate cognitive arousal and performance. (2) Physical Health Focus: We investigate clinical data from patients to study inflammation, fatigue, and metabolism using cytokines, stress hormones, and metabolic hormones, respectively. We deconvolve biochemical signals (e.g., hormones) to obtain the secretory events underlying their pulsatile production. Then, utilizing the recovered secretory events, we decode hidden health states (e.g., energy) dynamically. The ultimate goal is to design toolsets that can provide clinically relevant information using biosensors to prevent, diagnose, and manage health conditions.

Biography:

Dr. Rose T. Faghih is an associate professor of Biomedical Engineering at the New York University (NYU) where she directs the Computational Medicine Laboratory. She received a bachelor’s degree (summa cum laude) in Electrical Engineering (Honors Program Citation) from the University of Maryland, and S.M. and Ph.D. degrees in Electrical Engineering and Computer Science with a minor in Mathematics from Massachusetts Institute of Technology (MIT). She completed her postdoctoral training at the Department of Brain and Cognitive Sciences and the Picower Institute for Learning and Memory at MIT as well as the Department of Anesthesia, Critical Care and Pain Medicine at the Massachusetts General Hospital. Dr. Faghih is the recipient of various awards including a 2024 IEEE Engineering Medicine and Biology Society (EMBS) Early Career Achievement Award, a 2023 National Institutes of Health (NIH) Maximizing Investigators’ Research Award for Early Stage Investigators, a 2020 National Science Foundation CAREER Award, a 2020 MIT Technology Review Innovator Under 35 award, and a 2016 IEEE-USA New Face of Engineering award. In 2020, she was featured by the IEEE Women in Engineering Magazine as a “Woman to Watch”. She is on the editorial board of PNAS Nexus by the National Academy of Sciences, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Neural Systems and Rehabilitation Engineering. Moreover, she is a senior member of IEEE and currently an IEEE Engineering in Medicine and Biology Society Administrative Committee Technical Representative. Dr. Faghih is the senior author of a Biomedical Engineering book titled Bayesian Filter Design for Computational Medicine published by Springer. Her research interests include wearable technologies, and medical cyber-physical systems, as well as neural and biomedical signal processing.