Adjunct Faculty, Carnegie Mellon; ex-SSgA & FDP Institute Advisory Board


Global executive and thought leader with deep experience employing AI for Health (e.g., founding advisor to entity that’s the nucleus of ICAD), Wealth (sold AI / ML asset-mgmt. boutique into SSgA; worked with marquee institutional clients and allocators like Paloma Partners) & Wisdom (co-PI for many iARPA projects: Novel Intelligence from Massive Data (NIMD), Pro-Active Intelligence (PAINT), NLP (METAPHOR), Multi-media analytics (ALADDIN ); multiple patents)

Pioneered multiple innovations, leading teams using multi-modal (incl. alternative) data and augmented intelligence. Currently working on new, impactful projects and ventures in the areas of boosting diversity (in investment management), bias-free AI and consilience.

Mentor / advisor at many entities (e.g., TiE.org, Sabudh.org, FDPinstitute.org; IvyCap Ventures).

The dynamic world produces data that is constantly changing. Financial markets can be particularly mercurial, triggered by geopolitical events, regulation changes, industry news and earnings outlook of companies. Exploiting data science to explain or predict the ebb and flow of security prices can be a bit of an art. Knowing which data – from the plethora of traditional and alternative datasets – to focus on, what techniques to use (e.g., traditional statistical, historical-data-intensive deep learning, reinforcement learning, forward-looking simulations or a combination); and, what aspects to model are nuanced decisions that will significantly affect portfolio risk and return. Human-machine teaming is also a focus area and I hope to address some of the above themes in my brief presentation. A subsequent panel will elicit multiple opinions in this milieu.