Sanjay Ranka
· Ph.D. ProfessorUniversity of Florida · Computer & Information Science & Engineering
Active 1988–2026
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About
Sanjay Ranka is a Distinguished Professor in the Department of Computer & Information Science & Engineering at the University of Florida. His research focuses on high-performance computing and big data science, with an emphasis on developing efficient computational methods and data analysis techniques to model scientific phenomena. His practical applications include improving healthcare quality and reducing traffic accidents. Ranka has a background that includes serving as the Chief Technology Officer at Paramark, where he developed a real-time optimization service called PILOT, which served over 10 million decisions daily with high uptime, and was recognized as a top internet technology company before its acquisition. He has held faculty positions at Syracuse University, been an academic visitor at IBM, and a summer researcher at Hitachi America Limited. Ranka has co-authored a book, four monographs, and over 300 journal and conference articles. His work has received multiple awards, including best paper recognitions and the 2020 Research Impact Award from the IEEE Technical Committee on Cloud Computing. He is a fellow of IEEE and AAAS, and serves as an editor for several prominent journals. His research interests include data mining, informatics, grid computing, digital health, embedded systems, and energy-aware computing.
Research topics
- Computer Science
- Artificial Intelligence
- Psychology
- Medicine
- Machine Learning
- Physical medicine and rehabilitation
- Engineering
- Mathematics
- Computer vision
- Physical therapy
Selected publications
ACM Transactions on Spatial Algorithms and Systems · 2020 · 93 citations
Senior authorCorrespondingCamera-based systems are increasingly used for collecting information on intersections and arterials. Unlike loop controllers that can generally be only used for detection and movement of vehicles, cameras can provide rich information about the traffic behavior. Vision-based frameworks for multiple-object detection, object tracking, and near-miss detection have been developed to derive this information. However, much of this work currently addresses processing videos offline. In this article, we…
JMIR mhealth and uhealth · 2021 · 43 citations
BACKGROUND: Research has shown the feasibility of human activity recognition using wearable accelerometer devices. Different studies have used varying numbers and placements for data collection using sensors. OBJECTIVE: This study aims to compare accuracy performance between multiple and variable placements of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults. METHODS: In total, 93 participants (mean age 72.2 years, SD 7.1) c…
JMIR Aging · 2021 · 32 citations
BACKGROUND: Smartwatches enable physicians to monitor symptoms in patients with knee osteoarthritis, their behavior, and their environment. Older adults experience fluctuations in their pain and related symptoms (mood, fatigue, and sleep quality) that smartwatches are ideally suited to capture remotely in a convenient manner. OBJECTIVE: The aim of this study was to evaluate satisfaction, usability, and compliance using the real-time, online assessment and mobility monitoring (ROAMM) mobile app d…
Innovations in Geroscience to enhance mobility in older adults
Experimental Gerontology · 2020 · 30 citations
JMIR mhealth and uhealth · 2020 · 28 citations
BACKGROUND: Older adults who experience pain are more likely to reduce their community and life-space mobility (ie, the usual range of places in an environment in which a person engages). However, there is significant day-to-day variability in pain experiences that offer unique insights into the consequences on life-space mobility, which are not well understood. This variability is complex and cannot be captured with traditional recall-based pain surveys. As a solution, ecological momentary asse…
Recent grants
NSF · $270k · 2009–2013
Sparse Direct Methods on High-Performance Heterogeneous Architectures
NSF · $310k · 2011–2015
NSF · $535k · 2003–2008
Frequent coauthors
- 140 shared
Anand Rangarajan
- 82 shared
Tania Banerjee
- 74 shared
Sartaj Sahni
University of Florida
- 41 shared
Yashaswi Karnati
- 37 shared
Chilukuri K. Mohan
Virtual High School
- 35 shared
Todd M. Manini
University of Florida
- 31 shared
Rahul Sengupta
University of Florida
- 29 shared
Pan He
Auburn University
Labs
Education
- 1990
Ph.D., Computer Science
University of California, Santa Barbara
- 1986
M.S., Computer Science
University of California, Santa Barbara
- 1983
B.S., Computer Science and Engineering
Indian Institute of Technology, Kanpur
Awards & honors
- 2020 Research Impact Award from IEEE Technical Committee on…
- Best Paper Award at ICN 2007
- Best Student Paper Award at ACM-BCB 2010
- Best Paper Award at BICOB 2014
- Best Student Paper Runner-up Award at IGARSS 2015
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