Hoda Heidari

About

I am an Assistant Professor at Carnegie Mellon University with joint appointments in the Machine Learning Department and the Institute for Software Research.

I am broadly interested in Societal Aspects of Artificial Intelligence and Machine Learning and Algorithmic Economics. For more information, please find my CV here.

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Research

Publications:

• Stateful Strategic Regression
  K. Harris, H. Heidari, and S. Wu
  Neural and Information Processing Systems (NeurIPS), 2021.


• On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes
  H. Heidari, S. Barocas, J. Kleinberg, and K. Levy
  The ACM Conference on Economics and Computation (EC), 2021. Winner of an Exemplary Track Award at EC.


• Addressing the Long-term Impact of ML Decisions via Policy Regret
  D. Lindner, H. Heidari, and A. Krause
  The International Joint Conference on Artificial Intelligence (IJCAI), 2021.


• Fair equality of chances: fairness for statistical prediction-based decision-making
  M. Loi, A. Herlitz, and H. Heidari
  AAAI /ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2021.


• A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness
  M. Yaghini, A. Krause, and H. Heidari
  AAAI /ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2021.


• Allocating Opportunities in a Dynamic Model of Intergenerational Mobility
  H. Heidari, J. Kleinberg
  The ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021. Winner of a Best Paper Award at FAccT.


• On the Desiderata for Online Altruism: Nudging for Equitable Donations
  N. Mota, A. Chakraborty, A. J. Biega, K. P. Gummadi, H. Heidari
  The ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2020


• Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning
  M. Srivastava, H. Heidari, A. Krause
  The International Conference on Knowledge Discovery and Data Mining (KDD), 2019


• On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning
  H. Heidari, V. Nanda, K. P. Gummadi
  The International Conference on Machine Learning (ICML), 2019


• A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity
  H. Heidari, M. Loi, K. P. Gummadi, A. Krause
  The ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*), 2019


• On the Impact of Choice Architectures on Inequality in Online Donation Platforms
  A. Chakraborty, N. Mota, A. J. Biega, K. P. Gummadi, H. Heidari
  The Web Conference (WWW), 2019


• Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
  H. Heidari, C. Ferrari, K. P. Gummadi, A. Krause
  Neural and Information Processing Systems (NeurIPS), 2018


• A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual and Group Unfairness via Inequality Indices
  T. Speicher, H. Heidari, N. Grgic-Hlaca, K. P. Gummadi, A. Singla, A. Weller, M. B. Zafar
  The International Conference on Knowledge Discovery and Data Mining (KDD), 2018


• Fairness in Criminal Justice Risk Assessments: The State of the Art
  R. Berk, H. Heidari, S. Jabbari, M. Kearns, A. Roth
  Sociological Methods and Research, 2018


• Preventing Disparate Treatment in Sequential Decision Making
  H. Heidari, A. Krause
  The International Joint Conference on Artificial Intelligence (IJCAI), 2018


• A Convex Framework for Fair Regression
  R. Berk, H. Heidari, S. Jabbari, M. Joseph, M. Kearns, J. Morgenstern, S. Neel, A. Roth
  In FAT-ML Workshop, 2017


• Pricing a Low-regret Seller
  H. Heidari, M. Mahdian, U. Syed, S. Vassilvistskii, S. Yazdanbod
  The International Conference on Machine Learning (ICML), 2016


• Tight Policy Regret Bounds for Improving and Decaying Bandits
  H. Heidari, M. Kearns, A. Roth
  The International Joint Conference on Artificial Intelligence (IJCAI), 2016


• Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  H. Heidari, S. Lahaie, D. Pennock, J. W. Vaughan
  The ACM Conference on Economics and Computation (EC), 2015


• Competitive contagion in networks
  S. Goyal, H. Heidari, M. Kearns
  Games and Economic Behavior, Elsevier, 2014


• Learning from Contagion (Without Timestamps)
  K. Amin, H. Heidari, M. Kearns
  The International Conference on Machine Learning (ICML), 2014


• New Models for Competitive Contagion
  M. Draief, H. Heidari, M. Kearns
  The AAAI Conference on Artificial Intelligence (AAAI), 2014


• Depth-Workload Tradeoffs for Workforce Organization
  H. Heidari, M. Kearns
  The Conference on Human Computation & Crowdsourcing (HCOMP), 2013

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Teaching

In Fall 2021, I will be teaching Machine Learning, Ethics, and Society. For more information, please visit the course webpage.

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Activities

Organizer:

• NeurIPS Workshop on Human-centric Machine Learning, co-organizer 2019
• Tutorial on Economic Theories of Distributive Justice for Fair ML at the 30th Web Conference (WWW), 2019
• Weekly reading group on the “Societal Aspects of AI”, ETHZ 2017, 2018

Program Committee:

• ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*), 2019
• The AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2019
• The International Conference in Machine Learning (ICML), 2016---2019
• The Conference on Economics and Computation (EC), 2015, 2018
• The Conference on Artificial Intelligence (AAAI), 2018, 2020