Sanjay Ranka is a Distinguished Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research is on developing algorithms and software using Machine Learning, Internet of Things, GPU Computing and Cloud Computing for solving applications in Transportation and Health Care. He is a fellow of the IEEE, AAAS, and AIAA (Asia-Pacific Artificial Intelligence Association) and a past member of IFIP Committee on System Modeling and Optimization. He was awarded the 2020 Research Impact Award from IEEE Technical Committee on Cloud Computing. His research is currently funded by NIH, NSF, USDOT, DOE and FDOT.

From 1999-2002, as the Chief Technology Officer and co-founder of Paramark (Sunnyvale, CA), he conceptualized and developed a machine learning based real-time optimization service called PILOT for optimizing marketing and advertising campaigns. Paramark was recognized by VentureWire/Technologic Partners as a Top 100 Internet technology company in 2001 and 2002 and was acquired in 2002.

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RESEARCH AREAS

We are developing algorithms and software to fuse real-time feeds from video cameras and traffic sensor data to generate real-time detection, classification, and space-time trajectories of individual vehicles and pedestrians. This information is then transmitted to a cloud-based system and then synthesized to create a real-time city-wide traffic palette.  Learn more

Data mining and machine learning of large dimensional datasets is critical for understanding underlying relationships and ultimately improving healthcare outcomes.  Learn more

Hybrid multi-core processors (HMPs) – processors consisting of multiple cores and GPUs – are dominating the landscape of the next generation of computing from desktops to extreme-scale systems. We are developing algorithms and software that can exploit these architectures for a variety of computational science applications.  Learn more

BOOKS

RECENT FUNDING

  1. Principal Investigator, RAPIDS2: A SciDAC Institute for Computer Science, Data and Artificial Intelligence, DOE (2020-2025), $550,000.
  2. Principal Investigator, Video-Based Machine Learning for Smart Traffic Analysis and Management, National Science Foundation Smart Cities and Communities, (2019-2023), approx. $2 million.
  3. Principal Investigator, Bigdata Analytics and Artificial Intelligence for Smart Intersections, Florida Department of Transportation (2019-2022), $750,000.
  4. Principal Investigator, Wearable Technology Infrastructure to Enhance Capacity for Real-Time, Online Assessment and Mobility (ROAMM) of Intervening Health Events in Older Adults, National Institute of Aging, 2019-2024, approx. $2.6 Million (Todd Manini is the other PI).
  5. Principal Investigator, Machine Learning Algorithms for Improved Network Traffic Signal Policy Optimization, FDOT, (2019-2021), approx. $328K.
  6. Principal Investigator, EAGER: Software-Hardware Co-Design Approaches for Multi-Level Memories, National Science Foundation (2017-2020), $300,000.
  7. Principal Investigator, Machine Learning Algorithms for Demand and Turning Movement Count, FDOT, 2018-2021, approx. $200,000.
  8. Principal Investigator, Data Management and Analytics for UF Smart Testbed, FDOT, (2017-2020), approx. $540,000.

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ANNOUNCEMENTS

I will be presenting a keynote on ROAMM: A smartwatch-based framework for real-time and online assessment and mobility monitoring at Third World Aging and Rejuvenation Conference (ARC-2021), September 2021.

Congrats to Patrick Emami for acceptance of his paper for ICML 2021  (P. Emami, P. He, A. Rangarajan and S. Ranka, Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations, Proceedings of 2021 International Conference on Machine Learning, to appear).

