Faculty and Staff

Ravi Sankar, PhD, PE

Professor of Electrical Engineering and Director, iCONS (Interdisciplinary Communications Networking and Signal Processing) Research Group

 

Office: ENB 373 

Phone: 813-974-4769

Email

Ravi Sankar

Biography

Dr. Ravi Sankar is a Theodore and Venette Askounes-Ashford Distinguished Scholar and U.S. Fulbright Scholar Awards winning Professor of Electrical Engineering and has been with USF since 1985. He is responsible for establishing and leading the Interdisciplinary Communications, Networking and Signal Processing (iCONS) Research group and the Interdisciplinary Center of Excellence in Telemedicine (ICE-T). He is also the advisor of the Communications and Signal Processing graduate program track and a member of the Biomedical Engineering program. His educational background includes the B. E. (Honors) degree in Electronics and Communication Engineering from the University of Madras, India, M. Eng. degree in Electrical Engineering from Concordia University, and Ph. D. degree in Electrical Engineering from the Pennsylvania State University.

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Research Interests

Dr. Sankar鈥檚 main research interests are in the multidisciplinary areas of wireless communications, networking, signal processing and its applications. In particular, in integrating Artificial Intelligence (AI) and Machine Learning (ML) techniques in modeling and design of high performance and robust systems. His current focus is on the use of wearable sensors and technologies for advancing health care.

Collaborative research in the areas mentioned is conducted by the interdisciplinary Communications, Networking, and Signal Processing created and directed by Dr. Sankar. He has published extensively in those areas with over 250 papers in journals and premier international conferences and several book chapters. His research has been cited widely as measured by h-index of 30 and i10-index of 80. Under his leadership, they have successfully conducted numerous funded research projects with the support from various federal and state agencies, and industries.

Recent research involves the use of sensing and processing for applications in health care, extreme weather and pandemic disease spread prediction. Here, a couple of research areas where they have made significant contributions and added original knowledge to the current art by providing novel solutions to societal issues are elaborated: Area 1: Leveraging various bio-sensors/signals and wearable technologies and applying signal processing along with diverse statistical and machine learning models for automated detection and diagnosis assessment of neurodegenerative diseases such as Parkinson鈥檚 disease (PD). We have developed novel methods for early detection of motor symptoms using biomarkers including gait, speech, EEG, and fMRI. Current goal is to combine those multiple biomarkers and their relevant features to develop a multi-modal fusion system that can improve early-stage detection and diagnosis accuracy. Area 2: Integrated physical and social sensing for predicting extreme weather such as hurricanes and also disease spread. The objective is to integrate different data sources by fusing people-centric information derived from quantified social media with physical sensor network data. Algorithms have been developed to create composite models for aggregating the information derived from multiple data streams for improved prediction in applications such as extreme weather and disease spread. You can find more details in the website

Teaching

Dr. Sankar currently teaches the signal processing series courses. He is also a co-advisor for the Communications, Networking, and Signal Processing track program. Click on the link for the track information:

Signal Processing Series

Signal Processing deals with the operation of extracting, enhancing, storing, and transmitting useful information. This is probably second only to mathematics in terms of the number of areas it has been applied to from acoustics, audio, biomedical, communication, geophysics, image, sonar, speech, radar, terrestrial, to any other data including mechanical vibrations, transportation, and financial data analysis.

The following courses are offered. Click on the course title to find out more about the course.

  • EEL 6502 / EEL 4756 - Digital Signal Processing I
    This course provides an introduction to the exciting world of Signal Processing. When you complete this course, you will be familiar with the fundamentals of DSP methods and applications using the interactive MATLAB signal processing tool box.
  • EEL 6722C / EEL 4727C - DSP/FPGA Lab (Real-Time DSP Systems Laboratory)
    This course provides an introduction to the development of real-time digital signal processing (DSP) systems from algorithm to hardware using DSP, FPGA and hybrid DSP/FPGA rapid prototyping platforms.
  • EEL 6752 - Digital Signal Processing II
    This course provides an introduction to advanced topics in digital signal processing -- linear estimation and prediction analysis, signal modeling, lattice filters, spectral estimation and adaptive filters; signal processing algorithms and techniques used in a broad range of applications.
  • EEL 6586 - Speech Signal Processing
    This course will familiarize the student with principles of digital speech signal processing and its applications.
  • EEL 6753 - Digital Signal Processing III
    This course serves as the vehicle for introducing graduate students to the advanced topics in signal processing. Some selected topics include but are not limited to: Adaptive Filtering, Wavelets, Time-Frequency Methods, Signal Processing Applications, etc.

