MICHAEL ALEXANDER KOURITZIN

Department of Mathematical and Statistical Sciences     University of Alberta     Edmonton, Canada      T6G 2G1
Email: mkouritz@math.ualberta.ca       (780) 492-2704      Fax: (780) 492-6826

Professional Summary

Professor
University of Alberta, Mathematical Sciences
(July 2002 - present)

Associate Professor
University of Alberta, Mathematical Sciences
(July 1997 - June 2002)

• Lead Mathematics of Information Technology and Complex Systems (MITACS) national center of excellence Prediction in Interacting Systems''
• (PINTS).
• Taught undergraduate and graduate courses in Probability, Statistics, and Stochastic Equations.

Visiting Professor
Premier Class
Universite Paul Sabatier (France), Laboratoire de Statistique et Probabilities (February 2000)

• Conducted seminars in spatial stochastic process and filtering, collaborated on research.

IMA Industrial Fellow
University of Minnesota and Lockheed Martin
(Sept. 1995 - July 1997)

• Conducted NSF funded research in partial differential equations and averaging under supervision of Professor Avner Friedman.
• Investigated mathematical models and developed non-standard nonlinear filtering theory for air traffic control and military problems under sponsorship of Lockheed Martin.

Research Associate
Carleton University, Mathematics and Statistics
(Jan. 1994 - August 1995)

• Conducted Natural Science and Engineering Research Council (NSERC) of Canada funded research and interacted with the groups of Professors Donald Dawson and Miklos Csorgo.

Visiting Scientist
Universitat Freiburg, Institut fur Mathematische Stochastik
(Jan. - Dec. 1993)

• Conducted NSERC and Deutscher Akademischer Austauschdienst (DAAD) funded research under supervision of Professor Ernst Eberlein.

Assistant Professor
University of Waterloo, Electrical Eng.
(Jan. 1991 - Dec. 1992)

• Instructed seven half-year courses in Software Engineering, Control Theory, and Stochastic Processes for Engineers.
• Instruction included graduate, fourth year, and first year students with class sizes of up to 110.

Ph.D. awarded May 1991, Electrical Engineering, University of Waterloo, Advisor: Professor Andrew Heunis

Awards, Fellowships, and Grants

• Awarded 2001 PIMS Industrial Outreach Prize. (National Award, Sponsored by TD Bank).
• Project Leader for MITACS\_PINTS Grants. Current awards here are in excess of \$280,000/yr from NSERC, industry, and ASRA/PIMS.
• NSERC Research Grant and Industrial Grants holder (1997 - present).
• Institute for Mathematics and Its Applications Industrial Postdoctoral Fellowship (1995 and 1996)
• DAAD Study Visit Award (for Professors visiting Germany) (awarded 1993)
• NSERC Postdoctoral Fellowship (awarded 1992 and again in 1993)
• Contributed to NSERC collaborative grant proposal of Miklos Csorgo in Change Point Problems and Reliability - one of three collaborative grants awarded in the mathematical sciences during 1994.

Industrial Experience

• Currently working with five corporations under MITACS_PINTS
• Invented filtering algorithms being used by Lockheed Martin Corp. and Acoustic Positioning Research Inc.
• Two years experience in industry training and product development with Lockheed Martin.
• Two years engineering work experience during undergraduate degree.
Teaching
• Committed instructor, always striving to improve effectiveness and to challenge all students
• Taught undergraduate courses in Software Engineering, Control Theory, Probability and Statistics.
• Taught graduate courses in Probability, Statistics, and Stochastic Calculus.
• Have produced three major sets of class notes used as the main reference in: Software Engineering, Probability and Statistics, and Stochastic Calculus. Each are close to or in excess of 200 pages.
Service
• AMS Mathematics Reviewer for 2.5 years
• Organed a conference (with R.J. Elliott, T.G. Kurtz, and H. Long) in filtering for July 2002
• Organized session at the 2002 IMS Probability Symposium
• Co-organized (with T.G. Kurtz) a workshop in filtering at the University of Wisconsin-Madison in July 1999.
• Evaluated National Science Foundation and NSERC Research Grant proposals.
• Lead and manage a national centre of excellence
• Have contributed to and edited 6 bulletins and 4 phase reports for the centre. A total of about 300 pages.
• Have organized several meetings for the centre including a kick off'' attended by more than 50 scientists and students from various
• universities and industries.
• Served on various faculty and departmental committees including:
• Visiting committee, Hiring and programme advisory committees for Mathematical Finance, Advisory Examination in Statistics committee, NSERC postdoctoral candidate evaluation committee, Resource committee for MITACS\_PINTS.
Student Theses and Projects
• G.N. Nkabinde, On Almost Sure Convergence Rates for Recursive Stochastic Algorithms'', M.A.Sc. Thesis, 1992.
• M.K. Prefontaine, The Infinite Dimensional Exact Filter for a Mean-Reverting Financial Volatility Model'', M.Sc. Project, 2000.
Education
• Ph.D.  in Electrical Engineering, University of Waterloo, May 1991.
• Scholarships: NSERC Postgraduate Scholarship, Carl Pollock Scholarship, and Faculty of Engineering Scholarship.
• Nominated for the Alumni Gold Medal.
• B.A.Sc. Honours Bachelor of Applied Science, Electrical Eng., University of Waterloo, 1987
Research