  1. Wijayasiri, T. Banerjee, S. Ranka, S. Sahni, and M. S. Schmalz. Multiobjective Optimization of SAR Reconstruction on Hybrid Multicore Systems, Multiobjective Optimization of SAR Reconstruction on Hybrid Multicore Systems, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15 pages, accepted.
  2. He, A. Wu, X. Huang, J. Scott, A. Rangarajan, and S. Ranka. Truck and Trailer Classification with Deep Learning Based Geometric Features. IEEE Transactions on Intelligent Transportation Systems, to appear, 8 pages.
  3. Emami, P. Pardalos, L Elefteriadou and S. Ranka, Machine Learning Methods for Data Association in Multi-Object Tracking, ACM Computing Surveys, to appear, approx. 35 pages.
  4. Pourmehrab, P. Emami, M. Martin-Gasulla, J. Wilson, L. Elefteriadou, and S. Ranka, Signalized Intersection Performance with Automated and Conventional Vehicles: A Comparative Study, ASCE Journal of Transportation Engineering, Part A: Systems, to appear, 9 pages.
  5. Huang, P. He, A. Rangarajan. and S. Ranka. Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near-Accident Detection in Traffic Video. ACM Transactions on Spatial Algorithms and Systems, Vol. 6., No.2, Jan. 2020, pp. 1-28
  6. Zhai, T. Mishra, J. Hackl, D. Zwick, R. Koneru, and S. Ranka. Dynamic Load Balancing for a Mesh-Based Scientific Application. Concurrency and Computation: Practice and Experience, to appear.
  7. Kheirkhahan, S. Nair, A. Davoudi, P. Rashidi, A. A. Wanigatunga, D. B. Corbett, T. Mendoza, T. M. Manini, and S. Ranka. A Smartwatch-Based Framework for Real-Time and Online Assessment and Mobility Monitoring. Journal of Biomedical Informatics, Vol. 89, 2019, pp. 29-40.
  8. Yang, C. Delcher, E. Shenkman, and S. Ranka. Expenditure Variations Analysis Using Residuals for Identifying High Health Care Utilizers in a State Medicaid Program. BMC Medical Information & Decision Making, Vol. 19(1), 2019, pp. 131:1-15.
  9. Gadou, T. Banerjee, M. Arunachalam, S. Ranka. Multiobjective Evaluation and Optimization of CMT-Bone on Multiple CPU/GPU Systems. Sustainable Computing, Vol. 22, 2019, pp. 259-271.
  10. Yang, C. Delcher, E. Shenkman, and S. Ranka. Machine Learning Approaches for Predicting High Cost High Need Patient Expenditures in Health Care. BMC BioMedical Engineering OnLine, 2018, 17:131.

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  1. Sengupta, R. Reddy, P.J. Shah, A. Rangarajan, S. Ranka, A Platoon Matching Approach for the Estimation of Arterial Travel Time Distributions, Proceedings of IEEE Intelligent Transportation Systems Conference, September 2020, to appear.
  2. Mahajan, Y. Karanati, A. Rangarajan, S. Ranka, Unsupervised Summarization and Change Detection in High-Resolution Signalized Intersection Datasets, Proceedings of IEEE Intelligent Transportation Systems Conference, September 2020, to appear.
  3. Mahajan, Y. Karanati, T. Banerjee, R. Reddy, A. Rangarajan, S. Ranka, A Scalable Data Analytics and Visualization System for City-wide Traffic Signal Data-sets, Proceedings of IEEE Intelligent Transportation Systems Conference, September 2020, to appear.
  4. Gheibi, T. Banerjee, S. Ranka. S. Sahni, Cache Efficient Louvain with Local RCM, Proceedings of ISCC 2020, to appear.
  5. Mahajan, Y. Karnati, T. Banerjee, A. Rangarajan, and S. Ranka, A Data Driven Approach to Derive Traffic Intersection Geography Using High Resolution Controller Logs, Proceedings of 2020 Vehicle Technology and Intelligent Transportation System (VEHITS), 2020, accepted.
  6. He, A. Wu, X. Huang, A. Rangarajan, and S. Ranka, Video-Based Machine Learning System for Commodity Classification, Proceedings of 2020 Vehicle Technology and Intelligent Transportation System (VEHITS), 2020, accepted.
  7. Chen, T. Banerjee, X. Huang, A. Rangarajan, and S. Ranka, A Visual Analytics System for Processed Videos from Traffic Intersections, Proceedings of 2020 Vehicle Technology and Intelligent Transportation System (VEHITS), 2020, accepted.
  8. Banerjee, X. Huang, K. Chen, A. Rangarajan, and S. Ranka,
    Clustering Object Trajectories for Intersection Traffic Analysis, Proceedings of 2020 Vehicle Technology and Intelligent Transportation System (VEHITS), 2020, accepted.
  9. Huang T. Banerjee, K. Chen, N. Varanasi, A. Rangarajan and S. Ranka, Machine Learning based Video Processing for Real-time Near-Miss Detection, Proceedings of 2020 Vehicle Technology and Intelligent Transportation System (VEHITS), 2020, accepted.