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Publications

[H-index: 30 and i10-index: 79; 7800+ citations; Ref: ]

A. Patents

1. P. C. Adithya, R. Sankar, W. A. Moreno, and S. Hart, Systems and Methods for Determining Physiological Parameters from Blood Flow Dynamics U.S. Patent No. 10,667,701. Washington, DC: U.S. Patent and Trademark Office, June 2, 2020.

2. P. C. Adithya, S. Pandey, R. Sankar, and W. A. Moreno, Systems and Methods for Identifying a Biomedical Condition, U.S. Patent No. 11,357,470. Washington, DC: U.S. Patent and Trademark Office, June 14, 2022.

B. Book Chapters (Total: 12)

  • S. Thiruvenkadam, R. Sankar, and I. Ra, Investigation of Wind and Photovoltaic Energy System for Daily Load Dispatch on Reconfigurable Microgrid through Hybrid Fuzzy-MFO, Book Chapter in 鈥淎pplied Soft Computing Techniques for Renewable Energy鈥�, Nova Science Publishers, July 2020.

C. Selected Recent Journal Papers (Total: 67)

  • S. B. Appakaya, R. Pratihar, and R. Sankar, Parkinson鈥檚 Disease Classification Framework using Vocal Dynamics in Connected Speech, Algorithms, MDPI, Vol. 16, No. 11, 509, 19 pages, November 2023. (Impact Factor: 2.3)
  • H. Srivastava and R. Sankar, Cooperative Attention Based-learning Between Diverse Data Sources, Algorithms, MDPI, Vol. 16, No. 5, 240, 2023. (Impact Factor: 2.3)
  • Cong Xu and Ravi Sankar, Multiple Sound Sources 3D Localization System Using TDOA and Tetrahedral Microphone Array, Electronics Science Technology and Applications, Universe Scientific Publishing, Vol. 10, No. 3, 2023.
  • S. Sobolewski, W. L. Adams, Jr., J. E. Eckersley III, and R. Sankar, Improving High-Demand VDATS TPS Performance Through More Effective ATE Interface Design Using Example of AMR Application, IEEE Instrumentation & Measurement Magazine, Vol. 26, No. 5, pp. 18-24, August 2023.
  • H. Srivastava, E. Sheybani, and R. Sankar, Social Network Anomaly Detection for Optimized Decision Development, International Journal of Interdisciplinary Telecommunications and Networking (IJITN), IGI Global, Vol.14, No.1, pp. 1-8, Sep. 2022.
  • S. A. Khoshnevis and R. Sankar, Diagnosis of Parkinson's Disease Using Higher Order Statistical Analysis of Alpha and Beta Rhythms, Biomedical Signal Processing and Control, Elsevier, Vol. 77, Article Number 103743, August 2022. (IF: 5.076)
  • S. A. Khoshnevis and R. Sankar, Classification of the Stages of Parkinson鈥檚 Disease Using Novel Higher-Order Statistical Features of EEG Signals, Neural Computing and Applications, Springer, Vol. 33, No. 13, pp. 7615-7627, July 2021. (IF: 5.606)
  • P. C. Adithya, S. Hart, A. Tejada-Martinez, W. A. Moreno, and R. Sankar, Novel Catheter Stethoscope: A Feasibility Study, IEEE Transactions on Biomedical Engineering (TBME), Vol. 68, No. 2, pp. 606-615, February 2021. (Impact Factor: 4.424)
  • S. Yao, R. Sankar, and I. Ra, A Collusion-Resistant Identity-Based Proxy Reencryption Scheme with Ciphertext Evolution for Secure Cloud Sharing, Security and Communication Networks, Wiley, Volume 2020, October 14, 2020, 16 pages, (IF: 1.791)
  • H. Srivastava and R. Sankar, Information Dissemination from Social Network for Extreme Weather Scenario, IEEE Transactions on Computational Social Systems, Vol. 7, No. 2, pp. 319-328, April 2020. (Impact Factor: 3.290)
  • S. A. Khoshnevis and R. Sankar, Applications of Higher Order Statistics in Electroencephalography Signal Processing: A Comprehensive Survey, IEEE Reviews in Biomedical Engineering (R-BME), Vol. 13, pp. 169-183, Nov. 2019. (IF: 6.180)
  • N. Sapankevych and R. Sankar, Nonlinear Time Series Prediction Performance Using Constrained Motion Particle Swarm Optimization, Transactions on Machine Learning and Artificial Intelligence, Vol. 5, No. 5, pp. 25-46, Oct. 2017.
  • P. C. Adithya, R. Sankar, W. A. Moreno, and S. Hart, Trends in Fetal Monitoring Through Phonocardiography: Challenges and Future Directions, Biomedical Signal Processing and Control, Elsevier, Vol. 33, pp. 289-305, Mar. 2017. (IF: 3.137)
  • S. V. Perumal and R. Sankar, Gait and Tremor Assessment for Patients with Parkinson鈥檚 Disease Using Wearable Sensors, Information and Communications Technology (ICT) Express, KICS/Elsevier, Vol. 2, No. 4, pp. 168-174, Dec. 2016.
  • I. Butun, I. Ra, and R. Sankar, An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks, Sensors, MDPI, Vol. 15, No. 11, pp. 28960-28978, Nov. 2015. (Impact Factor: 3.275)
  • I. Butun, R. Sankar, and I. Ra, PCAC: Power and Connectivity Aware Clustering for Wireless Sensor Networks, EURASIP Journal on Wireless Communications and Networking, Spring Open Journal, March 20, 2015.
  • I. Butun, S. D. Morgera, and R. Sankar, A Survey of Intrusion Detection Systems in Wireless Sensor Networks, IEEE Communications Surveys and Tutorials, Vol. 16, No. 1, pp. 266-282, 2014. (Impact Factor: 23.7)

