Indian Symposium on Machine Learning (IndoML)

December 16 – 18, 2020 | Virtual

The first Indian Symposium on Machine Learning (IndoML) will be hosted by the Indian Institute of Technology Gandhinagar (IITGN) between 16-18 December 2020. 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 2020 is “AI for Science and Science for AI“

Organizers

Speakers

AADITESHWAR SETH

Indian Institute of Technology Delhi

ABIR DE

Indian Institute of Technology Bombay

ANKIT AGRAWAL

Northwestern University

ANUJ KARPATNE

Virginia Tech

Ard Louis

University of Oxford

Auroop Ganguly

Northeastern University

Brooks Paige

University College London AI Centre

Chin-Yew Lin

Microsoft Research Asia

J. Nathan Kutz

University of Washington

José Miguel Hernández-Lobato

University of Cambridge

JOYOJEET PAL

Microsoft Research India

KRISTOF SCHÜTT

TU Berlin

LINQING WEN

University of Western Australia

MAX WELLING

University of Amsterdam, and Qualcomm

Milind Tambe

Harvard University, and Google Research India

Mona Sloane

Institute for Public Knowledge, NYU

Ravi Kumar

Google

SATADEEP BHATTACHARJEE

Indo Korea Science and Technolgy Center (IKST)

Shirley Ho

Flatiron Institute, and Carnegie Mellon University

Srinivas (Sai) Ravela

MIT, and Galaxy.AI

SUDHEENDRA HANGAL

Ashoka University

Schedule

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

Time
(IST: GMT+5:30)

Talk

Speaker

Day 1 Session I: Chemical and Atmospheric Sciences

Session Chair: Mayank Singh (IITGn)

08:20 – 08:30

Inaugural talk by Mayank Singh

08:30 – 09:15

Auroop Ganguly: Is Artificial Intelligence the new electricity that will transform Earth Systems Sciences and Engineering?

09:20 – 10:05

Srinivas Ravela: Stochastic Physics designs of Informative Hybrid Learning Machines for Earth, Planet, Climate and Life

10:10 – 10:55

Ankit Agrawal: AI and High Performance Data Mining – Illustrative Applications in Materials Science

11:00 – 11:20

Satadeep Bhattacharjee: Modeling Functional Materials using Data Driven Methods

Day 1 Session II: Physical and Mathematical Sciences

Session Chair: Udit Bhatia (IITGn)

16:00 – 16:45

Max Welling: Lessons from Physics for Deep Learning

16:50 – 17:35

Ard Louis: A Function Based Picture Explains Why Neural Networks Generalise So Well In The Overparameterized Regime

17:40 – 18:25

Chin-Yew Lin: Towards Automatic Math Word Problem Solving

18:30 – 19:15

Linqing Wen: Potential and Challenges of Machine Learning for Gravitational Wave Discovery

 

Time (IST: GMT+5:30)

Talk

Speaker

Day 2 Session I: Social Sciences

Session Chair: Animesh Mukherjee (IITKGP)

09:00 – 09:45

Mona Sloane: AI, Society, and Inequality: Why We Need to Enhance Engineers’ Ability to Understand Social Impact

09:50 – 10:35

Joyojeet Pal: Social Media Misinformation in India

10:40 – 11:25

Ravi Kumar: Learning-Augmented Online Learning

Day 2 Session II: Chemical and Atmospheric Sciences

Session Chair: Niloy Ganguly (IITKGP)

16:00 – 16:45

Brooks Paige: Bayesian Inference and Meta-learning for Molecular Property Prediction with Graph Neural Networks

16:50 – 17:35

Jose Miguel Hernandez-Lobato: Advances in Molecular Design with Deep Generative Models

17:40 – 18:25

Kristof Schutt: Unifying Machine Learning and Quantum Chemistry with Deep Neural Networks

18:30 – 18:50

Abir De: NeVAE – A Deep Generative Model for Molecular Graphs

 

Time (IST: GMT+5:30)

Talk

Speaker

Day 3 Session I: Physical and Mathematical Sciences

Session Chair: Anirban Dasgupta (IITGn)

08:15 – 09:00

Shirley Ho: Discovering Symbolic Models in Physical Systems using Deep Learning

09:00 – 09:45

Anuj Karpatne: Science-guided Machine Learning – Advances in An Emerging Paradigm Combining Scientific Knowledge with Machine Learning

09:50 – 10:35

J. Nathan Kutz: Machine Learning for Science: Data-Driven Discovery Methods for Governing Equations, Coordinates and Sensors

Day 3 Session II: Social Sciences

Session Chair: Mainack Mondal (IITKGP)

16:00 – 16:45

Aaditeshwar Seth: Use of AI/ML to Scale Voice-based Participatory Media Forums

16:50 – 17:35

Sudheendra Hangal: Challenging problems in Indian Political Data

17:40 – 18:25

Milind Tambe: Advancing AI for Social Impact – Learning and Planning in the Data-to-Deployment Pipeline

 

Registration

Registration is free of cost. The final registration confirmation would be based on the discretion of the organizers.

Sponsor

This event is being sponsored by a grant from the AI Journal.