From: bharat@cs.uiuc.edu (R. Bharat Rao)
Subject: PhD EECS/AI/Modeling Entry level Research/Development
Reply-To: bharat@cs.uiuc.edu
Organization: University of Illinois, Dept. of Comp. Sci., Urbana, IL
Date: Wed, 12 Aug 1992 15:41:41 GMT



                         R. BHARAT RAO
                         _____________

      Office                              Residence
Beckman Institute                   2060D South Orchard Street 
405 North Mathews Street            Urbana, IL 61801 
Urbana, IL 61801                    (217) 337--6498 
(217) 244--1263, bharat@cs.uiuc.edu 


                          Objective

I would like to become an active member of a development community
that encourages cross-disciplinary activities leading to applications
of empirical modeling techniques to real-world problems.

 
                        Academic Degrees
  
Doctor of Philosophy (Ph.D.), August 1992 (expected date),
Electrical and Computer Engineering,, University of Illinois at Urbana,
      with emphasis on Artificial Intelligence (machine learning)
      developing machine learning and statistical algorithms to learn
      models to support to engineering design and optimization.

Master of Science (M.S.), February 1989, in Electrical and Computer
Engineering, University of Illinois at Urbana--Champaign, with
emphasis on Artificial Intelligence (expert systems).

Bachelor of Technology (B.Tech.), 1985, Electronics Engineering,
Indian Institute of Technology, Madras, India.

                        Technical Interests

Machine Learning           Modeling             Artificial Intelligence
Knowledge-based Systems    Statistics           Design/Planning
Empirical Discovery        CAD/CAM              Expert Systems


                        Technical Experience

January 1989 -- Present
  Research Assistant to Professor Stephen C. Lu, Artificial Intelligence
  (AI) Group, Beckman Institute for Advanced Science and Technology,
  University of Illinois.  Develop machine learning algorithms and
  integrate them with statistical and optimization techniques to solve
  problems in engineering modeling and design (domains: design of diesel
  engine combustion chambers and VLSI circuit design).

January 1986 -- August 1989 
  Research Assistant to Professor Robert E. Stepp, Department of
  Computer Science, AI Group, Beckman Institute, University of Illinois.
  Conducted research in the area of expert systems (OMAR), conceptual
  clustering, application of simulated annealing to machine learning,
  and language development for knowledge representation for
  communication between AI programs (SAPC). 

August 1985 -- May 1991
  At various times, was a Teaching Assistant at the Department of
  Electrical and Computer Engineering, University of Illinois.

            Awards and Professional Societies

Best Student Paper, ``KEDS: A Knowledge-based Equation Discovery
System for Engineering Problems,'' in CAIA-92, The Eighth IEEE
Conference on Artificial Intelligence for Applications, 1992 ($1500
award sponsored by IBM).

Avery Brundage Scholarship, 1989-1990, awarded by the University of
Illinois to students that are deemed ``outstanding athletes and
exceptional scholars.''

``List of Teachers ranked as Excellent by their Students,'' University
of Illinois, Fall 1990, Spring 1991, Fall 1991 (outstanding ranking).

Member, American Association for Artificial Intelligence.


                  Ph.D. Research

Title: INVERSE ENGINEERING: Learning Engineering Models to Support
       Synthesis Activities in Engineering Decision Making

Advisor: Dr. Stephen C. Lu, Associate Professor, Mechanical Engineering

Abstract: Current methods of doing synthesis tasks in engineering
  design involve the iterative use of computer-based analysis simulators
  in a generate-and-test fashion.  This thesis proposes a methodology
  called {\em inverse engineering}, to learn bi-directional models to
  directly support synthesis activities in engineering design, and
  greatly reduce design iterations.  New learning techniques, integrated
  with traditional statistical techniques, are used to process
  engineering data sets to learn comprehensible analysis and synthesis
  models.  In addition, these models can provide decision-making support
  for other engineering scenarios, such as prediction, control,
  monitoring (analysis activities), optimization, design, and inversion
  (synthesis activities).  This methodology has been applied to support
  early product design of combustion chambers for diesel engines and for
  ``worst-case'' design of analog MOS circuits.

