Alexander Gray Email & Phone Number

Uniquely broad experience in "practical theory and theory-guided practice" - both basic research on ML/AI algorithms/theoretical frameworks and designing practical ML/AI solutions for a large number of difficult use cases across sciences and industries - in government, academia, startup, big companies.General interests: (for more details, see Publications Section below)- NLP and large language models (toward more precise and factual NLP)- Neuro-symbolic AI (toward explainable, knowledge-augmented, and small-data AI)- Human-AI collaboration and visualization:- Data science (applied ML) methodology (toward best practical results in ML)- Data science (applied ML) use cases- Common ML computations for big data (toward practical fast algorithms)- Exploratory data analysis and density estimation- Optimization- Program generation and probabilistic programming (toward automated derivation of code and algorithms)- Sequential decision making/RL and design of experiments- Teaching innovationGlobal program on neuro-symbolic AI created/led since 2018:https://ibm.biz/nsworkshop2023/ winter 2023: 5000+ registrations (second research event)http://ibm.biz/ns-wkshp summer 2022: 6000+ (first educational event)http://ibm.biz/nsss2022 winter 2022: 1500+ registrations (first research event)