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. He was also awarded the 2022 Distinguished Alumnus Award from Indian Institute of Technology, Kanpur. 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, Hybrid learning techniques for scientific data reduction with performance guarantees, DOE (2021-2024), $900,000.
  2. Principal Investigator, RAPIDS2: A SciDAC Institute for Computer Science, Data and Artificial Intelligence, DOE (2020-2025), $550,000.
  3. Principal Investigator, Video-Based Machine Learning for Smart Traffic Analysis and Management, National Science Foundation Smart Cities and Communities, (2019-2023), approx. $2 million.
  4. Principal Investigator, Bigdata Analytics and Artificial Intelligence for Smart Intersections, Florida Department of Transportation (2019-2022), $750,000.
  5. 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).
  6. Principal Investigator, Machine Learning Algorithms for Improved Network Traffic Signal Policy Optimization, FDOT, (2019-2021), approx. $328K.
  7. Principal Investigator, EAGER: Software-Hardware Co-Design Approaches for Multi-Level Memories, National Science Foundation (2017-2020), $300,000.
  8. Principal Investigator, Machine Learning Algorithms for Demand and Turning Movement Count, FDOT, 2018-2021, approx. $200,000.
  9. Principal Investigator, Data Management and Analytics for UF Smart Testbed, FDOT, (2017-2020), approx. $540,000.

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ANNOUNCEMENTS

Recent Publications (Congrats to all the students involved).

  1. P. He, A. Wu, X. Huang, A. Rangarajan, S. Ranka. Machine Learning-based Highway Truck Commodity Classification Using Logo Data. Applied Sciences, to appear.
  2. P. He, P. Emami, S. Ranka and A. Rangarajan, Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions. Proceedings of AAAI conference on Artificial Intelligence, 2021.
  3. Y. Karnati, R. Sengupta, A.Rangarajan, S. Ranka , Subcycle Waveform Modeling of Traffic Intersections Using Recurrent Attention Networks, In IEEE Transactions on Intelligent Transportation Systems, special issue on AI. https://doi.org/10.1109/TITS.2021.3121250
  4. Y. Karnati, R. Sengupta, S. Ranka , Inter-Twin: Deep Learning Approaches for computing Measures of Effectiveness for Traffic Intersections, In Applied Sciences. https://doi.org/10.3390/app112411637
  5. P. Emami, L. Elefteriadou and S. Ranka, “Long-Range Multi-Object Tracking at Traffic Intersections on Low-Power Devices,” in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2021.3115513.
  6. P. He, P. Emami, S. Ranka and A. Rangarajan, Learning Scene Dynamics from Point Cloud Sequences. International Journal of Computer Vision （IJCV), 1-27, 2021.

I will be presenting at the following  conferences:

  1. Keynote Speaker, Machine Learning for Smart Transportation, nternational Conference on Civil Engineering Fundamentals and Applications (ICCEFA’23) , Dubai, UAE, December 2023.
  2. Keynote Speaker, Machine Learning for Smart Transportation, Advances in Information Communication Technology & Computing, Bikaner, India, December 2022.
  3. Keynote Speaker, Machine Learning for Smart Transportation, International Conference on Machine Learning and Intelligent Systems (MLIS2022), Seoul, Republic of Korea, November 2022.
  4. Keynote Speaker, Artificial Intelligence and Machine Learning for Smart Transportation, INFRAMEET 2022, November 2022.
  5. Keynote Speaker, Edge Based AI for Smart Transportation, International Conference on Computing Innovation and Applied Physics, August 2022.
  1. C. Laborde, E. Cenko , M. Mardini, S. Ranka, S. Nerella, M. Kheirkhahan, S. Ranka R. Fillingim, D. Corbett, E. Weber, P. Rashidi, T. Manini, Satisfaction, Usability, and Compliance With the Use of Smartwatches for Ecological Momentary Assessment of Knee Osteoarthritis Symptoms in Older Adults: Usability Study, JMIR Aging 2021;4(3):e24553
  2. M. Mardini, S. Nerella, M. Kheirkhahan, S. Ranka, R. Fillingim, Y. Hu, D. Corbett, E. Cenko, E. Weber, P. Rashidi, T. Manini, The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults With Knee Osteoarthritis: A Smartwatch-Based Demonstration Study, JMIR Mhealth Uhealth 2021;9(1):e19609, URL: https://mhealth.jmir.org/2021/1/e19609
  3. M. Mardini, S. Nerella, M. Kheirkhahan, S. Ranka, R. Fillingim, E. Cenko, P. Rashidi, T. Manini, The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults with Knee Osteoarthritis. Innovation in Aging, 4(Suppl 1), Dec. 2020, 799. https://doi.org/10.1093/geroni/igaa057.2897
  4. M. Mardini, S. Nerella, M. Kheirkhahan, et al. The Temporal Relationship Between Ecological Pain and Life-Space Mobility in Older Adults With Knee Osteoarthritis. Innov Aging. 2020;4(Suppl 1):799. Published 2020 Dec 16. doi:10.1093/geroni/igaa057.2897
  5. C. Laborde, E. Cenko , M. Mardini, S. Ranka, P. Rashidi, T. Manini. Older Adults’ Satisfaction and Compliance of Smartwatches Providing Ecological Momentary. Innov Aging. 2020;4(Suppl 1):799. Dec 2020.doi:10.1093/geroni/igaa057.2898
  6. M. Alperti, N. S. P. Kotai, S. Ranka, T. V Mendoza, L. M. Solberg, P. Rashidi, M. Manini, A Simulated Graphical Interface for Integrating Patient-Generated Health Data From Smartwatches With Electronic Health Records: Usability Study, JMIR Human Factors 2020;7(4):e19769, Oct. 2020, 8 pages.
  7. D. Anton, Y. Cruz-Almeida, A. Singh, J. Alpert, B. Bensadon, M. Cabrera, D. J. Clark, N. C. Ebner, K. A. Esser, R. B. Fillingim, S. M. Goicolea, S. M. Han, H. Kallas, A. Johnson, C. Leeuwenburgh, A. C. Liu, T.  M. Manini, M. Marsiske, F. Moore, P. Qiu, R. T. Mankowski, M. Mardini, C. McLaren, S. Ranka, P. Rashidi, S. Saini, K T. Sibille, S. Someya, S. Wohlgemuth, C. Tucker, R.  Xiao, M. Pahor, Innovations in Geroscience to enhance mobility in older adults, Experimental Gerontology, Volume 142, 2020, 18 pages.
  8. 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, Vol. 13, 2020, pp. 4674-4688..
  9. 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, July 2020, pp. 1-10.
  10. Emami, P. Pardalos, L Elefteriadou and S. Ranka, Machine Learning Methods for Data Association in Multi-Object Tracking, ACM Computing Surveys, Vol. 53, No. 4, Article 69, Aug. 2020 34 pages.