                  Publications

 1. R. B. Rao and S. C. Lu ``Learning Engineering Models with the
    Minimum Description Length Principle''.  (Appearing in) AAAI-92, The
    Tenth National Conference on Artificial Intelligence, 1992, (Also
    appears as Technical Report KBESRL-ML-92-001).

 2. R. B. Rao and S. C. Lu.  ``KEDS: A Knowledge-based Equation Discovery
    System for Engineering Problems,'' In Proceedings of the Eighth IEEE
    Conference on Artificial Intelligence for Applications}, 1992,
    (Also appears as Technical Report KBESRL-ML-91-004).

 3. R. B. Rao, S. C. Lu, and R. E. Stepp.  ``Knowledge-based Equation
    Discovery in Engineering Domains,'' In Proceedings of the Eighth
    International Workshop on Machine Learning, pages 630--634, 1991
    (Also appears as Technical Report KBESRL-ML-91-001).

 4. R. B. Rao and S. C. Lu, ``KEDS: A Knowledge-based Equation
    Discovery System for Learning in Engineering Domains,'' (to appear
    in) IEEE Expert. 

 5. R. B. Rao.  ``OMAR: An Object-oriented Multiple-worlds,
    Assumption-based Rulegroup Expert System Shell,'' Master's Thesis,
    Department of Electrical and Computer Engineering, University of
    Illinois, Urbana, IL, 1989.

                Technical Reports

 6. R. B. Rao and S. C. Lu, ``Inverse Engineering: A Framework for
    Building Synthesis Models to Support Engineering Design,'' In 
    Knowledge-Based Engineering Systems Research Laboratory (KBESRL)
    Annual Report, 1991, pages 73--80, 1991.

 7. R. Reinke, L. Holder, B. Whitehall, R. Stepp, and R. B. Rao.
    ``Annotated Predicate Calculus and S-Expression Annotated Predicate
    Calculus: Language Descriptions,'' Artificial Intelligence Research
    Group Report, University of Illinois, Urbana, Illinois, 1988.

 8. R. B. Rao.  ``Simulated Annealing: Theory and Application to
    Conceptual Clustering,'', Artificial Intelligence Research Group
    Report, University of Illinois, Urbana, IL, 1988.

 9. R. B. Rao and S. C. Lu, ``Inverse Engineering: A Methodology for
    Building Synthesis Models for Product and Process Design,'' In 
    KBESRL Annual Report, 1990, pages 214--230, 1990.

10. R. B. Rao, S. C. Lu, and R. E. Stepp, ``Inverse Engineering: A Machine
    Learning, Control Theory Approach,'' In KBESRL Annual Report, 1989,
    pages 101--109, 1989.


                  References

Dr. S. C. Lu, Associate Professor       
Mechanical and Industrial Engineering	 
University of Illinois			 
1206 W. Green, Urbana, IL 61801
(217) 333-6662		      	 
Electronic-mail: lu@kbesrl.me.uiuc.edu
					 
Dr. Srinivas Devadas, Associate Professor 
Electrical Engineering & Computer Science
Massachusetts Institute of Technology	 
Cambridge, MA 02139 
(617) 253-0454				 
Electronic-mail: devadas@cheetah.mit.edu

Dr. Jorma Rissanen 
IBM Almaden Research Center, K52 802 
650 Harry Road 
San Jose, CA 95120-6099 
(408) 927-1813 
Electronic-mail: rissanen@ibm.com

Dr. N. Ahuja, Professor
Electrical and Computer Engineering
University of Illinois
405 N. Mathews, Urbana, IL 61801 
(217) 333-1837
Electronic-mail: ahuja@uirvld.csl.uiuc.edu


                 Personal Statement of Professional Goals
                            R. Bharat Rao


--
R. Bharat Rao                          E-mail: bharat@cs.uiuc.edu 
AI Group, Beckman Institute for Advanced Science and Technology
405 N. Mathews, Urbana, IL 61801  (217)-244-1263 (O) 337-6498(H)
Electrical & Computer Engineering, University of Illinois, Urbana