The Indian Institute of Technology Kanpur (IITK) and NYU Tandon School of Engineering have announced a new list of collaborative research projects, the first such initiatives under the broad collaboration that NYU and IIT Kanpur formed last year. The seven projects, jointly led by researchers from each institution, aim to advance innovations across vital scientific fields, including cybersecurity, biotechnology, artificial intelligence, robotics, and wireless communications.
NYU and IIT Kanpur signed their initial partnership agreement in September 2023, following U.S. President Joe Biden’s visit to the G20 Summit in New Delhi, India, and the Association of American Universities’ push for further similar collaborations. In addition to collaborative research projects, they plan to enhance doctoral exchange opportunities and share teaching and research strategies.
Prof. Bushra Ateeq, Dean of International Relations at IIT Kanpur, expressed his thoughts on the collaboration:
International academic partnership improves the diversity of ideas, creates synergies, and allows collective efforts to address scientific challenges. Our cooperation with NYU would foster innovation and yield solutions that will enhance lives globally.
The IIT Kanpur partnership follows NYU’s 2022 launch of a formal alliance with KAIST (Korea Advanced Institute of Science and Technology), leading to joint academic research projects involving faculty from both institutions. The Memorandum of Understanding (MOU) with IIT Kanpur exemplifies NYU’s global reach and desire to find and create innovation regardless of borders.
Both institutions provide initial research funding, with further support from NYU Tandon’s Center for Advanced Technology in Telecommunications and the NYU Center for Cybersecurity.
Linda Ng Boyle, NYU Tandon’s Vice Dean for Research, added:
Forging academic ties across borders is crucial for driving scientific breakthroughs and is a central principle of how we pursue research. Through our collaboration with IIT Kanpur, we strive to deliver technological innovations that serve people worldwide, making our planet safer, cleaner, and healthier.
The seven NYU Tandon /IIT Kanpur research projects are:
- Engineering Multivalent Assembled Protein to Mimic Hypoxia-Inducible Factor
Researchers: Jin Kim Montclare, NYU Tandon; R. Sankararamakrishnan, IIT Kanpur
The team is developing synthetic proteins to dismantle harmful protein complexes associated with cancer-related diseases. Using computer models, the scientists design optimal shapes for these multi-armed structures, which are created and tested in the lab. The initial focus is on targeting protein complexes that promote tumour growth to advance cancer treatment.
- Enhancing Quadruped Robot Motion: A Reinforcement Learning Approach for Extreme Agility, Stability, and Safety
Researchers: Farshad Khorrami, NYU Tandon; Shakti S. Gupta, IIT Kanpur
This project uses advanced machine-learning techniques to improve four-legged robots’ agility, stability, and safety. By training robots through simulations and ensuring their movements are safe and predictable, the team hopes to enhance their ability to navigate the rough and unpredictable terrain. This work could significantly expand the capabilities of legged robots in real-world environments.
- High-Resolution Neural Interface SoC with Meta-Structure-Enhanced Wireless Power Transmission
Researchers: Hamed Rahmani, NYU Tandon; Raghvendra Chaudhary, IIT Kanpur
The team is developing a tiny, wireless system-on-chip for high-resolution brain monitoring. This device integrates innovative electromagnetic metastructures to improve wireless power delivery to a small implant. By co-designing the power, recording, and communication systems, researchers aim to dramatically increase the capabilities of neural interfaces, potentially advancing neuroscience and applications like brain-computer interfaces.
- Leveraging Modern Vision-Language Models for Traffic Camera Scene Understanding
Researchers: Chinmay Hegde, NYU Tandon; Pranamesh Chakraborty, IIT Kanpur
This project uses advanced vision-language models to enhance understanding of traffic scenes captured by urban video cameras. The team’s approach aims to reduce the costs and complexity of training computer vision models from scratch. The collaboration involves experts in transportation and AI, aiming to develop flexible and cost-effective systems for tasks like vehicle detection and traffic incident identification, particularly in Indian traffic conditions.
- EMI Shielded and FOD Enabled Smart Wireless EV Charging Station Powered by Renewable Energy
Researchers: Francisco De Leon, Dariusz Czarkowski, NYU Tandon; Suvendu Samanta, Gururaj Mirle Vishwanath, IIT Kanpur
The researchers are creating an intelligent, safe, and efficient wireless charging system for electric vehicles (EVs) that integrates renewable energy sources like solar power. This system will feature advanced foreign object detection, electromagnetic shielding, and the ability to manage coil misalignment. The project aims to develop a prototype and validate the system’s performance, with the potential for commercialization and enhancing renewable energy utilization in EV charging.
- Unconventional Physically Unclonable Functions for Micro-fluidics and Supply Chain Fingerprinting
Researchers: Ramesh Karri, NYU Tandon; Navajit Singh Baban, NYU Abu Dhabi; Urbi Chatterjee, IIT Kanpur
This research aims to develop unique security features called physically unclonable functions (PUFs) for authenticating microfluidic biochips and supply chain products. Through robust, machine learning-enhanced PUF designs, the goal is to improve security and authentication in medical diagnostics and supply chain management.
- Programmable Cryptographic Processing Units to Enable Secure, Private, and Quantum-Proof Computing
Researchers: Brandon Reagen, NYU Tandon; Angshuman Karmakar, IIT Kanpur
This project focuses on developing advanced cryptographic techniques to ensure secure and private computation, even in the face of future quantum computing threats. The researchers will design efficient post-quantum cryptography and homomorphic encryption schemes optimized for various hardware platforms. The project seeks to make privacy-preserving technologies practical and efficient, with secure authentication and machine learning applications, while fostering further research through open-source initiatives.
