Publications

Journals

  1. A. Ravindran, "Internet-of-Things Edge Computing Systems for Streaming Video Analytics: Trails Behind and the Paths Ahead", IoT 2023, 4(4), 486-513.
  2. B.R. Ardabili, A.D. Pazho, G.A. Noghre, C. Neff, S.D. Bhaskararayuni, A. Ravindran, S. Reid, H. Tabkhi, "Understanding Policy and Technical Aspects of AI-Enabled Smart Video Surveillance to Address Public Safety". Computational Urban Science, 2023 May 18;3(1):21.
  3. A. George, A. Ravindran, M. Mendieta, H. Tabkhi, “Mez: An Adaptive Messaging System for Latency-Sensitive Multi-Camera Machine Vision at the IoT Edge", IEEE Access, Vol. 9, pp. 21457-21473, 2021.
  4. K. Datta, A. Mukherjee, G. Cao, R. Tenneti, V. Lakshmi, A. Ravindran, and B. Joshi, “CASPER: Embedding Power Estimation and Hardware-Controlled Power Management in a Cycle-Accurate Micro-Architecture Simulation Platform for Many-Core Multi-Threading Heterogeneous Processors”, Journal of Low Power Electronics, 2012, 2(1), 30-68.
  5. S. Datta, B. Joshi, A. Mukherjee, and A. Ravindran, “Efficient Testing and Diagnosis of Digital Microfluidic Biochips,” ACM Journal on Emerging Technologies in Computing Systems, vol. 5, no. 2, 2009.
  6. R. Karanam, A. Ravindran, and A. Mukherjee, “A Stream Chip-multiprocessor for Bioinformatics”, ACM SIGARCH Computer Architecture News, Volume 36, Issue 2, pp. 2–9, May 2008.
  7. S. Tucker, A. Ravindran, C. Wichman, and A. Mukherjee, "Design Techniques for Micro-Power Algorithmic Analog-to-Digital Converters", Journal of Low Power Electronics, Vol. 3, pp. 1–10, April 2007.
  8. D. Davids, S. Datta, A. Mukherjee, B. Joshi, and A. Ravindran, "Multiple Fault Diagnosis in Digital Microfluidic Biochips", ACM Journal on Emerging Technologies in Computing Systems, vol. 2, no. 4, pp. 1–15, October 2006.
  9. S. Mohan, A. Ravindran, D. Binkley, and A. Mukherjee, "Power Optimized Design of CMOS Programmable Gain Amplifiers”, Journal of Low Power Electronics, Vol. 2, No. 2, pp. 259–270, August 2006.
  10. K. Datta, A. Mukherjee, and A. Ravindran, "Automated Design Flow for Diode-based Nanofabrics", ACM Journal of Emerging Technologies in Computing Systems, vol. 2, no. 3, pp. 219–241, July 2006.
  11. R. Karanam, A. Ravindran, A. Mukherjee, C. Gibas, and A. Wilkison, “Using FPGA-based Hybrid Computers for Bioinformatics Applications”, XCell Journal, Issue 58, Third Quarter, 2006.
  12. A. Ravindran, E. Vidal, S. Yoo, K. Ramarao, and M. Ismail, ”A Differential Current Mode Variable Gain Amplifier with a Digital dB-linear Gain Control”, Journal of Analog Integrated Circuits and Signal Processing, Kluwer Academic Publishers, Vol. 38, Issue 2–3, pp. 161–174, February 2004.
  13. H. Elwan, A. Ravindran, and M. Ismail, “A CMOS Low Power Baseband Chain for a GSM/DECT Multi-standard Receiver”, IEE Proceedings: Circuits, Devices, and Systems, Vol. 149, Issue 5, pp. 337–347, Oct. 2002.
  14. A. Ravindran, K. Ramarao, E. Vidal, and M. Ismail, “Compact Low-voltage Four Quadrant CMOS Current Multiplier”, Electronics Letters, Volume 37, Issue 24, 22 Nov. 2001, pp. 1427–1428.

Conferences and Workshops

  1. Siddhath Jain, Kunal Jain, Arun Ravindran, and Suresh Purini, "Seer: A Framework for Optimizing Traffic Camera Placement and Deep Learning Inference at the Edge for Vehicle Path Reconstruction", ACM/IEEE Symposium on Edge Computing, December 4-7, 2024, Rome, Italy.
  2. Owen Heckmann, and Arun Ravindran, "Evaluating Kubernetes at the Edge for Fault Tolerant Multi-Camera Computer Vision Applications", The 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, Research Poster, May 2023.
