Computer Science Archives - Page 2 of 2

Nanditha Rao

Dr. Nanditha Rao is Assistant Professor at the International Institute of Information Technology (IIIT), Bengaluru in the VLSI Systems group. She received her Ph.D. in electrical engineering from IIT Bombay in 2017. Her research interests include FPGA based acceleration for machine learning, RISC-V and radiation-hardened designs. She has received the SERB Core Research Grant 2018, MITACS Globalink Research Award 2018 and SERB SUPRA research grant 2022.

Dr. Rao believes in encouraging students in technology and leadership roles. She took up administrative roles such as General Secretary of a women’s hostel in IIT Bombay for which she was awarded the Institute Organizational Citation. She is currently the associate warden of women’s hostel in IIIT Bangalore. She worked as a hardware design engineer at Intel for five years prior to her Ph.D. Her work at Intel involved signal integrity simulations of PCIe, LVDS, DisplayPort and HDMI interfaces. She received 13 Intel Spontaneous Recognition Awards and one Intel Divisional Recognition Award.

During her Fulbright-Nehru Academic and Professional Excellence fellowship, Dr. Rao is working on improving the performance of hardware accelerators for convolutional neural networks (CNN). CNNs are most commonly used today in computer vision, and image and video processing. The CNN accelerator implemented using field-programmable gate arrays (FPGA) enables significant performance improvement and power efficiency compared to GPU implementations. However, to improve the performance on the FPGA further, it is important to explore the appropriate mapping of the accelerator architecture onto optimal FPGA resources, which is what Dr. Rao is focusing on during this fellowship.

Sarvesh Pandey

Dr. Sarvesh Pandey is an assistant professor of computer science at Banaras Hindu University since November 2020. At BHU, he has been actively involved in teaching, research, and administration activities. Dr. Pandey obtained his MTech and Ph.D. degrees from the Computer Science and Engineering Department of Madan Mohan Malaviya University of Technology, Gorakhpur. His broad research areas include blockchains, cloud computing, and database systems. In 2014, he secured 33rd rank in the CSIR-NET examination for engineering sciences. Under the CSIR scheme, he worked as a Junior Research Fellow (JRF) and subsequently as a Senior Research Fellow (SRF) during his Ph.D. He has also qualified for the GATE entrance examination in computer science and information technology.

As a Fulbright-Nehru Postdoctoral Research fellow, Dr. Pandey will explore two crucial research directions: efficient data management utilizing blockchain technology, and blockchain application in crowdsourcing. As the current decentralized data processing and retrieval landscape is transitioning, his plan involves optimizing blockchain performance, specifically addressing query retrieval efficiency and facilitating rich queries. Additionally, he aims to incorporate access control mechanisms within the blockchain framework. The research outcomes will be seamlessly integrated into existing crowdsourcing applications, capitalizing on the strengths of both domains

Saptarshi Saha

Saptarshi Saha is a Ph.D. candidate at the Indian Statistical Institute, Kolkata. His doctoral research is focused on integrating causality into deep learning frameworks to enhance their utility. Beyond his immediate thesis goals, Saptarshi envisions a broader research trajectory aimed at utilizing deep learning for a deeper understanding of cause-and-effect relationships. His aim is to address various challenges such as improving the robustness, explainability, and interpretability of models, addressing issues with limited control over generative models, enhancing generalization performance under varying data distributions, dealing with learning using limited labelled data, promoting fairness in decision-making systems, and more. Saptarshi’s scholarly contributions extend to renowned journals such as TMLR and prominent conferences like ICLR. He has showcased his work at various research fora, such as Amazon Research Day 2023 and the Machine Learning Summer School in Okinawa, 2024.

Saptarshi holds a BS-MS dual degree in mathematics from IISER Kolkata. Throughout his BS-MS studies (2015–2020), he was a recipient of the INSPIRE fellowship from DST, Government of India.

As a Fulbright-Nehru Doctoral Research fellow at the University of Buffalo, Buffalo, NY, Saptarshi is trying to utilize causal knowledge and principles to assess data quality and make informed decisions (in the context of learning with not enough data) regarding samples that need to be labelled (from the large unlabelled dataset) rather than selecting them randomly. He is primarily working on the challenge of efficiently selecting the most relevant samples for labelling while considering budget constraints. This challenge holds excellent relevance not only in academic research but also within the AI industry. Saptarshi is an avid nature photographer and finds solace in the wilderness. His interests extend to culinary adventures, globetrotting, and engaging with diverse cultures. His leisure activities also include playing football and cricket.

Sriparna Saha

Dr. Sriparna Saha is currently serving as an Associate Professor in the Department of Computer Science and Engineering, IIT Patna, India. She has authored or co-authored more than 400 papers. Her current research interests include machine-learning, deep-learning, natural-language-processing, and biomedical-information-extraction. She is the recipient of Google-India-Women-in-Engineering-Award-2008, NASI-Young-Scientist-Platinum-Jubilee-Award-2016, BIRD Award-2016, IEI-Young-Engineers’-Award-2016, SERB-Women-in-Excellence-Award-2018, Pattern-Recognition-Letters-Editor-Award-2023, prestigious “Young-Faculty-Research-Fellowship” under Visvesvaraya-PhD-Scheme for Electronics-&-IT for-5-years (Jan 2019-Jan 2024), Humboldt-Research-Fellowship, Indo-U.S.-Fellowship-for-Women-in-STEMM-2018. She won the best paper awards in ICONIP 2023, CLINICAL-NLP workshop of COLING 2016, and Area-chair-award (Information Extraction) at IJCNLP-AACL 2023.

With her Fulbright fellowship, at University of South Carolina, Sriparna is working towards developing some unified large language models (LLM) for low-resource settings. In general, it has been shown in the recent literature that the existing LLMs are not performing well for low resource Indian languages like Bengali. This disparity raises concerns about the fairness of LLMs, as it may lead to biased outcomes and unequal access to information and resources for speakers of low-resource languages. In this project Sriparna aims to develop some LLMs for low-resource language setting by developing a scalable training approach using reinforcement learning from human feedback.

Ujjwal Maulik

Prof. Ujjwal Maulik is a full Professor in the Department of Computer Science and Engineering, Jadavpur University since 2004. He was also the former head of the same department. He has worked in many universities and research laboratories in Australia, China, France, Germany, Hungary, Italy, Slovenia and U.S. and also delivered lectures in many more countries. He is the Fellow of India (INAE), India, National Academy of Science India (NASI), International Association for Pattern Recognition (IAPR), US, The Institute of Electrical and Electronics Engineers (IEEE), U.S., Asia-Pacific Artificial Intelligence Association (AAIA), Singapore and Distinguish Member of the Association for Computing Machinery (ACM). He is a Distinguish Speaker of IEEE as well as ACM. His research interests include machine learning, pattern analysis, data science, bioinformatics and computational biology, multi-objective optimization, social networking, IoT and autonomous car. In these areas he has published ten books, more than three hundred fifty papers, mentored several start-ups, filed several patents and already guided twenty five doctoral students. His other interests include outdoor sports and classical music.

During his tenure as Fulbright-Nehru Academic and Professional Excellence Fellowship Prof. Maulik is working for the better understanding of newly developed NicE-seq technology for chromatin accessibility through the application of artificial intelligence (AI) methods. This research has the potential to uncover novel regulatory mechanisms and advance our understanding of the functional genomics landscape. The AI-driven approaches can expedite and enhance chromatin accessibility studies, leading to advancements in various fields, including gene regulation, disease mechanisms, and therapeutic development.