Field of Study India: Computer Science

Debapriya Basu Roy

Dr. Debapriya Basu Roy received his PhD degree from IIT Kharagpur and was a post-doctoral fellow with the Technical University of Munich. He is currently an Assistant Professor with the Department of Computer Science and Engineering, Indian Institute of Technology Kanpur. His research interests include applied cryptography, hardware security, post-quantum cryptography, side channel analysis and digital VLSI. Some of his notable contributions in the domain of hardware security are efficient implementation of elliptic curve cryptography, side-channel leakage quantification and implementation of post-quantum cryptography on FPGAs.

In the Fulbright-Nehru Academic and Professional Excellence project, Dr. Basu Roy is aiming to implement and perform side channel analysis of a post-quantum secure lattice-based cryptographic algorithm. Due to the advancement of quantum computing, the security guarantees of public key algorithms have come under serious threat. In this project, Dr. Basu Roy’s aim is to develop a unified hardware implementation of three lattice-based cryptographic algorithms and perform a holistic side-channel analysis of the developed architecture.

Susmita Sur-Kolay

Dr. Susmita Sur-Kolay is a Visting Professor of Computer Science in Ashoka University. Till 2024, she was a Professor in the Advanced Computing and Microelectronics Unit of the Indian Statistical Institute, Kolkata. Earlier, she was a Reader in the Department of Computer Science and Engineering of Jadavpur University, a post-doctoral fellow at University of Nebraska-Lincoln, and a Research Assistant at the Laboratory for Computer Science in Massachusetts Institute of Technology, USA.

Dr Sur-Kolay’s research contributions are in algorithmic design automation for electronic and quantum circuits, fault modeling and testing, hardware security, and graph algorithms. She has co-authored several papers in international journals and refereed conference proceedings, three book chapters, and co-edited three books.

She has served on the committees of international conferences and on the editorial board of major journals. She was a Distinguished Visitor of IEEE Computer Society (India), and is a Fellow of Indian National Science Academy and Indian National Academy of Engineering. She has received the President of India Gold Medal and Distinguished Alumnus Award at IIT Kharagpur, Women in Technology Leadership Award from VLSI Society of India and International Excellence Fellowship at Karlsruhe Institute of Technology (2024).

During her tenure of the Fulbright-Nehru Academic Excellence Fellowship at UC San Diego, Dr. Sur-Kolay is aiming to design efficient methods for the layout phase of mapping quantum algorithms to the target quantum hardware with error correction capabilities and to teach related courses.

Tarun Sharma

Mr. Tarun Sharma is a PhD candidate at the Department of Electronics and Communication Engineering, Indraprastha Institute of Information Technology, Delhi. His doctoral research focuses on improving the performance and sustainably of heterogeneous CPU-GPU based multicore architecture. He also focuses on customising the open-source RISC-V architecture for various applications.

Tarun holds a bachelor’s degree in electrical and electronics engineering from Guru Tegh Bahadur Institute of Technology, Delhi and a master’s degree in microelectronics from Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus.

As a Fulbright-Nehru Doctoral Research fellow, Tarun is aiming to enhance transformer inference using Wireless Network-On-Chip (WNoC) and Machine Learning-based DRAM prefetcher. The proposed framework is expected to improve transformer inference while reducing the power required for off-chip DRAM access, while not requiring any changes in the software and is independent of any CPU, GPU, or accelerator hardware.

Lokeswari Malepati

Ms. Lokeswari is a direct PhD candidate at the Department of Civil Engineering, Indian Institute of Technology Hyderabad, Telangana. Her research focusses on developing computer vision algorithms suitable for usage in combination with drones for assessment of structures. She leverages multi-modal imaging and deep learning models for quantification of surface and subsurface damages in infrastructure.

Lokeswari holds a bachelor’s degree in civil engineering from National Institute of Technology, Tiruchirappalli. She has two years of experience in L&T’s research and testing laboratory where she worked on evaluating the suitability of lightweight concrete for structural applications and developing alternative connections for precast wall panels.

As a Fulbright-Nehru Doctoral Research fellow at University of Houston, Texas, Lokeswari is implementing the developed algorithms in the field for bridge inspections using drones. This research aims to evaluate the performance of these algorithms under practical scenarios and propose modifications to their architecture and training strategies. This work contributes to advancing unmanned aerial vehicle-based technologies for faster and more efficient structural assessments. In her free time, Lokeswari enjoys playing volleyball and table tennis.

Ashish Tiwari

Ashish Tiwari is currently a Ph.D. candidate in electrical engineering at IIT Gandhinagar. He obtained his MTech in electrical engineering from IIT Gandhinagar in 2020. He is the recipient of the Prime Minister’s Research Fellowship (PMRF) 2020-2024. His research interest lies at the intersection of computer vision, computer graphics, and deep learning with a primary focus on inferring the 3D world from image(s) through photometric methods such as photometric stereo, Shape from Polarization (SfP), and photo-polarimetric stereo. He was awarded the Qualcomm Innovation Fellowship (QIF) 2023-2024 for his project proposal, “Photometric Stereo for Refractive Objects.” He was a part of the core organizing team of ICVGIP 2022, held at IIT Gandhinagar. He was also a part of the Google Research Week 2023.

As a Fulbright-Nehru Doctoral Research fellow at Rice University, Houston, TX, Ashish is investigating a scene’s geometry, material, and lighting through a sparse set of images captured through hand-held acquisition devices such as smartphones. Ashish enjoys teaching and has delivered plenty of invited talks on his research on photometric stereo. He likes singing, sketching, playing outdoor sports, especially cricket, and long-hour endurance runs. He also enjoys interacting with people from different regions and cultures and involves himself in community services.

Rishiraj Adhikary

Mr. Rishiraj Adhikary is a Ph.D. student at the Computer Science Department, Indian Institute of Technology (IIT) Gandhinagar, Gujarat. His research interest is in human-computer interaction, ubiquitous computing and sensor-enabled embedded systems that can impact healthcare delivery or pave the way towards making healthcare more accessible. His current research focuses on retrofitting consumer-grade masks with sensors to detect lung health. His prior work has also studied the perception of people around air pollution to aid in risk communication.

During his Fulbright-Nehru Fellowship, he will study how contexts like human activity can be leveraged to implement opportunistic sensing techniques in smart masks. Successful research on context sensing will pave the way to preserve privacy and reduce the energy consumption of a smart face mask.

Mr. Adhikary received his B.Tech. (Electronics and Communication Engineering) from Gauhati University, Assam, where his capstone project was recognised as the best project. He has successfully conducted events targeting school children in the past where he has demonstrated prototyping tools to help students understand the basics of electronics. He also takes a keen interest in teaching undergraduate and school students.

Harish Sankar Aghila

Harish S A is a Ph.D. candidate and teaching assistant at the Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad. The broader domains encompassing his research interests include networks, systems, and security. His current research explores the security implications of in-network systems that leverage cutting-edge technologies like software-defined networks and programmable data planes.

Harish is a recipient of the prestigious Prime Minister’s Research Fellowship (PMRF) awarded by the Ministry of Education, Government of India. As a part of his doctoral research, he actively engaged in a security project alongside ASEAN countries and participated in their student exchange program. He published research papers and presented his work at reputed international venues. Additionally, he has received the notable SIGCOMM travel grant award, among many others.

He earned a bachelor’s degree in computer science and engineering from the National Institute of Technology Puducherry, during which time he interned with the UMR TETIS Joint Research Unit in Montpellier, France. He holds a master’s degree in computer engineering (cyber security) from the National Institute of Technology Kurukshetra.

As a Fulbright-Nehru Doctoral Research fellow at the University of Texas, Austin, TX, Harish is examining to secure data-driven, in-network systems built on high-speed programmable data planes against adversarial inputs. His vision is to bolster the resilience of next-generation computer networks against security threats. Harish teaches undergraduate students about network security. He enjoys road trips and chess.

