Ashudeep Singh

Applied Research Scientist, Pinterest.
Ph.D., Computer Science, Cornell University.
Résumé · CV

I am an Applied Research Scientist at Pinterest Labs where I build machine learning algorithms for inclusive and diverse recommendations at scale. In 2021, I completed my PhD in Computer Science at Cornell University in Ithaca, NY where I was advised by Thorsten Joachims along with Solon Barocas, Karthik Sridharan, and David Mimno on my dissertation committee.

My research spans the broad areas of Machine Learning, Recommender Systems, and Information Retrieval. My research focuses on:

  • Building machine learning models and algorithms to learn from interactive user feedback in user-facing platforms such as search and recommendation.
  • Fairness and Responsibility aspects of Recommender Systems considering fair distribution of opportunity for both users as well as the items.

Through my research, I envision search and recommendation systems to form the foundation of economically sustainable multistakeholder online platforms that ensure utility, fairness, and safety for the users as well as the creators and producers.

During my Ph.D., I have completed internships at Google Brain, Facebook Research, and Microsoft Research (NYC and Montreal) where I had the opportunity to collaborate closely with Alex Beutel, Fernando Diaz, Khalid El-Arini, John Langford. Previously, I was an undergraduate student at the Indian Institute of Technology (IIT) Kanpur and also spent a summer at Carnegie Mellon University doing research on Natural Language Processing. You can find more information on the resume and cv.


Dec 5, 2022 The slides to the NeurIPS 2022 tutorial on Fair and Socially Responsible ML for Recommendations are public. Download them here. Visit the NeurIPS portal to access the recording video if you are registered.
Sep 28, 2022 Hannah Korevaar (Meta), Manish Raghavan (MIT), and I are presenting a tutorial at NeurIPS 2022 on Fair and Socially Responsible ML for Recommendations.
Sep 29, 2021 Our paper “Fairness in Ranking under Uncertainty” has been accepted to NeurIPS 2021. This is joint work with my advisor Thorsten Joachims (Cornell) and David Kempe from USC. 📄
Aug 1, 2021 In August, I joined the Applied Science team at Pinterest. 💼
Jun 25, 2021 I successfully defended my PhD thesis. A big thanks to my advisor and the thesis committee. 🎓

selected publications

Find more information on the publications page and google scholar.

* contributed equally.

  1. KDD
    Fairness of Exposure in Rankings
    Ashudeep Singh, and Thorsten Joachims
    In In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, 2018.
  2. NeurIPS
    Policy learning for fairness in ranking
    Ashudeep Singh, and Thorsten Joachims
    In Neural Information Processing Systems (NeurIPS), 2019.
  3. SIGIR
    Controlling Fairness and Bias in Dynamic Learning-to-Rank
    Marco Morik*, Ashudeep Singh*, Jessica Hong, and Thorsten Joachims
    In Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval, 2020. Best Paper Award
  4. RecSys Workshop
    Building Healthy Recommendation Sequences for Everyone: A Safe Reinforcement Learning Approach
    Ashudeep Singh, Yoni Halpern, Nithum Thain, Konstantina Christakopoulou, Ed H. Chi, Jilin Chen, and Alex Beutel
    In FAccTRec Workshop at ACM RecSyS, 2020.
  5. NeurIPS
    Fairness in Ranking under Uncertainty
    Ashudeep Singh, David Kempe, and Thorsten Joachims
    In Neural Information Processing Systems (NeurIPS), 2021.