I am a senior PhD student in the Department of Computer Science at the Indian Institute of Technology, Delhi and a Google PhD Fellow. My PhD advisor is Dr. Manik Varma. I completed my bachelor's and master's degree in Mechanical Engineering from the Indian Institute of Technology, Kanpur in the year 2012.
My primary research interest is in Extreme Classification which is a new paradigm for solving ranking and recommendation problems. In particular, I have been focussing on two aspects -
I have applied my algorithms to solve real-world problems such as query-recommendation on a search engine, where they have shown significant improvements over existing systems.
H. Jain, V. Balasubramanian, B. Chunduri and M. Varma.
Slice: Scalable linear extreme classifiers trained on 100 million labels for related searches.
In Proceedings of the ACM International Conference on Web Search and Data Mining, Melbourne, Australia, Feburary 2019. [Best Paper Award]
Bibtex source | Abstract | Download in pdf format | Supplmentary in pdf format | Code | Extreme Classification Repository | Blog
H. Jain, Y. Prabhu and M. Varma.
Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications.
In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Francisco, California, August 2016.
Bibtex source | Abstract | Download in pdf format | Supplmentary in pdf format | Code | Extreme Classification Repository
K. Bhatia, H. Jain, P. Kar, M. Varma and P. Jain.
Sparse local embeddings for extreme multi-label classification.
In Advances in Neural Information Processing Systems, Montreal, Canada, December 2015.
Bibtex source | Abstract | Download in pdf format | Code | Extreme Classification Repository
This repository provides benchmark multi-label datasets and code that can be used for evaluating the performance of extreme multi-label algorithms. It also provides comparative results of various algorithms on all the benchmark datasets.
I love trekking, and aim to go for atleast 2 treks per year but as is usually the case, haven't been able to manage that :(
So far I have been to the following treks: