Host City USA: Bengaluru

Kaylin Clements

Dr. Kaylin Clements has a BS in environmental science and a BA in business administration from the University of Florida, and an MS in conservation leadership and a PhD in human dimensions of natural resources from Colorado State University (CSU). Her past work has included: applied quantitative and qualitative research on protected area management and community engagement in southern Belize; studying pro-environmental behaviors in Florida and Belize related to controlling the invasive lionfish; and social network analysis on a variety of social and environmental issues. Between graduate degrees, she served as a social scientist for the U.S. Fish and Wildlife Service. She has also served as a facilitator and research assistant for the Center for Public Deliberation at CSU, as an instructor in human dimensions of natural resources courses at CSU, and as a social network research assistant for the Institute for Research in the Social Sciences. Most recently, as a research social scientist fellow for the United States Geological Survey, she served as the partner engagement coordinator and as a co-chair of the National Early Detection and Rapid Response Framework to prevent the establishment of invasive species in the United States.

Her main research interests center around human dimensions of natural resources, which applies social science theory and methods to understand complex social–ecological systems. Specifically, she is interested in how social networks, cultural norms and models, and other social factors support or inhibit adoption of pro-environmental behaviors and collaboration. She is also passionate about teaching and building capacity in the social sciences to enhance the impacts of conservation work.

Dr. Clements’s Fulbright-Nehru project is applying social network research methods to investigate the networks of healthcare professionals, community leaders, and health information in communities adjacent to wildlife habitat in the Western Ghats. The analysis is identifying barriers and opportunities for improved access to health and safety services and information. In addition, a social science methods course is training natural scientists in Bengaluru and at the Centre for Wildlife Studies to integrate social science into their research and practice.

Sanjeev Chawla

Dr. Sanjeev Chawla is a research assistant professor in the Department of Radiology, Perelman School of Medicine, University of Pennsylvania. He is also a medical physicist certified by the American Board of Medical Physics. The focus of Dr. Chawla’s research has been directed toward the development of metabolic and physiological MR imaging-derived biomarkers in making correct diagnosis and assessing treatment responses to established, novel, and emerging therapies in patients with brain tumor, head and neck cancer, and neurodegenerative diseases.

He has a master’s degree in chemistry from the Indian Institute of Technology Delhi and a PhD in radiology from Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow. He has authored 103 peer-reviewed original research/review articles and eight book chapters. He has been awarded research grants by agencies like the National Institute of Health/National Cancer Institute, the International Society for Magnetic Resonance in Medicine, and the Penn Center for Precision Medicine. Currently, he is leading two clinical trials related to electric field therapy in glioblastomas (NCT05086497) and evaluation of treatment response in the case of salivary gland tumors (NCT04452162).

Dr. Chawla is also an associate editor with the Journal of Translational Medicine and a reviewer for several leading scientific journals. Earlier, he was a guest editor with Frontiers in Neurology. He has also won the Outstanding Researcher Award in Neuroradiology from the Venus International Foundation and the Leadership and Mentorship Scholarship Award from the National Cancer Institute Awardee Skill Development Consortia.

Dr. Chawla’s Fulbright-Nehru project is building a robust, reproducible, and objective clinical decision support (CDS) tool by incorporating physiologic and metabolic MR imaging-derived parameters and molecular signatures combined with machine learning algorithms for assessing treatment response in glioblastoma patients receiving standard treatment as well as novel therapies. This tool will not only facilitate accurate and timely differentiation of true progression and pseudo progression in glioblastomas (precision diagnostics) but also allow clinicians to make “go/stop” decisions on therapeutic interventions (precision therapeutics). Additionally, it will help to relieve “scanxiety” among patients and their loved ones.

Ricca Slone

Prof. Ricca Slone has been teaching graduate public policy courses in Northwestern University’s School of Professional Studies for the past 12 years. Most recently, she taught an online course on Congressional procedure in Fall 2023. Before teaching at Northwestern University, Prof. Slone worked on water-supply issues for three years at the Environmental Law & Policy Center, a research and advocacy organization based in Chicago which works in several U.S. Midwestern states. From 1997 to 2005, Prof. Slone served four terms as a state representative in the Illinois House of Representatives, representing the 92nd district in central Illinois. She also chaired the Higher Education Appropriations Committee and was the vice chair of the Energy & Environment Committee.

As a senior scholar near the end of her working years, Prof. Slone hopes to rejuvenate the Sun Oven project by relaunching the assembling and marketing of solar ovens from a new location in Karnataka so that they can help women in South India who cook over wood fires.

Prof. Slone’s Fulbright-Nehru project is identifying strategies to overcome Indian cultural challenges to adopting renewable technologies. The framework for analysis is Nordgren and Schonthal’s friction theory (The Human Element, 2022). The project’s focus is on adoption of clean solar cooking by rural Indian women who otherwise cook over smoky fires, which is time consuming and causes respiratory diseases and deforestation. The research is a case study comparing the relative ease of adoption of the following technologies: wind turbines for energy; electric tuk-tuks for mobility; and solar ovens for cooking. Prof. Slone’s hypothesis is that cooking will encounter the most cultural resistance.

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.