  3. Samantha Luu, Arun Ravindran, Armin Danesh Pazho, Hamed Tabkhi, “VEI: A Multicloud Edge Gateway for Computer Vision in IoT”, Accepted for publication at The 1ST Workshop On Middleware For The Edge, Collocated with ACM/IFIP/USENIX Middleware 2022, Québec, Canada, 7-11 November, 2022.
  4. Anjus George, and Arun Ravindran, “Scalable Approximate Computing Techniques for Latency and Bandwidth Constrained IoT Edge”, Best Paper Award, EAI International Conference on Intelligent Edge Processing in the IoT Era, December 2020.
  5. Anjus George, and Arun Ravindran, “Distributed Middleware for Edge Vision Systems”, IEEE HONET-ICT, October 2019.
  6. Anjus George, and Arun Ravindran, “Latency Control for Distributed Machine Vision at the Edge through Approximate Computing”, Best Paper Award, International Conference on Edge Computing, San Diego, June 2019.
  7. Matias Mendieta, Christopher Neff, Daniel Lingerfelt, Christopher Beam, Anjus George, Sam Rogers, Arun Ravindran, and Hamed Tabkhi, “A Novel Application/Infrastructure Co-design Approach for Real-time Edge Video Analytics”, SoutheastCon, April 2019.
  8. Arun Ravindran, and Anjus George, “An Edge Datastore for Latency-Critical Distributed Machine Vision Applications”, USENIX Workshop on Hot Topics in Edge Computing, July 2018, Boston.
  9. Yang Deng, Arun Ravindran, Tao Han, “Poster: Edge Datastore for Distributed Vision Analytics”, Symposium on Edge Computing, San Jose, October 2017.
  10. Arun Ravindran, Tyrone Vincent, “Thrifty: A Machine Learning Based Feedforward-Feedback Optimal Control Runtime System for Energy-Efficient Latency-Critical Systems”, Workshop on Feedback Computing, Columbus, OH, July 2017.
  11. D. Mehta, A. Ravindran, B. Joshi, and S. Kamalasadan, “Graph Theory Based Online Optimal Power Flow Control of Power Grid with Distributed Flexible AC Transmission Systems (D-FACTS) Devices”, North American Power Symposium, Charlotte, October 2015.
  12. G. Cao and A. Ravindran, “Energy Efficient Soft Real-Time Computing through Cross-Layer Predictive Control”, USENIX Workshop on Feedback Computing, June 2014.
  13. G. Cao, A. Ravindran, S. Kamalasadan, B. Joshi, and A. Mukherjee “A Cross-Stack Predictive Control Framework for Multimedia Applications”, IEEE International Symposium on Multimedia, December 2013.
  14. C. Zhang, and A. Ravindran, “A Statistical Machine Learning Based Modeling and Exploration Framework for Run-time Cross-Stack Energy Optimization”, IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), April 2013.
  15. R. Mitra, B. Joshi, A. Ravindran, A. Mukherjee, and R. Adams, “Performance Modeling of Shared Memory Multiple Issue Multicore Machines”, 41st International Conference on Parallel Processing Workshops, Pittsburgh, September 10-13, 2012.
  16. A. Arunkumar, A. Panday, B. Joshi, A. Ravindran, and H. Zaveri., “Estimating Correlation for a Real-time Measure of Connectivity”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, August 28 – September 1, 2012.
  17. C. Zhang, A. Ravindran, K. Datta, A. Mukherjee, and B. Joshi, “A Machine Learning Approach to Modeling Power and Performance of Chip Multiprocessors”, IEEE International Conference on Computer Design, October 2011.
  18. R. Mitra, B. Joshi, A. Ravindran, R. Adams, and A. Mukherjee, “Performance Modeling of Parallel Magnetostatic Wave Calculations on Shared Memory Multicore,” IEEE SoutheastCon, March 2010.
  19. A. Panday, B. Joshi, A. Ravindran, J. Byun, and H. Zaveri, “Study of Data Locality for Real-Time Biomedical Signal Processing of Streaming Data on Cell Broadband Engine,” IEEE SoutheastCon, March 2010.
  20. R. Mitra, B. Joshi, R. Adams, A. Ravindran, and A. Mukherjee, “Modeling and Performance Analysis of Parallel Magnetostatic Wave Calculations on Multicore,” SC2009, November 2009.
  21. J. Byun, K. Datta, A. Ravindran, A. Mukherjee, B. Joshi, and D. Chassin, “A Parallel Power Flow Solver Based on Gauss-Seidel Method on the IBM Cell/B.E.,” SC2009, November 2009.
  22. A. Ravindran, P. Tolley, and A. Mukherjee, “Introducing Reconfigurable Computing in the Undergraduate Computer Engineering Curriculum”, ASEE Annual Conference and Exposition, June 2009.
