Algorithms and AI Can Make Hiring More Diverse
The cost is likely minimal to achieve a fairer outcome.
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Biography
Rad Niazadeh is an Associate Professor of Operations Management at the University of 91吃瓜网 School of Business. He is also part of the faculty at the Toyota Technological Institute at Chicago (TTIC) by a courtesy appointment, and a faculty advisor at Lyft working with Fulfillment team. Prior to joining 91吃瓜网, Rad was a faculty researcher at the Google Research NYC's market algorithms team, and a postdoctoral fellow at Stanford University, Computer Science. He obtained his PhD in Computer Science (minored in Applied Mathematics) from Cornell University.听
Professor Niazadeh primarily studies the theory and practice of data-driven online decision-making in complex and dynamic operational scenarios. He develops (i) computationally and economically efficient real-time market algorithms and mechanisms for gig-economy platforms and electronic marketplaces, and (ii) sequential decision-making policies that prioritize equity, fairness, and non-discrimination in the operations of non-profit organizations, governmental agencies, and platforms.
Professor Niazadeh鈥檚 research has been published in journals such as Management Science, Operations Research, Mathematics of Operations Research, Journal of Machine Learning Research, Games and Economic Behavior, Journal of the ACM, Bernoulli, and in (peer-reviewed) top conference proceedings in computer science such as ACM STOC, IEEE FOCS, NeurIPS, ICML, ACM EC, ACM-SIAM SODA and ITCS.
Rad has received several awards for his research, including the Asness Junior Faculty Fellowship, INFORMS Auctions and Market Design Rothkopf Junior Researcher Paper Award (first place in 2021, second place in 2023, first place in 2024), INFORMS MSOM Best Student Paper Award 2024 (first place) , International Joint Conferences on Artificial Intelligence (IJCAI) 2024 Distinguished Paper Award, INFORMS Service Science IBM Best Student Paper Award (third place in 2023), INFORMS Data Mining Best Paper Award (finalist), the INFORMS Revenue Management and Pricing Dissertation Award (honorable mention), the Google PhD Fellowship in Market Algorithms, the Stanford Motwani fellowship, and the Cornell Jacobs fellowship.
Research Interests
Online algorithms and optimization in markets and platforms; Algorithmic mechanism design and game theory; Online learning theory and applications in operations management; Algorithmic aspects of machine learning and data science in management
Academic Areas
- Operations Management
Selected Publications
"Batching and Optimal Multi-stage Bipartite Allocations", with Yiding Feng, Management Science, 2024聽SSRN preprint: 3689448聽(preliminary conference version in ITCS'21)
"Near-optimal Bayesian Online Assortment of Reusable Resources", with Yiding Feng and Amin Saberi, Operations Research, 2024聽(preliminary conference version in ACM EC鈥�22)
"Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement", with Kirk Bansak, Soonbong Lee, Vahideh Manshadi, and Elisabeth Paulson, major revision from Management Science,聽SSRN preprint:4748762 (preliminary conference version in ACM EC'24)
"Online Matching with Cancellation Costs", with Farbod Ekbatani and Yiding Feng, major revision from Operations Research, SSRN preprint: 4245468 (preliminary conference version in ACM EC鈥�23)
"Markovian Search with Socially Aware Constraints", with Mohammad Reza Aminian and Vahideh Manshadi, major revision from Management Science, SSRN preprint: 4347447
"Robustness of Online Inventory Balancing Algorithm to Inventory Shocks", with Yiding Feng and Amin Saberi, major revision from Management Science, SSRN preprint:聽3795056
"Prophet Inequalities with Cancellation Costs", with Farbod Ekbatani, Pranav Nuti, and Jan Vondrak, SSRN preprint: 4779633 (preliminary conference version in ACM STOC'24)
"Online Job Assignment", with Farbod Ekbatani, Yiding Feng, and Ian Kash, SSRN preprint:聽4745629聽(preliminary conference version in MSOM Supply Chain SIG 2024)