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  1. S. Gheibi, T. Banerjee, S. Ranka. S. Sahni, An Effective Data Structure for Contact Sequence Temporal Graphs, Proceedings of IEEE ISCC 2021, to appear.
  2. P. Emami, P. He, A. Rangarajan and S. Ranka, Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations, Proceedings of International Conference on Machine Learning, to appear.
  3. R. Sengupta, Y. Karnati, A.Rangarajan, S. Ranka, TQAM: Temporal Attention for Cycle-wise Queue Length Estimation using High-Resolution Loop Detector Data, Proceedings of 24th IEEE International Conference on Intelligent Transportation, (ITSC) 2021, to appear.
  4. A. Wu, T. Banerjee, A. Rangarajan and S. Ranka, Trajectory Prediction via Learning Motion Cluster Patterns in Curvilinear Coordinates, Proceedings of 24th IEEE International Conference on Intelligent Transportation (ITSC) 2021, to appear.
  5. D. Mahajan, Y. Karnati, A.Rangarajan, S. Ranka , An Automated Framework for Deriving Inter-section Coordination Plans, Proceedings of 24th IEEE International Conference on Intelligent Transportation (ITSC) 2021, to appear.
  6. Y. Karnati, R. Zapata, M. J. McConnell, R. R. K. Reddy, V. Regalla, A. Thakkar, J. Alpert, T. Mendoza, P. Rashidi, M. Mardini,, M. Marsiske, T. M. Gill, T. M. Manini, and S. Ranka . 2021. ROAMM: A customizable and interactive smartwatch platform for patient-generated health data. In 2021 Thirteenth International Conference on Contemporary Computing (IC3-2021), August 5–7, 2021, to appear, 9 pages
  7. K. Zhai, P. He, T. Banerjee, A. Rangarajan and S. Ranka, SparsePipe: Parallel Deep Learning for 3D Point Clouds, Proceedings of HiPC 2020, to appear.
  8. K. Zhai, T. Banerjee, A. Wijayasiri and S. Ranka, Batched Small Tensor-Matrix Multiplications On GPUs, Proceedings of HiPC 2020, to appear.
  9. R. 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.
  10. D. 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.
  11. 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

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  1. Invited Keynote Speaker, ROAMM: A smartwatch-based framework for real-time and online assessment and mobility monitoring, Third World Aging and Rejuvenation Conference (ARC-2021), September 2021.
  2. Invited Speaker, ROAMM: A smartwatch-based framework for real-time and online assessment and mobility monitoring, IEEE Symposium on Data Analytics and Internet of Things, November 2020.
  3. Invited Keynote Speaker, Artificial Intelligence for Transportation, World Congress on Artificial Intelligence and Robotics Research, Zurich, Switzerland, October. 2020.
  4. 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.
  5. 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.
  6.  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.
  7. Invited Plenary Speaker, International Conference on Machine Learning and Data Science, Hyderabad, India, Dec. 2019.
  8. Invited Keynote Speaker, A Multi-sensor System for Traffic Analysis at Smart Intersections, International Conference on Contemporary Computing, Noida, India, Aug. 2019
  9. Invited Keynote Speaker, Smart Intersection Control Algorithms for Automated and Connected Vehicles, BigDF Workshop, High Performance Computing Conference (HiPC 2017), Jaipur, India, Nov. 2017.
  10. Invited Speaker, Optimization Algorithms for Transportation, International Conference on Contemporary Computing, Noida, India, Aug. 2017.

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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.