Postdoctoral Researchers

If you are interested in becoming a Postdoctoral Researcher, please see the Participate page.

Simons-Berkeley Postdoctoral Researcher

Yosi Atia
Quantum Algorithms, Adiabatic Quantum Computing, Quantum Walks, Uncertainty Relations, Foundations Of Quantum Mechanics, Quantum Gravity.
Siddharth Sandipkumar Bhandari
Zero-Error Information Theory, Coding Theory, Sampling Algorithms And Theoretical Guarantees For Generative Networks
William Hoza
Pseudorandomness, Derandomization, Complexity Theory
Jason Li
Graph Algorithms, Combinatorial Optimization, Maximum Flow, Minimum Cut, Shortest Path, Parameterized Complexity
Fermi Ma
Cryptography, Quantum Information, Interactive Proof Systems
Makrand Sinha
Complexity Theory, Quantum Computing, Stochastic Processes, Optimization
Jan van den Brand
Data Structures, Algebraic Algorithms, Optimization
Carrie Wu
Reinforcement Learning, Optimization, High Dimensional Statistics

Quantum Postdoctoral Researcher

Nilin Abrahamsen
Quantum Complexity, Local Hamiltonians, Electronic Structure Theory, Quantum Chemistry
Anurag Anshu
Quantum Computing, Quantum Communication, Hamiltonian Complexity
Yosi Atia
Quantum Algorithms, Adiabatic Quantum Computing, Quantum Walks, Uncertainty Relations, Foundations Of Quantum Mechanics, Quantum Gravity.
Adam Bouland
Quantum Computation, Computational Complexity Theory, And Connections With Physics
Andrea Coladangelo
Quantum Cryptography, Quantum Computing, Non-Locality and Entanglement
Yassine Hamoudi
Quantum Computing, Algorithm Theory, Computational Complexity, Monte Carlo Method
Qipeng Liu
Quantum Cryptography, Quantum Information
Fermi Ma
Cryptography, Quantum Information, Interactive Proof Systems
Makrand Sinha
Torin Stetina
Hamiltonian Simulation, Quantum Chemistry, Relativistic Electronic Structure

Machine Learning Postdoctoral Researcher

Stephen Bates
High-Dimensional Statistics, Causal Inference, Statistical Inference With Ml Models
Lin Chen
Machine Learning Theory
Sitan Chen
ML Theory (Robust Statistics, Deep Learning, Distribution Learning) And Quantum Learning
Luiz Fernando de Oliveira Chamon
Optimization, Constrained Learning, Signal Processing, Control
Mahsa Derakhshan
Spencer Frei
Deep Learning, Statistical Learning Theory, Optimization
Yanjun Han
High-Dimensional And Nonparametric Statistics, Information Theory, Online Learning And Bandits
Wei Hu
Machine Learning Theory, Deep Learning Theory
Frederic Koehler
Computational Learning Theory, Algorithms, Sampling, High-Dimensional Statistics
Adil Salim
Optimization, Sampling, Probability, Optimal Transport, Machine Learning
Dennis Shen
Causal Inference, Machine Learning, Statistics
Jan van den Brand
Data Structures, Algebraic Algorithms, Optimization
Ellen Vitercik
Machine Learning Theory; Algorithm Design; Economics And Computation
Carrie Wu
Reinforcement Learning, Optimization, High Dimensional Statistics
Manolis Zampetakis
Andrea Zanette
Reinforcement Learning, Machine Learning, Optimization, Statistics
Angela Zhou
Statistical Machine Learning, Causal Inference, Sequential Decision Making Under Uncertainty