Host Institution USA: Indian Institute of Science

Meenakshi Singh

Dr. Meenakshi Singh is a condensed matter experimentalist with her research focused on macroscopic quantum phenomena, quantum coherence, and quantum entanglement. She received her PhD in physics from Pennsylvania State University in 2012. She went on to work at Sandia National Laboratories on quantum computing as a postdoctoral scholar. At Sandia, she worked with a team focused on developing deterministic counted ion implants for quantum computing.

Since 2017, she has been an assistant professor in the Department of Physics at the Colorado School of Mines. Her research projects include measurements of entanglement propagation, phonon physics in quantum dots and donors in semiconductors, and thermal effects in superconducting hybrids. Her research work in these areas has been published in more than 20 peer-reviewed journal publications and cited more than 900 times. She is the recipient of the prestigious CAREER award (2021–2026) from the National Science Foundation. Dr. Singh is also involved in nationwide educational efforts to build a quantum workforce through curriculum development, alliance building, and workshop organization. At the Colorado School of Mines, she has taught undergraduate and graduate courses in digital electronics and microelectronics processing.

Through this Fulbright-Nehru award, Dr. Singh aims to achieve research, pedagogical, and cultural objectives. The research objective is to perform cutting-edge thermal measurements that can bring new insights into our understanding of fundamental physics in quantum materials and devices and thus catalyze novel applications. The pedagogical objective is to establish a graduate-student exchange program between the Colorado School of Mines and the Indian Institute of Science. Through student exchange, she expects the researchers at the two universities to collaborate on quantum information science research while training the “quantum workforce” of tomorrow. As for her cultural objective, it involves harnessing the two countries’ shared interests in quantum information science to engage in meaningful cultural exchange.

Ramakanth Kavuluru

Dr. Ramakanth Kavuluru is a professor of biomedical informatics (Department of Internal Medicine) in the College of Medicine at the University of Kentucky (UKY). He also has a joint courtesy appointment in the Department of Computer Science at UKY. He graduated with a PhD in computer science in 2009 from UKY with a focus on the security properties of pseudorandom sequences. Subsequently, he worked in knowledge-based search systems for focused bioscience domains as a postdoctoral scholar at Wright State University. Since 2011, he has been working as a faculty member at UKY focusing on natural language processing methods and their use in biomedicine and healthcare.

High-level applications of Dr. Kavuluru’s research include cohort selection for clinical trials, literature-based knowledge discovery, computer-assisted coding, social media-based surveillance for substance abuse, and clinical-decision support for precision medicine. He employs methods from machine learning (including deep learning) and data mining fields to drive his research agenda. His recent methodological contributions deal with zero-shot and few-shot classification, large language models, transfer learning, domain adaptation, and end-to-end relation extraction. Thus far, in his capacity as primary advisor, he has helped seven doctoral students and 10 master’s students attain their graduation.

Predicting disease onset ahead of time is an important application of artificial intelligence (AI) and this is being actively pursued in the U.S. and other western nations. From a global health perspective, it is not clear if the implications of the findings of U.S. patient-based modeling translate to more populous and diverse areas of the world. Thus, using latest machine learning methods and data sets from Indian healthcare facilities, Dr. Kavuluru’s Fulbright-Nehru project is rigorously assessing how well the promise of AI holds when applied to the Indian patient setting compared to the simpler standard-of-care approaches to risk stratification.

Jasmeet Judge

Dr. Jasmeet Judge received her BS in physics from Stillman College, Alabama, and her MS in electrical engineering, and PhD in electrical engineering and atmospheric, oceanic, and space sciences from the University of Michigan. She is a professor in the Agricultural and Biological Engineering Department at the University of Florida, where she is also the director of the Center for Remote Sensing.

Dr. Judge’s research interests include microwave remote-sensing applications to terrestrial hydrology, crop development, and crop growth; electromagnetic models for dynamic agricultural terrains; and machine learning (ML) methods for spatio-temporal scaling and data-model fusion. For her research projects, she has received grants from NASA, the National Science Foundation, and the U.S. Department of Agriculture. She has led many field experiments with active and passive microwave sensors to develop/improve remote sensing, crop growth, hydrology, and ML algorithms. Dr. Judge has also won NASA Group Achievement Awards for interdisciplinary field campaigns. She has over 70 journal publications, three co-authored books, and numerous conference and invited presentations to her credit.

In addition to research, Dr. Judge has been active in advocating for the protection of the EM spectrum as the past member, vice chair, and chair of the National Academies Committee on Radio Frequency. She is also a member of the American Geophysical Union and a senior member of the IEEE Geoscience and Remote Sensing Society, where she has served in different roles on many committees for the past three decades.

Dr. Judge’s Fullbright-Kalam project is being carried out in collaboration with researchers in the Interdisciplinary Center for Water Research at the Indian Institute of Science in utilizing data from the upcoming NASA ISRO Synthetic Aperture Radar (NISAR) mission for the availability of timely soil and crop information in India. In addition, she is training the next generation of Indian scientists in microwave remote sensing.