Omid Sadeghi

Omid Sadeghi

Lead Research Scientist @ 84.51°

Biography

As of September 2024, I am a lead research scientist at 84.51°. Before that, I was a Postdoctoral Associate at the MIT Sloan School of Management, supervised by Prof. Negin Golrezaei. I received my Ph.D. from the Electrical and Computer Engineering department at the University of Washington in December 2023, supervised by Prof. Maryam Fazel (you can find my dissertation here). Before that, I obtained my Master's degree in Mathematics (with a focus on mathematical optimization) also from UW. Before coming to UW, I earned my bachelor's at the Sharif University of Technology, where I obtained a B.S. degree in Electrical Engineering and Math. Also, during my undergraduate studies, I spent the summer of 2015 as a junior research assistant at the Chinese University of Hong Kong (CUHK) under the supervision of Prof. Chandra Nair.

Competencies: Python, CVXPY, Scikit-learn, Pandas.

In my spare time, you can find me learning new languages (currently learning German and Spanish), going for a run, or playing soccer. I am also a certified Heroic Life Coach.

Research Interest

I specialize in applying convex optimization tools to tackle non-convex problems in Machine Learning under various additional limitations (e.g., limited resource/budget availability, privacy, incentive compatibility, and fairness) and in both online and offline settings. My research finds applications in online advertising and online resource allocation problems. Most of my works fall into one of the following categories:

Online Learning Submodular Optimization Privacy and Incentives in ML

Publications

Peer-reviewed papers and workshop talks. Filter by topic, or see everything on Google Scholar.

NeurIPS 2023

No-Regret Online Prediction with Strategic Experts

with Maryam Fazel

NeurIPS 2023

TL;DRDevelops prediction algorithms that work even when experts can strategically manipulate their advice, ensuring robust performance in adversarial settings.

ICML Workshop 2021

Improved Regret Bounds for Online Submodular Maximization

with Maryam Fazel

ICML 2021 Workshop on Subset Selection in Machine Learning: From Theory to Applications

TL;DRProvides better theoretical guarantees for online learning algorithms that select diverse and representative subsets of data in real-time applications.

ICML Workshop 2020

Online Algorithms for Budget-Constrained DR-Submodular Maximization

with Reza Eghbali and Maryam Fazel

ICML 2020 Workshop on Negative Dependence and Submodularity for ML

TL;DRDevelops online optimization algorithms that maximize objective functions while staying within budget limits, with applications to advertising and resource allocation.

Notes and Surveys

Course projects and surveys from my time at UW.

PDF Spring 2021

Data-Dependent Regret Bounds for Bandits Problems

with Max Gray and Tanner Fiez

TL;DRSurvey of multi-armed bandit algorithms with performance guarantees that adapt to the actual difficulty of the problem instance, providing tighter theoretical bounds.

PDF Winter 2021

Online Adversarial Zero-Sum Games

TL;DRComprehensive notes on game theory algorithms for competitive scenarios where one player's gain equals another's loss, with applications to security and economics.

PDF Spring 2020

Introduction to Spectral Graph Theory

with Catherine Babecki and Kevin Liu

TL;DRTutorial on using linear algebra to analyze network structures, covering eigenvalues and eigenvectors of graphs with applications to clustering and network analysis.

PDF Winter 2018

Linear Regression and Sequential Experimental Design

with Johannes Linder, Felix Leeb, and Sumit Mukherjee

TL;DRGuide to optimally designing experiments over time to learn linear relationships, balancing exploration of new conditions with exploitation of known information.

Wisdom Unlocked

The three big ideas I took away from each book I've read. Pick a cover to open it.

3 big ideas

    Contact

    The best way to reach me is by email. I'm always happy to chat about optimization, online learning, or good books.

    Google Scholar Papers and citations LinkedIn in/sadeghiomid