D. Selected Recent Refereed Conference Papers (Total: 185)

  • X. Xu, R. Sankar, and I. Ra, Enhancing Lung Disease Diagnosis via Semi-Supervised Machine Learning, The 20th World Congress of the International Fuzzy Systems Assoc. (IFSA), Daegu, S. Korea, Aug. 20-24, 2023.
  • R. Pratihar, R. Sankar, and I. Ra, Comparative Analysis of Speech Features in the Aspect of Parkinson鈥檚 Disease Classification Based on Machine Learning Methods, The 20th World Congress of the International Fuzzy Systems Association (IFSA), Daegu, Korea, Aug. 20-24, 2023.
  • S. Appakaya, R. Sankar, and I. Ra, Novel Parkinson鈥檚 Disease Classification using Voiced Speech with Advanced Spectrograms, Convolutional Autoencoders and Machine Learning, The 11th International Conference on Smart Media and Applications (SMA), Saipan, USA, Oct. 19-22, 2022.
  • X. Xu, I. Ra, and R. Sankar, Classification of Lung Sounds using Machine Learning, The 11th International Conference on Smart Media and Applications (SMA), Saipan, USA, Oct. 19-22, 2022.S. Sobolewski, William Larry Adams, Jr., and R. Sankar, Recognition of Modern Modulated Waveforms with Applications to ABMS and VDATS Test Program Set Development, IEEE Autotestcon, National Harbor, MD, Aug 29-Sep 2, 2022.
  • H. Srivastava and R. Sankar, Cooperation Model for Optimized Classification on Social Data, The 4th International Workshop on Social (Media) Sensing (SMS 2022) in conjunction with IEEE 27th IEEE Symposium on Computers and Communications (ISCC 2022), Rhodes Island, Greece, June 30 -July 3, 2022.
  • H. Srivastava, E. Sheybani, and R. Sankar, Social Network Anomaly Detection for Optimized Decision Development, The 20th Wireless Telecommunications Symposium (WTS), Pomona, CA, April 6-8, 2022.
  • S. Sobolewski, William Larry Adams, Jr., and R. Sankar, Universal Feature Vectors for Discrimination Of Modern Modulated Waveforms, The 20th Wireless Telecommunications Symposium (WTS), Pomona, CA, April 6-8, 2022.
  • S. A. Khoshnevis, N. Maharaj, I. Ra, and R. Sankar, Classification of Parkinson鈥檚 Disease EEG Signals Using CNN and ResNet, The 10th International Conference on Smart Media and Applications (SMA), Gunsan, S. Korea, Sep. 9-11, 2021.
  • S. A. Khoshnevis, N. Maharaj, I. Ra, and R. Sankar, A Comparison of Transfer Learning and Neural Architecture Search for Diagnosis of Breast Cancer, The 10th Int. Conf. on Smart Media and Applications (SMA), Gunsan, S. Korea, Sep. 9-11, 2021.
  • S. Appakaya, E. Sheybani, and R. Sankar, Novel Unsupervised Feature Extraction Protocol using Autoencoders for Connected Speech: Application in Parkinson's Disease Classification' The 20thAnnual Wireless Telecommunications Symposium (WTS), San Francisco, CA, April 21-23, 2021.
  • S. Appakaya, R. Sankar, and I. Ra, Classifier Comparison for Two Distinct Applications Using Same Data, The 9th International Conference on Smart Media and Applications (SMA), Jeju Island, S. Korea, Sep. 17-19, 2020.