1. M.A. Kouritzin and A.J. Heunis, Rates of convergence in a central limit theorem for stochastic processes defined by differential equations with a small parameter'', J. Multivariate Analysis, 43(1) (1992) pp.58--109.

2. M.A. Kouritzin, On almost sure bounds for the LMS algorithm'', IEEE Trans. Inform. Theory IT-40(2), (1994) pp.372--383.

3. M.A. Kouritzin and A.J. Heunis, A law of the iterated logarithm for stochastic processes defined by differential equations with a small
parameter'', Ann. Probab 22(2) (1994) pp. 659--679.

4. A.J. Heunis and M.A. Kouritzin, Strong convergence in the stochastic averaging principle'', Math. Anal. Appl. 187(1) (1994) pp.134--155.

5. M.A. Kouritzin, Inductive methods and rates of rth-mean convergence in adaptive filtering'', Stochastics and Stochastics Reports51 (1994) pp. 241--266.

6. M.A. Kouritzin, Parabolic equations with random coefficients'', The IMS Bulletin 24(5) (1995) pp.  462--463.

7. M.A. Kouritzin, Strong approximation for cross-covariances of linear variables with long-range dependence'', Stochastic Processes
Appl. 60 (1995) pp. 343--353.

8. M.A. Kouritzin, On the convergence of linear stochastic approximation procedures'', IEEE Trans. Inform. Theory IT-42(4) (1996) pp. 1305--1309.

9. M.A. Kouritzin, On the interrelation of almost sure invariance principles for certain stochastic adaptive algorithms and for partial sums of random variables'',  J. Theoretical Probability 9(4) (1996) pp. 811--840.

10. M.A. Kouritzin, Averaging for fundamental solutions of parabolic equations'', Journal of Differential Equations 136 (1997) pp. 35--75.

11. K. Kastella, M.A. Kouritzin, and A. Zatezalo, A nonlinear filter for altitude tracking'', October 1996 Proceedings of the Air Traffic Control Association  pp.1--5.

12. M.A. Kouritzin, Arbitrary order parabolic stochastic partial differential equations with general Hilbert-space-valued noise'',  The IMS Bulletin 26 (1997) pp. 322-323.

13. M.A. Kouritzin, Stochastic processes and perturbation problems defined by parabolic equations with a small parameter'', Nonlinear Analysis, Theory, Methods & Applications, 30, (1997) 4089--4099.

14. D.A. Dawson and M.A. Kouritzin, Invariance principles for parabolic equations with random coefficients'', Journal of Functional Analysis 149 (2) (1997) pp. 377-414.

15. M.A. Kouritzin, On exact filters for continuous signals with discrete observations'', IEEE Trans. on Auto Contr., AC-43 (1998) pp. 708--715.

16. M.A. Kouritzin, Approximations for singularly-perturbed parabolic equations of arbitrary order'', Nonlinear Studies  7 (2) (2000) pp 179--210.

17. M.A. Kouritzin and D. Li, On explicit solutions to stochastic differential equations'', Stochastic Analysis and Applications, 18 (4), (2000), 571--580.

18. M.A. Kouritzin, Exact infinite dimensional filters and explicit solutions'', in  Stochastic Models Eds. Luis G. Gorostiza and B. Gail Ivanoff (2000) 265--282.

19. D.J. Ballantyne, H.Y. Chan, and M.A. Kouritzin, A novel branching particle method for tracking'', in  Signal and Data Processing of Small Targets 2000, Proceedings of SPIE, 4048  (2000) Ed. Oliver E. Drummond 277--287.

20. D. Blount and M.A. Kouritzin, Holder continuity for spatial and path processes via spectral analysis'', Probability Theory and Related Fields 119 (2001), 589--603.

21. D.J. Ballantyne, J. Hoffman, and M.A. Kouritzin, Practical applications of a branching particle-base filter'', in Signal Processing, Sensor Fusion, and Target Recognition X 2001, Proceedings of SPIE 4380 (2001) Ed. I. Kadar 253--260.

22. H.Y. Chan, and M.A. Kouritzin, Particle filters for combined state and parameter estimation'', in  Signal Processing, Sensor Fusion, and Target Recognition X 2001, Proceedings of SPIE, 4380 (2001) Ed. I. Kadar 244--252.

