Hi! I am a PhD student at Yale University in the Department of Statistics and Data Science, where I am advised by Prof. Elisa Celis. Prior to this, I was at École Polytechnique Fédérale de Lausanne (EPFL) for two years.

I am interested in problems related to machine learning, algorithmic fairness and social networks. Broadly, I am intrigued by interactions between society and automation and the various questions around the potentially discriminatory impacts of AI applications.

I received my Bachelor and Master degrees in Computer Science and Engineering from Indian Institute of Technology, Kanpur under the supervision of Prof. Rajat Mittal.

I am on the job market for ethical AI positions.

Publications and Preprints

• Vijay Keswani, L. Elisa Celis
  Addressing Strategic Manipulation Disparities in Fair Classification
  Working paper. arxiv

• Vijay Keswani, L. Elisa Celis
  An Anti-Subordination Approach to Fair Classification
  EAAMO 2022 (Poster). ssrn

• Florian Evéquoz, Johan Rochel, Vijay Keswani, L. Elisa Celis
  Diverse Representation via Computational Participatory Elections – Lessons from a Case Study
  EAAMO 2022. arxiv

• Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi
  A Convergent and Dimension-Independent Min-Max Optimization Algorithm
  ICML 2022. arxiv

• Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
  Designing human-in-the-loop approaches for closed deferral pipelines
  BHCC 2021. arxiv

• Vijay Keswani, L. Elisa Celis
  Auditing for Diversity using Representative Examples
  ACM SIGKDD 2021. arxiv

• Vijay Keswani, Matthew Lease, Krishnaram Kenthapadi
  Towards Unbiased and Accurate Deferral to Multiple Experts
  AIES 2021. arxiv

• L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi
  Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees
  ICML 2021. arxiv

• Vijay Keswani, L. Elisa Celis
  Dialect Diversity in Text Summarization on Twitter
  The Web Conference 2021. arxiv

• L. Elisa Celis, Vijay Keswani
  Implicit Diversity in Image Summarization
  CSCW 2020. arxiv

• L. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi
  Data preprocessing to mitigate bias: A maximum entropy based approach
  ICML 2020. arxiv

• L. Elisa Celis, Vijay Keswani
  Improved Adversarial Learning for Fair Classification
  arxiv

• L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Vijay Keswani, Nisheeth K. Vishnoi
  A Dashboard for Controlling Polarization in Personalization
  Invited paper in AI Communications 2019 (Previously in IJCAI-ECAI 2018)

• L. Elisa Celis, Lingxiao Huang, Vijay Keswani and Nisheeth K. Vishnoi
  Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
  ACM-FAT* 2019. arxiv

• L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, Nisheeth K. Vishnoi
  Fair and Diverse DPP-based Data Summarization
  ICML 2018. arxiv

Fairness in AI

• Check out the website controlling-bias.github.io for demos related to the algorithms we have developed to control bias in AI.

Master’s Thesis

• Laplacian Solvers and Graph Sparsification (pdf)
  Supervised by Prof. Rajat Mittal.