Sotabase

Career

· Co-Founder, Optimal Intellect (Current)2025–
· Co-Founder, Day One Health & Wellness2023–
· Algorithmic Trader, Tower Research Capital2023–2023
· Founder CEO, Convex Trading LLC2021–2023
· Research Consultant, AI Lab, BlackRock2020–2021
· Research Intern, AI Lab, BlackRock2020–2020
· Consultant, San Francisco Giants2020–2021
· Software Engineering Intern, Level 5, Autonomous Driving Division, Lyft2019–2019
· Doctor of Philosophy - PhD, Electrical Engineering, Stanford University2017–2021
· PhD, Boyd Convex Optimization Group, Stanford University2017–2021
· Platform Engineering Intern, Soroco2016–2016
· Undergraduate Student Researcher, Sahai Wireless Foundations Lab, UC Berkeley Electrical Engineering & Computer Sciences (EECS)2016–2017
· Hardware Engineering Intern, Terra Bella, Google2015–2015
· Undergraduate Student Researcher, Abbeel Robot Learning Lab, University of California, Berkeley2014–2014
· Bachelor of Science - BS, Electrical Engineering and Computer Science, 3.98/4.0, University of California, Berkeley2013–2017
· IOS Developer, Make School2012–2012
· Intern, Qualcomm2012–2012

Publications (33)

Differentiable Convex Optimization Layers
Neural Information Processing Systems · 2019
781
cited
A Note on the Inception Score
2018
780
cited
Differentiating through a cone program
2019
151
cited
Learning Convex Optimization Control Policies
2019
80
cited
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace From Position Data
IEEE transactions on intelligent transportation systems (Print) · 2018
75
cited
On the Differentiability of the Solution to Convex Optimization Problems
2018
60
cited
Learning Convex Optimization Models
2020
52
cited
Fitting a Kalman Smoother to Data
2019
44
cited
Cooperative Multi-Agent Reinforcement Learning for Low-Level Wireless Communication
arXiv.org · 2018
28
cited
Differentiating Through a Conic Program
2019
28
cited
Least squares auto-tuning
2019
27
cited
A Distributed Method for Fitting Laplacian Regularized Stratified Models
2019
26
cited
InterpNET: Neural Introspection for Interpretable Deep Learning
2017
25
cited
Covariance prediction via convex optimization
2021
16
cited
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint
Conference on Learning for Dynamics & Control · 2020
15
cited
Improved Training with Curriculum GANs
arXiv.org · 2018
15
cited
A non-rigid point and normal registration algorithm with applications to learning from demonstrations
IEEE International Conference on Robotics and Automation · 2015
14
cited
Stochastic Control With Affine Dynamics and Extended Quadratic Costs
2018
12
cited
Minimizing a sum of clipped convex functions
2019
10
cited
A Matrix Gaussian Distribution
2018
9
cited
Sotabase