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Dinesh Bhatia

Dinesh Bhatia

Professor - Electrical and Computer Engineering
 
972-883-2386
ECN4926
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Professional Preparation

Ph.D. - Computer Science
University of Texas at Dallas - 1990
M.S. - Computer Science
University of Texas at Dallas - 1987
B.E. - Electrical Engineering
Regional Engineering College - 1985

Research Areas

Research Interests and Specialization
Architecture and Computer-Aided Design for Field Programmable Gate Arrays (FPGAs), Reconfigurable Computing, Custom Computing Systems, and domain-specific architectures supporting AI Systems.

Medical Electronics, Personal Medical Devices, AI in Medicine

Power Electronics, Embedded Systems.


 Others:

  •  All aspects of reconfigurable and adaptive computing architecture and CAD for field programmable gate arrays (FPGAs)
  •  Physical design automation of VLSI Systems
  •  Biomedical electronics and systems
  •  Medical devices
  •  Natural energy scavenging
  •  Applications of wireless sensor networks.
Teaching Interests
  •  Physical design automation of VLSI systems,
  •  Digital Logic, Switching theory,
  •  Reconfigurable computing,
  •  Introduction to Engineering and Contemporary topics in Engineering
  •  VLSI systems,
  •  Data structures and algorithms,
  •  Microsystems design,
  •  VLSI architecture,
  •  Combinatorial optimization, Graph theory and algorithms.

Publications

Application of Machine Learning in FPGA EDA Tool Development 2023 - Journal Article
Machine learning based fast and accurate High Level Synthesis design space exploration: From graph to synthesis 2023 - Journal Article
Digital Pulsewidth Modulation (DPWM) Using Direct Digital Synthesis 2022 - Journal Article
Robust Estimation of FPGA Resources and Performance from CNN Models 2022 - Conference Paper
Predicting Post-Route Quality of Results Estimates for HLS Designs using Machine Learning 2022 - Conference Paper
PPA Based CNN Architecture Explorer 2022 - Conference Paper
MLSBench: A Benchmark Set for Machine Learning based FPGA HLS Design Flows 2022 - Conference Paper
Congestion prediction in fpga using regression based learning methods 2021 - Journal Article

Awards

Circuits and Systems Society Distinguished Lecturer. - IEEE [2007]
William H. Middendorf Award for Research Excellence - ECECS Department, University of Cincinnati [1995]

Appointments

Department Head
Electrical and Computer Engineering [2024–Present]
Professor
University of Texas at Dallas [2010–Present]
Program Head
University of Texas at Dallas [2004–2006]
Erik Jonsson School of Engineering and Computer Science
Associate Professor
University of Texas at Dallas [2000–2010]
Associate Professor
University of Cincinnati [1997–2000]
Director
University of Cincinnati [1991–2000]
Assistant Professor
University of Cincinnati [1991–1997]
Visiting Assistant Professor
Southern Methodist University [1990–1991]

Additional Information

Awards and Honors
IEEE Circuits and Systems Society Distinguished Lecturer, 2007-08.
Honorable Mention for Ph.D. Dissertation Award, EE Department, 2004-2005,
Shankar Balachandaran, Advisee.
Associate Editor, IEEE Transactions on Computers, July 1999-2003.
Invited Tutorial Speaker, Physical Design of VLSI Systems, IEEE Design and Test
Workshop, Delhi, India, August 1999.
Best MS Thesis Award, ECE Department, 1998-99. Karthik Gajjalapurna, Advisee.
Embedded Tutorial Speaker, Reconfigurable Computing, IEEE

News Articles

Event to Explore the Fast-Evolving World of Medical Devices
Event to Explore the Fast-Evolving World of Medical Devices The University of Texas at Dallas will host the first Texas Medical Device Symposium on Friday, Nov. 2.

The symposium provides an opportunity for the public to hear the latest findings in the field from leading academic researchers, clinicians and representatives of companies making the devices. The symposium also includes an opportunity for researchers to learn more about the federal process for getting a medical device approved for use.