"Misalignment, Learning, and Ranking: Harnessing Users Limited Attention", with Arpit Agarwal and Prathamesh Patil, SSRN preprint: 4365381
"Robust Dynamic Staffing with Predictions", with Yiding Feng and Vahideh Manshadi, SSRN preprint: 4732158聽(preliminary conference version in MSOM Service SIG 2024)
"Linear Programming Based Near-Optimal Pricing for Laminar Bayesian Online Selection", with Nima Anari, Ali Shameli, and Amin Saberi, minor revision from Mathmetics of Operations Research, SSRN preprint:聽3430156 (preliminary conference version in ACM EC'19)
"Bernoulli Factories for Flow-Based Polytopes", with聽With Jon Schneider and Renato Paes Leme,聽SIAM Journal on Discrete Mathematics (SIDMA), 2023.听
"Correlated Cluster-Based Randomized Experiments: Robust Variance Minimization", with Chen Chen and Ozan Candogan, Management Science, 2023 (preliminary conference version in ACM EC鈥�23)
"Online Bipartite Matching with Reusable Resources", with Steven Delong, Alireza Farhadi, Balu Sivan, and Rajan Udwani,聽Mathematics of Operations Research, 2023聽(preliminary conference version in ACM EC鈥�22)
"Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes", with聽Yuval Emek, Ron Lavi and Yangguang Shi, Mathematics of Operations Research (preliminary conference version in NeurIPS'20)
"Two-stage Stochastic Matching and Pricing with Applications to Ride Hailing", with Yiding Feng and Amin Saberi, Operations Research, 2023聽(preliminary conference version in ACM-SIAM SODA鈥�21, spotlight talk in RMP鈥�21 conference)
"Fair Dynamic Rationing", with Vahideh Manshadi and Scott Rodilitz,
Management Science, 2023聽(preliminary conference version in ACM EC鈥�21, spotlight talk in RMP鈥�21 conference)
"Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimiza-tion", with Negin Golrezaei, Joshua Wang, Fransisca Susan and Ashwinkumar Badanidiyuru, Management Science, 2022聽(preliminary conference version in ACM EC鈥�21)
"Sequential Submodular Maximization and Applications to Ranking an Assortment of Products", with Arash Asadpour, Amin Saberi and Ali Shameli,
Operations Research, 2022聽(preliminary conference version in ACM EC鈥�22)
"Combinatorial Bernoulli Factories", with Renato Paes Leme and Jon Schneider, Bernoulli (Journal of the Bernoulli Society), 2023聽(preliminary conference version in ACM STOC鈥�21)
"Bernoulli Factories and Black-Box Reductions in Mechanism Design", with Shaddin Dughmi, Jason Hartline and Robert Kleinberg,聽Journal of the ACM, 2021聽(preliminary conference version in ACM STOC鈥�17, presented at 6th World Congress of the Game Theory Society 鈥� GAMES鈥�21)
"Fast Core Pricing for Rich Advertising Auctions", with Jason Hartline, Mohammad Reza Khani, Nicole Immorlica, and Brendan Lucier,聽Operations Research (OR), 2020聽(preliminary conference version in ACM EC鈥�19)
"Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization", with Tim Roughgarden and Joshua Wang,
Journal of Machine Learning Research, 2020聽(preliminary conference version in 狈别耻谤滨笔厂鈥�18, oral presentation)
"Multi-scale Online Learning and its Applications to Online Auctions", with Se麓bastien Bubeck, Nikhil Devanur and Zhiyi Huang,聽Journal of Machine Learning Research, 2019聽(preliminary conference version in ACM EC鈥�17)
"Descending Price Auctions with Bounded Number of Price Levels and Batched Prophet Inequality", with Saeed Alaei, Ali Makhdoumi, and Azarakhsh Malekian, in Proc. 23rd ACM conference on Economics and Computation (础颁惭听EC 2022)
Working Papers
2025 - 2026 Course Schedule
| Number | Course Title | Quarter |
|---|---|---|
| Managerial Decision Modeling | 2025 (Autumn) | |
| Workshop in Operations/Management Science | 2025 (Autumn) | |
| Workshop in Operations/Management Science | 2026 (Spring) |
Get Insights from Rad Niazadeh in 91吃瓜网 Review
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Research explores a way to make AI recruiting decisions more fair.
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A Tool to Help Algorithms Cope with Human 鈥楪aming鈥�
User attempts to outwit algorithms can lead to less-optimal outcomes for everyone.
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