Centre of Excellence in Artificial Intelligence IIT Kharagpur

05/01/2022

27/07/2021

We are looking for 1/2 student(s) from IIT Kharagpur (any branch) for a project sponsored by DST to study the spread of Covid-19 in university campuses.
Required experience: Web development, especially Django and Reactjs, Python API design and also familiarity with AWS
Duration of work: 1 month
Stipend: INR 10,000
Interested students with the aforementioned skills may drop a mail to [email protected]

10/03/2021

The 6th week of TWin AI ML will feature the second part of the talk by Prof. Plaban Kumar Bhowmik on "Machine Learning on Graph Data". The first part of the talk was held on last wednesday. The speaker is a joint faculty member of Centre of Excellence in AI.
MS Teams channel code: o7ac2a2
Meeting Link: https://teams.microsoft.com/l/meetup-join/19%3aa462121f91e64e9ab4a59b8c2b91bfe5%40thread.tacv2/1612897430573?context=%7b%22Tid%22%3a%2271dbb522-5704-4537-9f25-6ad2dcd4278d%22%2c%22Oid%22%3a%222de4572d-50db-42b4-ad68-0dce55110ec2%22%7d

01/03/2021

The 5th week of TWin AI ML will feature two talks by 1) Prof. Plaban Kumar Bhowmik on "Machine Learning on Graph Data" and 2) Prof. Arnab Sarkar on "Brownout Based Blackout Avoidance in Smart Microgrids". Both the speakers are joint faculty members of Centre of Excellence in AI.
MS Teams channel code: o7ac2a2
Meeting Link: https://teams.microsoft.com/l/meetup-join/19%3aa462121f91e64e9ab4a59b8c2b91bfe5%40thread.tacv2/1612897430573?context=%7b%22Tid%22%3a%2271dbb522-5704-4537-9f25-6ad2dcd4278d%22%2c%22Oid%22%3a%222de4572d-50db-42b4-ad68-0dce55110ec2%22%7d

23/02/2021

The 4th week of TWin AI ML will feature a talk by Dr. Rajendra Machavaram of Department of Agriculture and Food Engineering.

MS Teams Link: https://teams.microsoft.com/l/team/19%3aa462121f91e64e9ab4a59b8c2b91bfe5%40thread.tacv2/conversations?groupId=e5defe53-8a2b-4afd-aade-bd26cb9398dc&tenantId=71dbb522-5704-4537-9f25-6ad2dcd4278d
The link to the Microsoft Teams meeting:
https://teams.microsoft.com/l/meetup-join/19%3aa462121f91e64e9ab4a59b8c2b91bfe5%40thread.tacv2/1612897430573?context=%7b%22Tid%22%3a%2271dbb522-5704-4537-9f25-6ad2dcd4278d%22%2c%22Oid%22%3a%222de4572d-50db-42b4-ad68-0dce55110ec2%22%7d

17/02/2021

The 3rd session of TWin AI ML will feature a talk by Prof S K Pal of Centre of Excellence in Advanced Manufacturing Technologies.
MS Teams Link: The link to the Microsoft Teams meeting:
The link to the Microsoft Teams meeting:
https://teams.microsoft.com/l/meetup-join/19%3aa462121f91e64e9ab4a59b8c2b91bfe5%40thread.tacv2/1612897430573?context=%7b%22Tid%22%3a%2271dbb522-5704-4537-9f25-6ad2dcd4278d%22%2c%22Oid%22%3a%222de4572d-50db-42b4-ad68-0dce55110ec2%22%7d

16/02/2021

Congratulations to Nilanjan Mukherjee, a PhD student in Centre of Excellence in Artificial Intelligence for securing the First position on the theme Quantum Computing and Artificial Intelligence for his presentation of his work on "A Robust Fuel Optimization Strategy for Hybrid Electric Vehicles: A Deep Reinforcement Learning Based Continuous Time Design Approach" in the Young Scientists Conference in IISF 2020.

10/02/2021

TwinAIML session will feature talks by Dr Debdoot Sheet and Dr Adway Mitra
Today at 7 pm
Two talks from Centre of Excellence in AI

1. Deep Digital Twins: Fast Simulators of Physical Processes using Deep Learning by Dr. Debdoot Sheet
This is where I would be presenting our research in making fast simulators of medical images like ultrasound, CT, MRI, etc. using Deep Learning, and how we have created physics engrained learning models. The overarching objective is to convey the ability to build better and computationally faster digital twins, through a data driven approach with embedded physics constraints.

2. Spatio-temporal Graphical Models for Earth Science by Dr. Adway Mitra
I will be talking about how probabilistic graphical models can be used to answer questions related to spatial distribution of geophysical variables such as rainfall, relationships between different geophysical variables, regionalization of a landmass based on geophysical variables and so on. I will also briefly mention how Deep Learning may be used to simulate geophysical data.