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Hi, welcome to my webpage!

Currently, I am working as an Assistant Professor in the Department of Computer Science and Engineering at IIT Hyderabad.

Prior to joining IITH, I spent three pleasant years in the Shivalik Range of the Himalayas as an Assistant Professor at the School of Computing and Electrical Engineering (SCEE), IIT Mandi.

I am an algorithmist, and work in the intersection of theory and practice. I am interested in developing "extremely simple", practical approximation algorithms with provable performance guarantees for real-world problems. Among other things, my current research focuses around sketching/dimensionality reduction algorithms. In particular, I'm focusing on: a) developing new sketching/dimensionality reduction algorithms for various data types and similarity measures, b) improving existing sketching/dimensionality reduction algorithms by making them fast, scalable and accurate, and c) exploring applicability of such results in various machine learning tasks such as learning node embedding in large scale network, itemset mining, model compression etc.

I generally use techniques from matrix algebra, sampling, random projection, and randomized hashing.

I earned my Ph.D. in Theoretical Computer Science from Chennai Mathematical Institute (Aug 2009 - Nov 2014).

Previously, I have been working with industry research labs in the areas of algorithms in Data Science and Machine Learning at Wipro-AI Research, Bangalore; and TCS Innovation Labs, New Delhi. I have also spent a few months at IIIT Bangalore as a Research Associate.

Openings: I'm looking for highly motivated MS/PhD students to work on the areas mentioned above.

Note: I am not taking students for any short term internships (summer/winter). Unfortunately, I will be unable to individually respond to such emails/queries. Please contact me only if you are interested in at least a year long project, and have strong academic credentials.

My Erdös Number is 3.

Recent News:

• Our paper “Improving Sign-Random-Projection via Count Sketch” joint work Punit Pankaj Dubey, Bhisham Dev Verma, and Keegan Kang got accepted in the UAI-2022.

• Our paper “One-pass additive-error subset selection for $\ell_{p}$ subspace approximation” joint work with Amit Deshpande got accepted in the ICALP-2022.

• Our paper “Variance reduction in Feature Hashing using MLE and Control Variate Method” joint work with Bhisham Dev Verma and Manoj Thakur got accepted in the Machine Learning journal, 2022.

• Our paper “Efficient Binary Embedding of Categorical Data using BinSketch” joint work with Bhisham Dev Verma, and Debajyoti Bera has been accepted in the journal of Data Mining and Knowledge Discovery-2022.

• Our paper “Dimensionality Reduction for Categorical Data” joint work with Debajyoti Bera and Bhisham Dev Verma got accepted in the IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

• Our paper “QUINT: Node embedding using network hashing” joint work with Debajyoti Bera, Bhisham Dev Verma, Biswadeep Sen, and Tanmoy Chakraborty got accepted in the IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

Old News:

• Our paper "Feature Hashing with Insertion and Deletion of Features" joint work with Hrushikesh Sudam Sarode, Suryakant Bhardwaj and Raghav Kulkarni got accepted in the IEEE International Conference on Big Data (IEEE-Big data-2021).

• Delivered a keynote talk at “Data Analytics and Predictive technologies” organised by IIT-BHU on 8th July, 2021. I presented our recent work on "Sketching and Sampling Techniques for Big Data ''.

• Delivered a keynote talk at “Online short term course on Data Analytics and its Application in Industries” organised by IIT-BHU on 19th December, 2020. I presented our recent paper “Efficient Sketching Algorithms for Sparse Binary Data”.

• Our following two papers got accepted in ACML 2020

1) Randomness Efficient Feature Hashing for Sparse Binary Data. Joint work with Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni.

2) Scaling up Simhash. Joint work with Anup Deshmukh, Pratheeksha Nair, Anirudh Ravi. This paper was also invited for Special Issue in Springer Nature Computer Science.

• We (Mukesh Prasad, Rameshwar Pratap, Rajiv Ratn Shah, Weiping Ding, Javier Andreu-Perez, Guandong Xu) are organising a special session on “Feature Extraction and Learning on Image and Text Data” to be held in conjunction with the conference “IEEE International Conference on Systems, Man and Cybernetics (SMC)-2020”. You may consider submitting your paper. Further details are available here.

• Amit Sangroya (TCS Research) and I are co-chairing IEEE BigMM’20 Grand Challenge which is to be held in conjunction with the IEEE International Conference on Multimedia Big Data from September 24-26, 2020 at New Delhi. You may consider submitting your Grand challenge proposal to us. Further details are available here.