Summary
Bhaskar Mishra is a Ph.D. student and graduate researcher at UC Berkeley’s Center for Human-Compatible AI, advised by Stuart Russell, focusing on scalable inference for probabilistic-logic programs and broader interests in knowledge representation and cognitive architectures. With nine years of combined research and engineering experience, he has contributed to algorithmic game theory, PDE solvers on curved surfaces, and competitive AI agents—work that has resulted in conference presentations and first-author publications. Comfortable bridging theory and implementation, he has applied statistical convergence theorems to learning properties of simulation-based games and engineered practical Python libraries for scientific computing. Based in Berkeley, he blends rigorous CS and math training with eclectic intellectual pursuits—often reading philosophy, rock climbing, or playing Tetris—which inform a thoughtful, multidisciplinary approach to AI research.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Berkeley
High School Diploma, 10-12, High School Diploma, 10-12 at West Broward High School
Bachelor of Science - BS, Mathematics and Computer Science, Bachelor of Science - BS, Mathematics and Computer Science at University of Florida