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Design & fabrication of a cold plate using friction stir channeling for thermal management of electronic systems & battery packs

Design and Development of low-cost leather ironing machine (A Miniature model) for leather artisans

Design, growth & fabrication of III-Nitride based single photon source operating at higher (200k & above) temperature

Development & application of multiscale modeling for complex biological systems & drug design

SAFAR: Safe and Accessible Future with AI on Roads

The aim of this project is to develop a dashboard for visualizing traffic safety scenarios in a target region (eg. Kolkata city), and assess the impact of potential localized interventions to improve the safety scenario. The project is built around t

AI-enabled NDT software for auto-evaluation of industrial ToFD data

The objective is to develop an Artificial Intelligence based model for automatic detection of location and size of defects in a welded component from ToFD data, and a user-friendly software for visualization of results in industrial practice.

Optimal Use of Friction Modifiers Through Machine Learning for Improved Safety and Reduced Running Costs In Metro Trains

Wheel wear, contact noise, rail-climb derailment, and braking distance are directly affected by rail-wheel friction characteristics. More specifically, wheel wear, derailment tendency, and noise can be significantly reduced if friction can be moderat

MARL-based Beam Formation in IRS-Assisted Two-way Ultra Massive MIMO Communications for 6G Standardization

This project focuses on developing an ultra-massive MIMO IRS-assisted two-way communication system in the mmWave spectrum. It integrates Multi-Agent Reinforcement Learning (MARL) for real-time, collaborative channel estimation, improving system perfo

Automated Design and 3D Printing-based Fabrication of Cost-effective Patient- specific Cranioplasty Implants

The project aims to leverage AI-based techniques to automatically design patient-specific cranioplasty implant from CT data, and fabricate the implants using a cost-effective 3D printing-based process. Both public and private datasets will be used fo

Machine-intelligent MoS2 functionalized paper-based sensing platform for quantitative estimation of uric acid and ascorbic acid in human serum samples

The current project proposes to develop a paper based electrochemical sensor for simultaneous detection of ascorbic acid and uric acid. The MoS2 based paper sensor will non-enzymatically detect the targeted biomolecules. This detection will rule out