Sotabase

Career

· Robotics Engineer, Dexterity2020–
· Research Scientist, OpenAI2020–
· Research Intern, Perception Team, Lyft2019–
· PhD in Computer Science, Stanford University2015–2020
· Research Assistant, Graphics Lab, Stanford University2015–2015
· Research Assistant, Data Mining Group, University of Illinois, Urbana-Champaign2014–2014
· Research Assistant, Parallel Programming Laboratory, University of Illinois, Urbana-Champaign2013–2013
· B.S. in Engineering Physics, Minor in Computer Science, University of Illinois Urbana-Champaign2007–2015
· Dexterity

Publications (24)

Sample-efficient safety assurances using conformal prediction
Workshop on the Algorithmic Foundations of Robotics · 2021
65
cited
Belief Propagation Neural Networks
Neural Information Processing Systems · 2020
47
cited
Query-Based Outlier Detection in Heterogeneous Information Networks
International Conference on Extending Database Technology · 2015
20
cited
Adaptive Hashing for Model Counting
Conference on Uncertainty in Artificial Intelligence · 2019
10
cited
Approximating the Permanent by Sampling from Adaptive Partitions
Neural Information Processing Systems · 2019
8
cited
Approximate Inference via Weighted Rademacher Complexity
AAAI Conference on Artificial Intelligence · 2018
7
cited
Target Tracking with Kalman Filtering
2016
7
cited
Privacy Preserving Recalibration under Domain Shift
arXiv.org · 2020
3
cited
Diagnostic Runtime Monitoring with Martingales
arXiv.org · 2024
2
cited
Equivariant Neural Network for Factor Graphs
arXiv.org · 2021
1
cited
Fast approximate inference: shifting the Pareto frontier via adaptation
2020
Our approach most closely resembles a recent line of work involving the Gumbel distribution ( Hazan and Jaakkola 2012
2017
Sotabase
Jonathan Kuck | Researcher Profile | Sotabase | Sotabase