  • H. Srivastava, I. Ra, and R. Sankar, Cooperative Influence Learning, The 9th International Conference on Smart Media and Applications (SMA), Jeju Island, S. Korea, Sep. 17-19, 2020.
  • S. A. Khoshnevis, I. Ra, and R. Sankar, Early Stage Diagnosis of Parkinson鈥檚 Disease Using HOS Features of EEG Signals, The 9th International Conference on Smart Media and Applications (SMA), Jeju Island, S.Korea, Sep. 17-19, 2020.
  • S. Appakaya and R. Sankar, Parkinson's Disease Classification using Pitch Synchronous Speech Segments and Fine Gaussian Kernels based SVM, IEEE 42nd Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), Montreal, Quebec, Canada, July 20-24, 2020.
  • S. A. Khoshnevis, E. Sheybani, and R. Sankar, 'Compression of Gait IMU signals Using Sensor Fusion and Compressive Sensing, The 19thAnnual Wireless Telecommunications Symposium (WTS), Washington, DC, USA, April 22-24, 2020.
  • S. Appakaya, S. A. Khoshnevis, E. Sheybani, and R. Sankar, 'A Novel Pitch Cycle Detection Algorithm for Telemonitoring Applications, The 19thAnnual Wireless Telecommunications Symposium (WTS), Washington, DC, USA, April 22-24, 2020.
  • S. A. Khoshnevis, I. Ra, and R. Sankar, Compression of Background Electroencephalography Signals using Empirical Mode Decomposition and Compressive Sensing, The 8th International Conference on Smart Media and Applications (SMA), Guam, Dec. 6-7, 2019, pp. 64-67.
  • S. Sobolewski, W. L. Adam, Jr., and R. Sankar, Complex Source Detection and Threat Simulation in an Ambiguous Era, Electronic Warfare Europe 2019, Stockholm, Sweden, May 13-15, 2019.
  • S. Appakaya and R. Sankar, Classification of Parkinson鈥檚 Disease Using Pitch Synchronous Analysis, IEEE 40th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, July 17-21, 2018.
  • V. A. B. K. Vadali, S. Pandey, P. C. Adithya, and R. Sankar, Fetal Phonocardiogram Decomposition Framework, IEEE SoutheastCon, St. Petersburg, FL, April 19-22, 2018.
  • S. Appakaya and R. Sankar, Effectiveness of Speech Analysis in Classification of Neurodegenerative Diseases: A Study on Parkinson鈥檚 Disease, IEEE SoutheastCon, St. Petersburg, FL, April 19-22, 2018.
  • P. C. Adithya, S. R. Pandey, R. Sankar, S. Hart, and W. A. Moreno, Cluster Analysis Framework for Novel Acoustic Catheter Stethoscope, IEEE-NIH 2017 Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies (HI-POCT), Bethesda, MD, November 6-8, 2017, pp. 22-25.
  • P. C. Adithya, R. Sankar, W. A. Moreno, and S. Hart, A Novel Acoustic Catheter Stethoscope Based Acquisition and Signal Processing Framework to Extract Multiple Vital Bio Signals, IEEE 39th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC), Jeju Island, South Korea, July 11-15, 2017, pp. 1336-1339.
  • S. V. Perumal and R. Sankar, Gait Monitoring System for Patients with Parkinson鈥檚 Disease Using Wearable Sensors, IEEE-NIH 2016 Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies (HI-POCT), Cancun, Mexico, November 9-11, 2016, pp. 21-24.

