Sotabase

Career

· Board Member, Qualcomm2025–
· Chief Expert, Bosch USA2024–2025
· Professor And Director, Machine Learning Department, Carnegie Mellon University2024–
· Chief Technical Advisor, Gray Swan AI2024–
· Board Member, OpenAI2024–
· VP And Chief Scientist Of AI Research, Bosch USA2022–2024
· Associate Professor (w Tenure), Carnegie Mellon University2021–2024
· Chief Scientist Of AI Research, Bosch USA2018–2022
· Associate Professor, Carnegie Mellon University2018–2021
· Chief Data Scientist, C3.ai2014–2018
· Assistant Professor, Carnegie Mellon University2012–2018
· Postdoctoral Fellow, Massachusetts Institute of Technology (MIT)2010–2012
· Doctor of Philosophy (Ph.D.), Computer Science, Stanford University2005–2010
· Bachelor of Science (BS), Computer Science, Georgetown University2001–2005

Publications (0)

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
arXiv.org · 2018
6,006
cited
Universal and Transferable Adversarial Attacks on Aligned Language Models
arXiv.org · 2023
2,427
cited
Certified Adversarial Robustness via Randomized Smoothing
International Conference on Machine Learning · 2019
2,319
cited
Multimodal Transformer for Unaligned Multimodal Language Sequences
Annual Meeting of the Association for Computational Linguistics · 2019
1,829
cited
Provable defenses against adversarial examples via the convex outer adversarial polytope
International Conference on Machine Learning · 2017
1,574
cited
REDD : A Public Data Set for Energy Disaggregation Research
2011
1,405
cited
Towards fully autonomous driving: Systems and algorithms
2011 IEEE Intelligent Vehicles Symposium (IV) · 2011
1,330
cited
Fast is better than free: Revisiting adversarial training
International Conference on Learning Representations · 2020
1,305
cited
OptNet: Differentiable Optimization as a Layer in Neural Networks
International Conference on Machine Learning · 2017
1,126
cited
Deep Equilibrium Models
Neural Information Processing Systems · 2019
791
cited
Differentiable Convex Optimization Layers
Neural Information Processing Systems · 2019
781
cited
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
Journal of machine learning research · 2007
764
cited
Input Convex Neural Networks
International Conference on Machine Learning · 2016
754
cited
A Simple and Effective Pruning Approach for Large Language Models
International Conference on Learning Representations · 2023
685
cited
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
International Conference on Artificial Intelligence and Statistics · 2012
669
cited
Learning to Detect and Classify Malicious Executables in the Wild
Journal of machine learning research · 2006
657
cited
Learning to detect malicious executables in the wild
Knowledge Discovery and Data Mining · 2004
551
cited
Patches Are All You Need?
Trans. Mach. Learn. Res. · 2022
491
cited
Scaling provable adversarial defenses
Neural Information Processing Systems · 2018
465
cited
Dynamic weighted majority: a new ensemble method for tracking concept drift
Third IEEE International Conference on Data Mining · 2003
439
cited
Sotabase