I am an Assistant Professor of Decisions, Operations and Technology Management at the UCLA Anderson School of Management. My research focuses on developing models that draw from optimization, machine learning, and game theory, often to address questions related to incentives, contracting, or competition. Application areas of my work include healthcare, urban mobility, and labor platforms.

Before joining UCLA, I received a PhD in Operations Research from the
University of California, Berkeley, an MASc in Industrial Engineering from the University of Toronto, and a BEng in Electrical Engineering from Dalhousie University, located in my hometown of Halifax, Canada.

Contact: auyon.siddiq@anderson.ucla.edu 
Suite B-511, Leon and Toby Gold Hall



Published / Accepted:

Ride-hailing Platforms: Competition and Autonomous Vehicles.
with Terry Taylor. 

Forthcoming, M&SOM. [PDF]

Partnerships in Urban Mobility: Incentive Mechanisms for Improving Public Transit Adoption.

with Christopher S. Tang and Jingwei Zhang.
Forthcoming, M&SOM. [PDF]

Data-Driven Incentive Design in the Medicare Shared Savings Program.
with Anil Aswani and Zuo-Jun (Max) Shen.
Operations Research, Vol 67, No 4: 1002--1026, 2019.  [

Inverse Optimization with Noisy Data.
with Anil Aswani and Zuo-Jun (Max) Shen.
Operations Research, Vol. 66, No. 3: 870--892, 2018.  [

Robust Defibrillator Deployment Under Cardiac Arrest Location Uncertainty via Row-and-Column Generation.
with Timothy C. Y. Chan and Zuo-Jun (Max) Shen.
Operations Research, Vol. 66, No. 2: 358--379, 2018.  [

Modeling the Impact of Public Access Defibrillator Range on Cardiac Arrest Coverage.
with Steven C. Brooks and Timothy C. Y. Chan.
Resuscitation, Vol. 84, No. 7: 904--909, 2013.  [

Working / Under review:

Estimation of a Non-Parametric Principal-Agent Model with Hidden Actions.

with Nur Kaynar.

Major revision, Management Science. [PDF]

Shield-Net: Matching Supply with Demand for Face Shields During the COVID-19 Pandemic.

with Rebecca Alcock and Justin Boutilier.

Major revision, INFORMS Journal on Applied Analytics. [PDF]

Discovering Causal Models with Optimization: Confounders, Cycles, and Feature Selection.

with Frederick Eberhardt and Nur Kaynar.

Submitted. [PDF]



Data and Decisions (MGMTFT 402), Full-Time MBA, Fall 2018, 2019, 2020.
Optimization (MGMTMSA 403), Master of Science in Business Analytics, Fall 2019, 2020.

Named to Poets&Quants Best 40 Under 40 Professors in 2020.