Curriculum Vitae

Current Position

Professor, University of Alberta, Mathematical & Statistical Sciences

• Conduct research in Probability, Stochastic Processes and Data Science, including neural networks, machine learning, filtering theory, (weak and almost sure) invariance principles, stochastic convergence, measure-valued processes, large deviation theory, mathematical finance, random field simulation.
• Committed instructor, always striving to improve effectiveness and to challenge all students. Have produced several man-years of problems and content to help student assimilation.
• Teach undergraduate and graduate courses in calculus, probability, measure theory, statistics, Markov processes and stochastic equations.
• Supervise undergraduate students, graduate students, and postdoctoral fellows.
• Served on: Science Faculty Visiting committee, Department Appointments committee, Programme Advisory committees, Advisory Examination committees, Outreach committees, NSERC postdoctoral candidate evaluation committee

Graduate Students and Postdoctoral Fellows

• Miranda Liu, current MSc student.
• Minghuan Wu, current MSc student.
• Ryan Mannion, current MSc student.
• Sumaiya Rahman, current MSc student.
• Michael Gyimah, current MSc student.
• Jyoti Bhadana, current PIMS Postdoctoral fellow.
• Hanbo Gong, current MSc student.
• Seoyeon Park, current MSc student.
• Rishabh Kumar, current MSc student.
• Nuzhat Nishi, current MSc student.
• Prem Kumar, "Statistical Methods in Flood Prediction'', 2022 visiting PhD student, PhD 2023.
• Dan Richard, "Topological and Distributional Neural Networks'', MSc Thesis 2022, Next Position: Data Science Methodologist, Statistics Canada.
• Jiayu Zheng, Postdoctoral fellow 2019-2021. Next Position: lecturer in the Shenzhen MSU-BIT University.
• Stephen Styles, "Bootstrapped Stochastic Approximation for Wide Neural Network Classifications" MSc 2021. Next Position: Methodologist, Statistics Canada.
• Sounak Paul, "Marcinkiewicz strong law of large numbers for products of long-range dependent and heavy-tailed linear processes'', MSc Thesis 2019. Current Position: PhD program in Statistics at the University of Chicago.
• Khoa Le, Postdoctoral fellow 2016-2017. Next Position: Post-doctoral Fellow of (Field's Medalist) Martin Hairer.
• Chi Dong," Replication and Its Application to Weak Convergence", PhD Thesis 2017,   Faculty of Science Dissertation Award. Current Position: Lead quantitative strategy engineer, Shenzhen ZMate Network Technology Company.
• Huiting Hu, " On Path-Dependent Option Pricing for the Heston Model ", M.Sc. Thesis 2016, Next Position:  PhD. Student Chinese University of Hong Kong.
• Xingpu Wang," Web-based Particle Filters ", M.Sc. Thesis 2015, Current Position:  RGA reinsurance group of America, Shanghai.
• S. Sadeghi, " Marcinkiewicz Strong Law of Large Numbers and Stochastic Approximation Algorithms Under Heavy-tailed and Long-range Dependence Setting", PhD Thesis 2015,   Faculty of Science Dissertation Award. Current Position: Staff Statistician at Invidi Technologies.
• Zi Ye, " A Discrete-time Particle Filter and Central Limit Theorem", M.Sc. Thesis 2013, Next Position:  PhD student in Statistics at Cornell University.
• F. Newton, "On Random Field CAPTCHA Generation", M.Sc. Thesis 2012, Next Position:  Senior Developer at Clio and Themis Solutions.
• B. Wu, Postdoctoral fellow 2007-2008. Recent Position: Manager, Basel Parameter Validation, Royal Bank of Canada, Toronto.
• J. Huang, "Microstructure Filtering in Finance", PhD Thesis 2007, Recent Position: Tenured Associate Professor at the Hong Kong Polytechnical University.
• D.J. Ballantyne, "Homeomorphic Methods for Separating Measures in Historical Filtering", M.Sc. Thesis 2005, Next Position:  Research Scientist at Invidi Technologies.
• Xingqiu Zhao, Postdoctoral fellow 2003-2004. Recent Position: Associate Head and Professor, Hong Kong Polytechnical University.
• H. Long, Postdoctoral fellow 1999 - 2003. Recent Position: Full Professor, Florida Atlantic University, Florida.
• W. Sun, Postdoctoral fellow 2000-2003. Recent Position: Full Professor, Concordia University, Quebec.
• D. Lyder, Postdoctoral fellow 1999-2000. Next Position: Professor King's College, Alberta.
• D. Li, Postdoctoral fellow 1997-1998. Recent Position: Full Professor, Lakehead University, Ontario.
• M.K. Prefontaine, "The infinite dimensional exact filter for a mean-reverting financial volatility model'', M.Sc. Project, 2000. Next Position: Financial Analyst at Weyerhauser, Vancouver.
• G.N. Nkabinde, "On almost sure convergence rates for recursive stochastic algorithms'', M.A.Sc. Thesis, 1992. Next Postition: Engineer at DeBeers, South Africa.

