I'm a first-year computer science Ph.D. student at the Berkeley Artificial Intelligence Research Lab
, where I have the privilege of being co-advised by Sergey Levine
and Anca Dragan
I'm currently exploring the intersection of machine learning, robotics, and cognitive science as a member of the RAIL
labs. I'm interested in combining human and machine intelligence to solve sequential decision-making problems that neither can on their own.
In my undergraduate research, I developed a mathematical framework for spaced repetition
that can be used to improve long-term human learning, in collaboration with Thorsten Joachims
, Siddhartha Banerjee
, and Igor Labutov
. Our work on the Leitner Queue Network
combines ideas from queueing theory and psychology to optimize review scheduling in flashcard software. I also worked on the Latent Skill Embedding
, a probabilistic model of student knowledge and educational content that can be used to recommend personalized lesson sequences in online courses.
Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shared Autonomy via Deep Reinforcement Learning
, Robotics: Science and Systems, 2018.
Siddharth Reddy, Igor Labutov, Siddhartha Banerjee, Thorsten Joachims, Unbounded Human Learning: Optimal Scheduling for Spaced Repetition
, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016.
Siddharth Reddy, Anca D. Dragan, Sergey Levine, Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior
, arXiv, 2018.
Siddharth Reddy, Igor Labutov, Thorsten Joachims, Latent Skill Embedding for Personalized Lesson Sequence Recommendation
, arXiv, 2016.
Siddharth Reddy, Sergey Levine, Anca D. Dragan, Accelerating Human Learning with Deep Reinforcement Learning
, NIPS Workshop on Teaching Machines, Robots, and Humans, 2017.