Vision and Goals

The vision of my research is to advance scientific discovery and technology in computer engineering, electrical engineering, and computer science; while transforming the knowledge into real-life applications to create a broad, constructive impact to the people and societies in the 21st century.

Research Interests

My research interests are at the interdisciplinary confluence of computer engineering, computer science, electrical engineering, neural engineering, biomedical engineering, and medicine. The center of my current research efforts focus on the following thrusts:

(1) Developing energy-efficient, high-performance, self-adaptive, reliable, secure, embedded and bio-implantable computing technology via algorithm-software-hardware co-design.

(2) Integrating this cutting-edge computing technology into real-life biomedical applications of highest impact.

The research efforts of my Center for Advanced Computing Technology involve both developing fundamental science and implementing practical engineering solutions in both system hardware and software to pioneer assistive biomedical devices.

This research thrust focuses on the areas of computer system architecture, processor microarchitecture, and compiler optimization with emphasis on low-power, reliable, secure, high-performance embedded systems, specialized processors, and System-on-a-Chip (SoC) with applications in health care, science, and engineering.

Topics of interests include but are not limited to: low-power embedded system designs and compilation, application-specific architectures, reconfigurable architectures, hardware/software CO-designs, energy-efficient architectures for low-power sensor networks; multi-processor (MP), multi-core, and multi-threaded (MT) designs; low-power very large-scale integrated circuits (VLSI), architectures and designs for next generation multimedia, high-definition graphics and display hardware; real-time computing (RTC) systems, memory hierarchies, storage systems, I/O subsystems, interconnection networks, network-on-a-chip (NoC); parallelism discovery, parallel processing and programming models; algorithms metrics, and tools for performance measurement and tuning, simulation, benchmarking; programming language semantics, design, and implementation for futuristic and specialized architectures.

Thrust 2: Biomedical Engineering, Neural Engineering, and Medicine

This research thrust focuses on the areas of bio-computing and implantable computing system for sensing, monitoring, and transmitting neurophysiological information.

Topics of interests include but are not limited to: engineering bio-computing system by co-designging hardware and software that serves as the "brain", or the central control of various neural sensors and actuators. The vision is to develop the next-generation computing platform capable of performing in vivo diagnosis, therapeutic interventions, and functional replacement. Current research focuses on developing autonomously reconfigurable and energy-efficient implantable chip with longer life span and superior reliability.

Click here to visit my web page at Neural Engineering in the McGowan Institute for Regenerative Medicine.

Research Sponsors

Thanks for the generous support from the following federal and industrial sponsors.

Students

Click here to see the list of students that I am currently supervising. Click here to see how to join my research group.

Publications

Visit my publications link for a complete list of my publications on professional journals, conference proceedings, and workshops papers.

Doctoral Dissertation

Thesis: Application Specific Instruction Set Synthesis Frameworks (Abstract, Full)
Thesis Advisors: Professor Trevor Mudge and Professor Gary Tyson

Dissertation Committee

• Professor Trevor Mudge (Bredt Family Professor of Engineering), Chair
• Associate Professor Gary S. Tyson, Co-Chair
  
• Professor Marios C. Papaefthymiou
  
• Associate Professor Scott A. Mahlke
  
• Associate Professor Dennis Sylvester
  

Dissertation Summery:

• Pioneered an original application-specific processor framework for embedded systems
• Established a novel instruction set synthesis paradigm
• Developed efficient low-power microarchitecture
• Explored effective compiler optimization techniques for specialized on-chip memories