Rahul Gupta

Masters in Computer Science

Indian Institute of Technology, Kanpur

Biography

I am a graduate in Computer Science from Indian Institute of Technology, Kanpur. I have been fortunate to work with Prof. Kuldeep Meel from NUS and Prof. Subhajit Roy from IIT Kanpur who broadly led me into the world of Logic and Automated Reasoning in CS. I am currently working on analysing the size and compile times in Knowledge Compilations on random CNFs. Our works on sampling using knowledge compilations have been accepted to TACAS 2019 and LPAR 2019. In further past, my work on securing databases from insider attacks using Blockchains got published in workshop at ISRDC, IIT Bombay. I have also interned with Partner Center team on automating User Migration at Microsoft in summer of 2017.

I am always interested in exploring new territories in Computer Science by working on interesting and challenging problems. At other times, you can find me just reading a book, playing guitar or thinking into an abyss. I also like to take pics of appealing compositions whenever I can find them.

Interests

Knowledge Compilations
Constrained Sampling and Counting
Blockchains
Artificial Intelligence

Education

B.Tech - M.Tech (Dual Degree), 2019

Indian Institute of Technology, Kanpur
Class 12, 2014

DAV Public School, Kota, Rajasthan
Class 10, 2012

DAV Public School, Kota, Rajasthan

Recent Publications

Rahul Gupta, Shubham Sharma, Kuldeep S. Meel. WAPS: Weighted and Projected Sampling . In Proceedings of Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2019.

PDF Code

Shubham S. Srivastava, Medha Atre, Shubham Sharma, Rahul Gupta, Sandeep K. Shukla. Verity: Blockchains to Detect Insider Attacks in DBMS. 2019.

Preprint

Shubham Sharma, Rahul Gupta, Subhajit Roy, Kuldeep Meel. Knowledge Compilation meets Uniform Sampling. In Proceedings of International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), 2018.

PDF Code

Shubham Sharma, Rahul Gupta, Shubham Sahai Srivastava, Sandeep K. Shukla. Detecting Insider Attacks on Databases using Blockchains. In proceedings of Workshop on Blockchain Technologies and its Applications, ISRDC, IIT Bombay, 2017.

PDF

Recent Posts

May 3, 2019 5 min read

WAPS: Weighted and Projected Sampling

This blogpost talks about our tool WAPS. Specifically, we will talk about how we are able to utilize the idea of sampling using knowledge compilations (d-DNNFs) from our previous work (KUS) and generalize it in order to achieve weighted and projected sampling. This work was jointly performed by Rahul and Shubham in the mentorship of Subhajit and Kuldeep. You can read the paper here and get the tool here. You can read the previous blog that describes uniform sampling using knowledge compilations, though it is not absolutely necessary for this post.

Contact

grahul@cse.iitk.ac.in