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  1. Invited Keynote Speaker, Big data Computing and Machine Learning for Intelligent Transportation and Connected Vehicles, The Fifth International Conference on Fog and Mobile Edge Computing (FMEC 2020), Paris, France, Jul. 2020.
  2. Invited Keynote Speaker, Big data Computing and Machine Learning for Intelligent Transportation and Connected Vehicles, The Third International Workshop on Intelligent Transportation and Connected Vehicles Technologies (ITCVT 2020), part of The 32th IEEE/IFIP Network Operations and Management Symposium (NOMS 2020), Budapest, Hungary, Apr. 2020.
  3.  Invited Speaker, Vision Track, A Vision of Smart Traffic Infrastructure for Traditional, Connected and Autonomous Vehicles, IEEE Conference on Connected and Autonomous Driving (MetroCAD), Detroit, Michigan,  Feb. 2020.
  4. Invited Plenary Speaker, International Conference on Machine Learning and Data Science, Hyderabad, India, Dec. 2019.
  5. Invited Keynote Speaker, A Multi-sensor System for Traffic Analysis at Smart Intersections, International Conference on Contemporary Computing, Noida, India, Aug. 2019
  6. Invited Keynote Speaker, Smart Intersection Control Algorithms for Automated and Connected Vehicles, BigDF Workshop, High Performance Computing Conference (HiPC 2017), Jaipur, India, Nov. 2017.
  7. Invited Speaker, Optimization Algorithms for Transportation, International Conference on Contemporary Computing, Noida, India, Aug. 2017.
  8. Invited Keynote Speaker, Performance, Energy and Thermal Aware Algorithms for Hybrid Multicore Processors, The 22nd IEEE Symposium on Computers and Communications, Heraklion, Greece, Jul. 2017.
  9. Invited Keynote Speaker, Multiobjective Algorithms for Hybrid Multicore Processors, International Green and Sustainable Computing Conference, Huangzhou, China, Nov. 2016.
  10. Invited Keynote Speaker, High Performance Computing and Data Science for Large Scale Spatiotemporal Applications, Noida, India, International Conference on Contemporary Computing, Aug. 2016

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  1. United States Patent Number 8,805,715. Brian Jones and Sanjay Ranka. Method for Improving the Performance of Messages Including Internet Splash Pages. Aug. 12, 2014.
  2. United States Patent Number 8,386,315. Arvind Bala, Richard Chatwin, Brian Jones, Ahmet Nalcacioglu, and Sanjay Ranka. Yield Management System and Method for Advertising Inventory, Feb. 26, 2013.
  3. United States Patent Number 8,260,663. Sanjay Ranka, Diane Chang, and Daniel Veiner. Method, Algorithm, and Computer Program for Targeting Messages Including Advertisements in an Interactive Measurable Medium, Sept. 4, 2012.
  4. United States Patent Number 8,144,686. Sartaj Sahni, Nageshwar Sirikonda Venkata, Sanjay Ranka, Yan Li, Eun-sung Jung, and Narayana Kamath. Method and Systems for Bandwidth Scheduling and Path Computation for Connection-Oriented Networks, Mar. 27, 2012.
  5. United States Patent Number 7,573,978. Srijit Kamath, Sartaj Sahni, Jonathan Li, Jatinder Palta, and Sanjay Ranka. Variable Feathering Field Splitting for Intensity Modulated Fields of Large Size, Aug. 11, 2009.
  6. United States Patent Number 7,415,423. Sanjay Ranka, Jason Lenderman, and James Weisinger. Method, Algorithm, and Computer Program for Optimizing the Performance of Messages Including Advertisements in an Interactive Measurable Medium, Aug. 19, 2008.
  7. United States Patent Number 7,406,434. Diane Chang, Richard Chatwin, Sachin Kumar, Sanjay Ranka, James Weisinger, and Jason Lenderman. System and Method for Improving the Performance of Electronic Media Advertising Campaigns through Multi-attribute Analysis and Optimization, July 29, 2008.
  8. United States Patent Number 7,142,635. Srijit Kamath, Sartaj Sahni, Jonathan Li, Jatinder Palta, and Sanjay Ranka. Field Splitting for Intensity Modulated Fields of Large Size, 28, 2006.
  9. United States Patent Number 7,085,348. Srijit Kamath, Sartaj Sahni, Jonathan Li, Jatinder Palta, and Sanjay Ranka. Leaf Sequencing Method and System, Aug. 1, 2006.
  10. United States patent number 6,563,952. Anurag Srivastava, G. D. Ramkumar, Vineet Singh, and Sanjay Ranka. Method of High Dimensional Data and Apparatus for Classification, May 13, 2003.
  11. United States Patent Number 6,173,280. G. D. Ramkumar, Sanjay Ranka, and Shalom Tsur. Method and Apparatus for Generating Weighted Association Rules, Jan. 9, 2001.
  12. United States Patent Number 5,987,468. Vineet Singh, Khaled Alsabti, and Sanjay Ranka. Structure and Method for Efficient Parallel High-Dimensional Similarity Join, Nov. 16, 1999.
  13. United States Patent Number 5,983,224. Vineet Singh, Sanjay Ranka, and Khaled Alsabti. Method and Apparatus for Reducing the Computational Requirements of K-Means Data Clustering, Nov. 9, 1999.