Indian Symposium on Machine Learning (IndoML)

 

December 16 – 18, 2021 | Virtual

The Second Indian Symposium on Machine Learning (IndoML) will be hosted by the Indian Institute of Technology Gandhinagar (IITGN) between 16-18 December 2021. The symposium aims to be a forum to discuss state-of-the-art ML research through invited talks from leading experts within India and abroad. IndoML fosters mentoring of Indian Ph.D./Master students to network with their peers, seek expert guidance and develop early-stage collaborations.

IndoML aims to provide an opportunity for the faculty to engage with leading research groups in the country and conduct high-quality research leading to competitive publications. It will also provide a platform for industrial partners, including startups, working in ML-related areas to showcase their products and receive reviews/feedback as well as setup potential collaborations.

Theme

The theme of IndoML 2021 is “AI for Data and Data for AI

Organizers

Volunteers

  • IIT Kharagpur:

    Abhilash Nandy, Arijit Nag, Souvic Chakraborty, Gunjan Balde

  • Carnegie Mellon University: 

     Pratik Joshi

 

Speakers

Abhijnan Chakraborty

Abhijnan Chakraborty

Indian Institute of Technology Delhi, India

Chris Potts

Chris Potts

Stanford University, California

Dipanjan Das

Dipanjan Das

Google AI, New York

Dragomir R. Radev

Dragomir R. Radev

Yale University, US

Ido Dagan

Ido Dagan

Bar-Ilan University, Israel

Iryna Gurevych

Iryna Gurevych

Technische Universität Darmstadt,Germany

Marinka Zitnik

Marinka Zitnik

Harvard University, US

Michael Bronstein

Michael Bronstein

Imperial College London, London

Mohit Bansal

Mohit Bansal

UNC Chapel Hill, USA

Monojit Choudhury

Monojit Choudhury

Microsoft Research Lab, India

Raymond J. Mooney

Raymond J. Mooney

University of Texas at Austin, US

Robert Hoehndorf

Robert Hoehndorf

King Abdullah University of Science and Technology, Saudi Arabia

Ronita Bardhan

Ronita Bardhan

University of Cambridge, UK

Sameer Singh

Sameer Singh

University of California, Irvine

Sharad Goel

Sharad Goel

Harvard University, US

Subimal Ghosh

Subimal Ghosh

IITB, India

Tavpritesh Sethi

Tavpritesh Sethi

IIIT Delhi, India

Thomas Vandal

Thomas Vandal

NASA Earth eXchange, USA

Tim Baldwin

Tim Baldwin

University of Melbourne, Australia

Udit Bhatia

Udit Bhatia

IIT Gandhinagar, India

Schedule 

Mentioned time is Indian Standard Time (GMT+5 hr 30 mins)

Datathon

 

Datathon is a part of the workshop named IndoML organized by a team consisting of academics and researchers from IIT Gandhinagar, IIT Kharagpur, University of Warwick, Google, and Microsoft Research with a theme of “Data for AI and AI for Data”. The broad aim of this Datathon is to invite participants to gain experience in solving real world data science/ML problems posed by experts in industry and academia.

As a part of Datathon-2021 following are the set of competitions:

1. GLUECoS-NLI-Knowledge: This is a Conversational Code-switched Natural Language Inference dataset, in English and Hindi (written in Roman script). Here, the premise is a multi-turn dialog and hypothesis is a sentence. The traditional NLI task is to determine whether the hypothesis is entailed by or contradicts with the premise (there are only 2 labels: entailment or contradiction unlike the popular NLI task). For this competition, the task is: given a premise-hypothesis pair (and the entailment label), the goal is to determine whether inferring the entailment label would require some sort of external knowledge or not. This problem is posed by Microsoft.

2. IndoRE: IndoRE is a relation extraction task for three low resource Indian Languages (Bengali, Telugu and Hindi) and this task is posed by IIT Kharagpur.

3. E-Manual: This is a question-answering task. Here the dataset is a set of manuals of electronic instruments, and the goal here is to extract an answer and/or the section from the manual where an answer is present for a given question. This problem statement is posed by IIT Kharagpur.

4. Multilingual Abusive Comment Identification: Multilingual Abusive Comment Identification Challenge is a challenge towards combating abusive comments (in multiple Indian regional languages) on Moj, which is one of India’s largest short-video apps. This challenge is posed by Sharechat.

5. COVID-19 India Dataset: Flex your brains on one of the most comprehensive sources of COVID data from India, extracted automatically from daily health bulletins published by major Indian states. This challenge is posted by IBM Research. STARTS SOON.

Participants will have an opportunity to win prizes worth up to 4.25 Lacs generously sponsored by ACM India and other companies including Microsoft Research India, Google and IBM Research!!!

Sponsors