23. K. Fleischmann and M.A. Kouritzin, Flexible efficient branching particle tracking algorithms and implementation'', US Patent Application Seriel Number 09/879210, filed by Lockheed Martin corp. June 13, 2001, 20 pages.

24. P. Del Moral, M.A. Kouritzin, and L. Miclo, On a class of discrete generation interacting paricle systems'', Electronic Journal of Probability , Vol. 6 (2001) Paper no. 16, 1-26.

25. D.J. Ballantyne, H.Y. Chan, and M.A. Kouritzin, A branching particle-based nonlinear filter for multi-target tracking'', Distributed Tracking I, Fusion2001, WeA2 }(2001) Ed. J. Llinas 3--10.

26. M.A. Kouritzin and H. Long, Convergence of Markov chain approximations to stochastic reaction diffusion equations'', to appear in Annals of Applied Probability, 31 pages.

27. M.A. Kouritzin, B. Remillard, and C.P. Chan, Parameter estimation for filtering problems with stable noise'', Target Tracking III, Fusion 2001, WeB1 (2001) Ed. P. Valin, 27--30.

28. M.A. Kouritzin, H. Long, and W. Sun, Nonlinear filtering for diffusions in random environments'', to appear in Journal of Theoretical Probability.

29. M.A. Kouritzin, H. Long, and W. Sun, On Markov chain approximations to semilinear partial differential equations driven by Poisson measure noise'', to appear in Stochastic Analysis and Applications.

30. W. Bauer, S. Kim, and M.A. Kouritzin, Continuous and discrete space particle filters for predictions in acoustic positioning'', to appear in 2002 Proceedings of SPIE

31. D.J. Ballantyne, M.A. Kouritzin, H. Long, and W. Sun Discrete-space particle filters for reflecting diffusions'', to appear in Proceedings of 2002 IEEE Aerospace Conference.

30. D.J. Ballantyne, and M.A. Kouritzin,  Weighted-Interacting particle-based nonlinear filters'', to appear in Signal Processing, Sensor Fusion, and Target Recognition XI, 2002 Proceedings of SPIE.

Have written eighteen review articles for the AMS Mathematical Reviews.

Edit and Contribute to the MITACS_PINTS Bulletin and Phase End Reports

Selection of Invited Lectures

1. Hidden in the Noise: Tracking and Prediction in Complex Systems', Pattern Recognition and Prediction, CASCON2002, Toronto, October 2002.

2. Workable approximations for stochastic reaction-diffusions', CMS Summer meeting, Laval June 2002.

3. Continuous and Discrete State Filters', Workshop on Spatially Distributed and Hierarchically Structured Stochastic Systems, Organizers: D. Dawson, K. Fleichmann, A. Greven, A. Wakolbinger, CRM, April 2002.

4. Continuous and Discrete Space Particle Filters'', Particle Systems and Filtering Workshop, Paris VI, Organizers: Pierre Del Moral, Jean Jacod, and Rene Carmona, June 2001.

5. Particle Filters'', Probability Days, Carleton University, Organizers: M. Csorgo and D. Dawson, April 2001.

6. Particle Filters'', Workshop on Nonlinear Filtering Methods for Tracking, Wright-Patterson Air Force Base, Dayton Ohio, Organizers = Stan Musak and Keith Kastella, February 2001.

7. Holder continuity in spatial processes'', University Paul Sabatier, February 2000.

8. A Perspective on Filtering Theory'', Department of Mathematics and Statistics, Arizona State University, Tempe, April 1999.

6. Weak invariance principles for parabolic equations with random coefficients'', Canadian Mathematical Society winter meeting, Kingston, December 1998.

9. Convolution in Filtering'', Technical University, Berlin, July 1998.

10. Arbitrary order parabolic stochastic partial differential equations with general Hilbert-space-valued noise'', Institute for Mathematical Statistics Annual Meeting, Park City, Utah, July 30, 1997.

11. Stochastic processes defined by parabolic equations with a small parameter'', The Second World Congress of Non-linear Analysts, Athens, Greece, July 16, 1996.

12. Parabolic equations with random coefficients'', {\em New Researchers in Statistics and Probability} meeting of the Institute of Mathematical Statistics, Kingston, Canada, July 7, 1995.

13. Rates of convergence and design considerations for on-line parametric inference'', Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada, January 25, 1995.

14. Law of the iterated logarithm results in sequential methods of statistical inference'', Statistics Society of Canada, Ottawa, March 4, 1994.

15. `On inferring almost-sure invariance principles for linear stochastic adaptive algorithms'' in Workshop Uber Mathematische Statistik, Universitat Freiburg, Germany, July 3, 1993.