• Switches for UTEP Distributed Computing Lab, Cisco Systems (Higher Education Equipment Grant), PIs: Williams (Lead), Nava, Pierluissi, Dec 2003, $20,305.
• Office of Sponsored Projects Incentive Award, 1 year, Fall 2003, $1000 awarded.
• UTEP Distributed Computing Lab: Creation of a Pipeline for Minority Particpation in Research, NSF Institutional Infrastructure for Minority Institutions (CISE/EIA II-MI), PIs: Nava (Lead), Williams, Pierluissi, September 2003-August 2006, $750,514.
• FPGA-Based Laboratory for Teaching and Research in Digital Design, Xilinx University Program, Principal Investigator, August 2003, $31,806 (Xilinx Equipment Grant).
• Model-based Characterization and Classification of Respiratory Diseases Prevalent Among US-Mexico Border Residents, Tobacco Settlement, PIs: Nava (Lead), Nazeran, Diong, Solis, Ortiz, and Menendez, March 2003-August 2003, $20,050.
• A Virtual Development Center Site at The University of Texas at El Paso, Institute of Women in Technology, Principal Investigator, Sept 2002, $120,309 (HP Equipment Grant).
• Investigation of Neuro-Fuzzy Hybrid Systems and Their Applications, NASA Faculty Award for Research, Principal Investigator, Sept 1999-May 2003, $289,000. Office of Sponsored Projects Incentive Award, 1 year, Fall 1999, $1000 awarded.
• Hybrid Nonlinear Computation Models: Fusing the Benefits of Neural Networks and Fuzzy Systems, Forrest and Henrietta Lewis Endowed Professorship, University of Texas at El Paso, 1998-1999, $12,000.
• Evaluation and Analysis of A Neuro-Fuzzy Classifier for Voice Recognition, University Research Institute, University of Texas at El Paso, Principal Investigator, 1996-1997, $3,543.
• Cascadable Microcomputer Module Research, U.S. Army Research Contract, New Mexico State University, team member, 1981-1982.

• Attigadda, Prasanna, MSEE thesis December 2003
  " Hardware Implementation of Rijndael Encryption Algororithm. "
• Ameet Chavan, MSEE thesis August 2003
  " Design and Test of Reconfigurable Data Path Processor using Xilinx Development Tools. "
• Jovan Saenz, MSEE thesis August 2003
  " FPGA Implementation of an Interval-Based Neural Network. "
• Rex Velasquez, M.S.E.E., thesis, December 2002
  " VHDL Implementation of MCAP Modules for Reconfigurable Hardware Processors. "
• Deepthi Ratnakar, M.S.E.E., thesis, November 2002
  " An Investigation of an Analog Neural Network as a Function Approximator. "
• Janette Cano, M.S.E.E. thesis, May 2002
  " A Fuzzy Method for Automatic Generation of Membership Functions. "
• Raul Cruz, M.S. thesis, May 2002
  " On Markov Monte Carlo Methods for Neural Networks. "
• K. Kawaguchi, M.S.E.E. thesis, July 2000
  " A Threaded Parallel Implementation of Backpropagation in an Artificial Neural Network Simulation. "
• Y. Kamat, M.S.E.E. thesis, December 2000
  " An Assembler for a Microcoded CPU. "
• Yvonne Lucero, M.S.E.E. thesis, December 1999
  " A Method for Automatic Membership Function Generation. "
• Shu-Fai Au, M.S.E.E. thesis, April 1998
  " Letter Recognition with a Fuzzy-Logic-Controlled Neural Network. "
• G. Velasquez, M.S.E.E. thesis, December 1997
  " A Distributed Approach to Neural Network Simulation. "
• Mita Moorthy, M.S.E.E. tech. report, May 1997
  " A Model for PLA Fault Analysis. "
• Yihong Zhou, M.S.E.E. tech. report, May 1997
  " A Fuzzy System for Recognition of 11 Vowel Sounds. "

Research Interests:

• Hybrid Nonlinear Computation Models: Fusing the Benefits of Neural Networks and Fuzzy Systems (currently working on this project)
  This is basically a continuation of a body of work begun during my graduate studies. Previous work has established that one particular fuzzy neural network (FNN) model outperforms a standard neural network (ANN) by 33% to 49% on the task of vowel recognition. The FNN is a neural network that processes fuzzy numbers. This line of investigation seeks to find other ways to incorporate fuzzy techniques into neural network operation. This work has already generated two conference papers.
• Automatic Generation of Membership Functions ( currently working on this project )
  In this effort, we are studying current membership function generation techniques and exploring new methods that will yield more accurate results. The resulting code will be used as a preprocessing function to existing fuzzy neural network simulations. I am supervising research and C coding process.
• Fuzzy Neural Network Simulation in a Parallel Distributed Environment (currently working on this project)
  This research involves simulation of neural networks considering each process as an object. In this manner, we can distribute computation over several machines and obtain some statistics on the overall performance of the simulation. A comparison to two different distributed computing simulations, written previously, will be performed.