  23. J. Byun, A. Ravindran, A. Mukherjee, B. Joshi, and D. Chassin, “Accelerating the Gauss-Seidel Power Flow Solver on a High Performance Reconfigurable Computer”, IEEE Symposium on Field Programmable Custom Computing Machines (FCCM ’09), April 2009.
  24. A. Ravindran, A. Mukherjee, and P. Tolley, “An Undergraduate Computer Engineering Educational Framework for using Field Programmable Gate Arrays as Efficient Hardware Accelerators”, Conference of Course, Curriculum and Laboratory Improvement Program, August 14-15, 2008.
  25. Daniel Davids, Bharat Joshi, Arindam Mukherjee, and Arun Ravindran, “A Fault Detection and Diagnosis Technique for Digital Microfluidic Biochips,” IEEE International Mixed-Signals, Sensors, and Systems Test Workshop, June 18-20, 2008.
  26. R. Karanam, A. Ravindran, and A. Mukherjee, “A Stream Chip Multiprocessor for Bioinformatics”, Workshop on Design, Analysis and Simulation of Chip Multiprocessors, December 2007.
  27. Bharat Joshi, Arindam Mukherjee, and Arun Ravindran, “Highly Dependable SCADA Systems,” National Workshop on Beyond SCADA: Networked Embedded Control for Critical Physical Systems, November 2006.
  28. J. Byun, R. Karanam, A. Ravindran, A. Mukherjee, and B. Joshi, "Fault Tolerant Techniques for I/O Bound High Performance Systolic Arrays on SRAM FPGAs", MAPLD, September 2006.
  29. K. Datta, J. Bolano, O. Eruotor, Y. Nerie, A. Mukherjee, and A. Ravindran, “The Wireless Sensor Tissue: A Network of Wireless Sensor Nodes using Cellular Mechanisms for Autonomous Distributed Fault Tolerance”, North Atlantic Test Workshop May 10-12, 2006.
  30. Kushal Datta, Ravi Kiran Karanam, Jong-Ho Byun, Arindam Mukherjee, Bharat Joshi, and Arun Ravindran, “A Biology-inspired Distributed Fault Tolerant Design Methodology for Highly Available Systems with Efficient Redundancy Insertion Technique,” North Atlantic Test Workshop, May 10-12, 2006.
  31. A. Ravindran and S. Mohan, “A Low Input Impedance Fully Differential CMOS Transresistance Amplifier using Cascode Regulation”, IEEE CICC, September 2005.
  32. C. Wichman, S. Tucker, and A. Ravindran, “A Micropower OTA for Digitally Calibrated Algorithmic ADCs”, 48th IEEE MWSCAS, August 2005.
  33. J. Bolano, J. Johnson, A. Wood, A. Mukherjee, H. Hilger, and A. Ravindran, “Real Time Wireless Remote Monitoring of Methane Flux in Landfills”, INCEED, July 2005.
  34. A. Yamazaki, A. Ravindran, O. Akgun, and M. Ismail, "An Active-RC Reconfigurable Lowpass-polyphase Tow-Thomas Biquad Filter", 47th IEEE MWSCAS, July 2004.
  35. A. Savla, A. Ravindran, and J. Leonard, “A Novel Queuing Architecture for Background Calibration in Pipelined ADCs”, IEEE ISCAS, May 2004.
  36. A. Ravindran, A. Savla, and J. Leonard, “Digital Error Correction and Calibration of Non-linearities in a Pipelined ADC”, IEEE ISCAS, May 2004.
  37. Y. Yoo, A. Ravindran, and M. Ismail, "A Low Voltage CMOS Transresistance-based Variable Gain Amplifier", IEEE ISCAS, May 2004.
  38. A. Savla, A. Ravindran, and M. Ismail, "A Reconfigurable Low-IF/Zero-IF Receiver Architecture for Multi-Standard Wide Area Wireless Networks", IEEE ICECS 2003, pp. 934-937, December 2003.
  39. A. Savla, A. Ravindran, J. Leonard, and M. Ismail, “System Analysis of a Multi-standard Wireless Direct Conversion Receiver”, 45th IEEE MWSCAS Conference, August 2002.
  40. A. Ravindran, A. Savla, I. Younus, and M. Ismail, “A 0.8V CMOS Filter based on a Novel Low Voltage Operational Transresistance Amplifier”, 45th IEEE MWSCAS, August 2002.
  41. A. Savla, A. Ravindran, and M. Ismail, “A Reconfigurable Low Power Pipeline ADC for Multi-standard Wireless Applications”, IEE-Japan, Analog VLSI Workshop, September 2002.
  42. A. Ravindran, E. Vidal, and M. Ismail, “A Digitally Generated Exponential Function for dB-linear CMOS Variable Gain Amplifiers”, 14th International Conference on Digital Signal Processing, July 2002.