Ashudeep Singh


349, Bill and Melinda Gates Hall

107 Hoy Rd

Ithaca, NY-14853

mail@ashudeepsingh.com

I am a Ph.D. Candidate in Computer Science at Cornell University in Ithaca, NY. I am advised by Thorsten Joachims. I am fortunate to have Solon Barocas, Karthik Sridharan and David Mimno on my dissertation committee.

My research focuses on Fairness and Responsibility aspects of Machine Learning algorithms for Search and Recommendation systems. Through my research, I envision these search and recommendation systems to form the foundation for building economically sustainable multistakeholder platforms. In my research, I have developed notions and algorithms for fair distribution of opportunity and benefits for the both the stakeholders–users as well as the content providers.

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


news

Sep 20, 2020 Our new work on Building Healthy Recommendation Sequences for Everyone: A Safe Reinforcement Learning Approach has been accepted at FAccTRec workshop on Responsible Recommendation at ACM RecSys 2020 to be held from September 22-26, 2020. This is joint work with my collaborators at Google Research.
Aug 19, 2020 Communications of the ACM (CACM) and Cornell Chronicle covered a story about our ACM SIGIR 2020 paper Controlling Fairness and Bias in Dynamic Learning-to-Rank. :newspaper:
Jul 22, 2020 New: Our paper Controlling Fairness and Bias in Dynamic Learning-to-Rank has been awarded the Best Paper Award at the ACM SIGIR 2020 conference that was held virtually. :trophy:

publications

Find more information on google scholar.

* contributed equally.

  1. 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
  2. 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.
  1. NeurIPS
    Policy learning for fairness in ranking
    Ashudeep Singh, and Thorsten Joachims
    In Neural Information Processing Systems (NeurIPS), 2019.
  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.
  1. NeurIPS Workshop
    Equality of Opportunity in Rankings
    Ashudeep Singh, and Thorsten Joachims
    In Workshop On Prioritizing Online Content (WPOC) at NeurIPS, 2017.
  2. NeurIPS Workshop
    Learning item embeddings using biased feedback
    Ashudeep Singh, and Thorsten Joachims
    In NeurIPS Workshop on Causal Inference and Machine Learning for Intelligent Decision Making, 2017.
  1. ICML
    Recommendations as treatments: Debiasing learning and evaluation
    Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims
    In International Conference on Machine Learning (ICML), 2016.
    1. Preprint
      A Semantic Approach to Summarization
      Divyanshu Bhartiya*, and Ashudeep Singh*
      arXiv preprint arXiv:1406.1203 2014.
    2. ITS
      Predicting student learning from conversational cues
      David Adamson, Akash Bharadwaj, Ashudeep Singh, Colin Ashe, David Yaron, and Carolyn P Rosé
      In International Conference on Intelligent Tutoring Systems (ITS), 2014.
    1. AIED
      Automatically generating discussion questions
      David Adamson, Divyanshu Bhartiya, Biman Gujral, Radhika Kedia, Ashudeep Singh, and Carolyn P. Rosé
      In International Conference on Artificial Intelligence in Education (AIED), 2013.