Akhil Arora



May, 2018:

Our SIGMOD 2017 paper has won the SIGMOD most reproducible paper award!!

Mar, 2018: Paper alert!

Our work on approximate k nearest neighbor search in high-dimensional spaces has been accepted in VLDB 2018. Congrats Sakshi and Piyush!

Oct, 2017: Workshop Proposal Accepted!

Co-chairing the first edition of the GRADES-NDA workshop in conjunction with SIGMOD 2018. Don't miss the chance to submit your relevant research work!

Sep, 2017:

Serving on the program committee of DASFAA 2018

Jul, 2017:

Here is our report systematically refuting and responding to the refutations made by Lu et al. on our SIGMOD 2017 paper on "Debunking the Myths of Influence Maximization".

May, 2017:

Serving on the program committee of SIGMOD 2018 (Demonstrations Track).

May, 2017:

Attending SIGMOD 2017 from 14th May-19th May.

12th May, 2017:

Giving a talk on "Influence Maximization on Social Networks: The State of the Art and the Gaps that Remain" at the University of Michigan, Ann Arbor.

March, 2017:

Attending COMAD/CODS 2017 from 8th-10th March. Invited to present our SIGMOD 2016 paper: "Holistic Influence Maximization" and VLDB 2016 Demo: "GARUDA" in the premier papers track!!

Jan, 2017:

Giving a talk on Debunking the Myths of Influence Maximization at NEDB Day, 2017.

Sep, 2016: Paper accepted in SIGMOD!

Are you aware of the subtleties in the area of Influence Maximization? We bet not! Debunking the Myths of Influence Maximization in our new sexy SIGMOD 2017 paper.

[I moved to EPFL in September 2018, so this website isn't updated any longer. For updates and news, please refer to my new website.]

Hi, I am Akhil Arora, a data management researcher by profession. My research interests include large scale data-mining: graph mining, social-network analysis; and databases: indexing & querying large graphs, text and high dimensional databases. The tag-cloud of my paper abstracts provides an accurate representation of my research interests.

Previously, I was associated with the Big Data Labs at American Express and Text & Graph Analytics Group at Xerox Research respectively as a Research Scientist for close to four years. In both the roles, I worked as a leading contributor in devising novel scalable algorithms to solve a gamut of complex real-world problems in the area of databases, data mining and machine learning. I have also spent an year at Intel Corporation, Bangalore.

I graduated from the Computer Science department of Indian Institute of Technology (IIT) Kanpur, India in June, 2013. During my masters, I worked on statistically significant subgraph mining in the SIGDATA group under the supervision of Prof. Arnab Bhattacharya.