Shrikanth Narayanan, PhD

Professor of Electrical and Computer Engineering, Computer Science, Linguistics, Psychology, Pediatrics, and Otolaryngology

Niki and Max Nikias Chair in Engineering and University

Converging developments across the machine intelligence ecosystem-from multimodal sensing and signal processing to computing-are enabling new human-centered possibilities both in advancingscience and in the creation of technologies for societal applications including in human health and wellbeing. These technologies create unprecedented opportunities for acquisition, analysis and sharing of diverse, information-rich data that allow causal and multimodal characterization of an individual’s physical and psychological state with granularity, context, and scale not possible before. This includes behavioral machine intelligence - approaches for quantitatively and objectively understanding human behavior - with a specific focus on multimodal communicative, affective and social behavior; this can be additionally enriched with direct observations of physiology and neural activity.  These have applications in screening, diagnostics and treatment, including mapping progression. Using examples drawn from varied domains such as depression, suicide, autism spectrum disorder, dementia, addiction to workplace health and wellbeing, this talk will highlight some advances and possibilities in this realm in creating trustworthy human centered AI approaches.

Mohamed Elmeliegy, PhD

Senior Director Clinical Pharmacology (Pfizer)

Development of elranatamab (a BCMA x CD3 bispecific) in multiple myeloma and the role of quantitative systems pharmacology in accelerating development

Prashant Dogra, Ph.D

Assistant Research Professor, Houston Methodist Research Institute 

Integrating Biology and Data: Synergies Between Mechanistic Modeling and Machine Learning

Jason Coloma, Ph.D.

Chief Executive Officer of Maze Therapeutics