Shruti Singh

Ms. Shruti Singh is a doctoral candidate at the Computer Science and Engineering department, Indian Institute of Technology Gandhinagar, Gujarat. Her research interests lie in the field of natural language processing, specifically in learning representations of scientific articles. Her research goal is to develop tools that assist researchers at various stages of the research cycle and democratize the entry of marginalized communities into research.

Ms. Singh received her bachelor’s in information and communication technology with a minor in computational sciences from Dhirubhai Ambani Institute of Information and Communication Technology, Gujarat. Post her bachelor’s, she worked as a research engineer at Raxter and a product engineer at Sprinklr.

During her Fulbright-Nehru Doctoral Research fellowship, Ms. Singh is working with Prof. Arman Cohan at Yale University on learning aspect-based representations for scientific articles. Aspect-based representations of research articles will enable fine-grained scholarly search, increase the productivity of researchers, and expedite the process of knowledge discovery.

Debanjan Konar

Dr. Debanjan Konar earned a Bachelor of Engineering in Computer Science and Engineering (CSE) from the University of Burdwan , in 2010, an MTech in CSE from the National Institute of Technical Teachers’ Training and Research (NITTTR), Kolkata , in 2012, and a PhD from the Indian Institute of Technology Delhi in New Delhi , in 2021. He is currently working as a postdoctoral researcher at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Germany. Prior to this, Dr. Konar served as an Assistant Professor at Sikkim Manipal Institute of Technology, Sikkim , and SRM University-AP, Andhra Pradesh . His research interests include quantum machine learning (QML), hybrid classical-quantum neural networks, deep learning, and computer vision. He has authored several papers in prestigious computer science journals, conference proceedings, book chapters, and internationally renowned books. Dr. Konar received a National Scholarship in 2001 and a GATE Postgraduate Fellowship in 2010. He is an IEEE senior member and an ACM member. He also serves as an editor and a reviewer for several esteemed journals and international conferences.

Recently, Quantum Computing (QC) has been leveraged for machine learning with the expectation that the uncertainty inherent in QC may be used to great advantage in stochastic-based modelling , spurring new research on Noisy Intermediate-Scale Quantum (NISQ) devices. To exploit the advantages of stochastic-based modelling in QML research, Dr. Konar has proposed Spiking Quantum Neural Networks using hybrid classical-quantum algorithms with the merits of superposition states and amplitude encoding. Within this Fulbright-Nehru Postdoctoral Research Fellow ship, the proposed models will be extensively validated on various computer vision applications, including disguised facial recognition using the PennyLane Quantum Simulator with limited quantum hardware and supercomputing resources available at Purdue University, USA.

Vineeth N Balasubramanian

Dr. Vineeth N Balasubramanian is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Hyderabad (IIT-H), and currently serves as the Head of the Department of Artificial Intelligence at IIT-H. His research interests include deep learning, machine learning, and computer vision. His research has resulted in many publications in several top conferences and journals including ICML, CVPR, NeurIPS, ICCV, AAAI, TPAMI, etc. His Ph.D. dissertation at Arizona State University on the Conformal Predictions framework was nominated for the Outstanding Ph.D. Dissertation at the Department of Computer Science. His recent awards include: Best Paper Awards at CODS-COMAD 2022, CVPR 2021 workshops on Causality in Vision and Adversarial Machine Learning; Teaching Excellence Awards at IIT-H in 2017 and 2021; Google Research Scholar Award (earlier known as Google Research Faculty award) in 2020; Outstanding Reviewer Awards at ICLR 2021, CVPR 2019, ECCV 2020. For more details, please see https://iith.ac.in/~vineethnb/.

During his Fulbright-Nehru Research Fellowship, Dr. Balasubramanian aims to work towards developing trustworthy machine learning models that are implicitly imbued with causal reasoning capabilities. In particular, he plans to understand and develop methods for causal generative mechanisms in real-world data, and bring together perspectives of causality and robustness into explanations of deep neural network models.