🚀 Building the future of GTM & warm outbound

Research on planning under uncertainty:

• Partially-observable Markov decision processes (POMDPs) with non-acting observers (smart infrastructure for self-driving)

• Markov decision processes (MDPs) on graph diffusion problems (social networks, heat conduction, epidemics)

• Artificial Intelligence (January 2022, January 2021; Eduexplora)

• Numerical Simulation (August 2021; Stanford Pre-Collegiate Studies)

• Technology in the World Today (July 2021; August 2021; Pre-Collegiate Pathways)

• Artificial Intelligence (June 2020; August 2020; June 2021; Stanford Pre-Collegiate Studies)

Two-week courses at various levels:

• 11th-12th grade: undergraduate-level course including the fundamentals of AI, ML, & optimization with deep exposure to mathematics, algorithms, and programming; includes supervised, unsupervised, and reinforcement learning algorithms.

• 9th-11th grade: survey & project course focused on the fundamentals of AI & ML with moderate exposure to algorithms & programming; project-based design thinking & data literacy.

• 7th-9th grade: survey & project course considering the core concepts of AI (perception, representation & reasoning, learning, natural interaction, and societal impact)