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Honors and Awards

  • Fulbright Scholar, Fulbright-Brazil Scientific Mobility Program, 2015-16; conducted collaborative research on advanced wearable sensors and technology for improving healthcare
    • As Fulbright research scholar - Brazil Scientific Mobility program, engaged in collaborative research in 鈥淲earable Sensors and Technologies for Advancing Healthcare鈥� and promoted academic cooperative partnerships with Universidade de Sao Paulo (USP) at S茫o Carlos School of Engineering (EESC-USP) and Universidade Estadual De Campinas (UNICAMP) at Campinas, Brazil. Responsible for leading USF to MOU agreement with University of Campinas, 2016.
  • Outstanding Faculty Award, USF, 2016.
  • IEEE EMBS Distinguished Lecturer, 2014-16; Delivered 15+ invited, keynote lectures in USA, Mexico, Brazil, Argentina, Turkey, and India.
    As an invited plenary and keynote speaker and as a Distinguished Lecturer for the IEEE Society, delivered numerous (more than 50) plenary and keynote or invited lectures at conferences and academic/research institutions both nationally in US and internationally, including Argentina, Brazil, India, Japan, Korea, Mexico, and Turkey.
    • Keynote Speaker, The 8th Seminar on Electronics and Advanced Design, IEEE Puebla Chapter & the Instituto Nacional de Astrof脥sica, 脫ptica y Electr贸nica (INAOE), Puebla, Mexico, Sep. 21-23, 2016.
    • Keynote Speaker I-Workshop, IEEE Centro-Norte Section, University of Brasilia, Jun. 24-25, 2016.
    • Invited EMBS Distinguished Speaker, EMBS Turkey Conference, Istanbul, Turkey, May 7-8, 2016.
    • Plenary Keynote Speaker at the XX Argentinean Congress of Bioengineering (SABI 2015), San Nicolas de Los Arroyos, Buenos Aires, Argentina, Oct. 28-30, 2015.
    • Keynote Speaker at the First IEEE International Conference on Circuits, Control, Communication and Computing (I4C), Bangalore, India, November 21-22, 2014.
  • Editorial Board Member, International Journal of Control, Automation, and Systems (IJCAS), Institute of Control, Robotics, and Systems and Korean Institute of Electrical Engineers, 2008-2013.
  • Editorial Board Member, Journal of Electrical and Computer Engineering, Hindawi Publishing Corp., 2009-.
  • Associate Editor, IEEE Communications Surveys and Tutorials (Signal Processing Area), 2003-09.
  • Guest Associate Editor, IEEE Trans. on Information Technology and Biomedicine (T-ITB), 2002-03.
  • Theodore and Venette Askounes-Ashford Distinguished Scholar Award, USF, 2007.
  • Invitation Research Fellow, Japanese Society for Promotion of Science (JSPS), Mar-Apr 2000; conducted collaborative research on wireless communications at Shinshu University, Japan. Nominated by the National Science Foundation (NSF) for the Invitation Research Fellowship Award by the Japanese Society for Promotion of Science (JSPS), 1999-2000.
  • Following that, held a visiting position at the University of Melbourne, Australia, 2000.
  • Research Associate, Air Force Office of Scientific Research (AFOSR), Rome Laboratory, NY, 1997.
  • Outstanding Contributions in Research Award (for the best paper published in a technical journal), Southeastern Section ASEE, April 1997.
  • IEEE Florida Council Outstanding Engineering Educator Award, 1996.
  • Recognition and Appreciation Award for 35 Years of Continuous Service to USF, 2020.
  • Actively engaged with several Korean academic institutions to establish strong cooperative relationships; Led USF to MOU agreements with two Korean universities, Kunsan National University and Kangnam University. Hosted seven visiting research scholars/professors from Korean universities at the iCONS research lab, USF to conduct collaborative research. Besides South Korea, collaborative partnerships and invited lecture tours have also been undertaken in Brazil, Japan and India.

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