Other Positions, Service, Awards, Grants

Industry Grant,  Scotiabank (2023-2025)

Industry Grant,  Canadian Western Bank (2018-2019)

CRC Service,  Served on College of Reviewers for the Canadian Research Chair programme.

Honor Roll of Teachers, Faculty of Science (Students Choice Category 2013-2014)

Recipient, NSERC Discovery Grant (1997-present)

President of Probability Section, Statistics Society of Canada (Jun. 2013 - May 2014)

• In charge of five talk sessions, a workshop and a student poster prize competition for 2014 meeting at the University of Toronto

Grant Reviewer: Evaluated many NSERC, National Science Foundation, MITACS, PIMS, Hong Kong (RGC) and American Mathematical Society research grant proposals (1999-present).

Chief Trader Perfect Timing Investment Club (2011-2014).

Co-recipient of RGC Hong Kong collaborative research grant (2010-2012) (valued at approximately $100,000 over three years)

President, Random Knowledge Inc. and Fast Track Technologies Inc. (October 2002 - December 2009)

• Led companies through startup and funding process.
• Directed work in network security and privacy, finance, sports modeling and dynamic profiling.
• Company successes include runner up in 2004 Venture Prize Business Plan Competition, being awarded Alberta Ingenuity Fund Awards, winning large industrial contracts, being awarded an equipment grant from SUN, and obtaining a first round of financing.

Co-founder , MuchLearning.org and MuchTraining.org, online Learning Centres, provides open content.

• Contributed online open calculus, probability and statistics content used by thousands of students.

Project Leader , Mathematics of Information Technology and Complex Systems (MITACS) (Jan. 1999- May 2005)

• Contributed to winning MITACS Network of Centers of Excellence Application
• Led highly-rated MITACS national center of excellence "Prediction in Interacting Systems''
• Granted $250,000-$320,000 annually from NCE, industry, and ASRA/PIMS.
• Worked with five different companies, including Lockheed Martin Corp.
• Organized many meetings and edited many publications.

Honorary Fellow, University of Wisconsin-Madison, Department of Mathematics (Jan. - May 2003).

Visiting Professor, H.E.C. Montreal, Department of Mathematics (Nov. - Dec. 2002).

Visiting Professor, Carlton University, Department of Mathematics and Statistics (Aug. - Oct. 2002).

Organizer, Filtering 2002, a successful international PIMS and MITACS sponsored conference (with R.J. Elliott, T.G. Kurtz, and H. Long) in filtering (July 2002).

Session Organizer, 2002 IMS Probability Symposium in Banff.

Recipient, 2001 PIMS Industrial Outreach Prize. (National Award, Sponsored by TD Bank).

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

Associate Professor, University of Alberta (1997-2001)

Reviewer, wrote twenty-one AMS mathematics review articles (1996-2000)

Organizer, (with T.G. Kurtz) filtering workshop at the University of Wisconsin-Madison (July 1999)

Recipient, Institute for Mathematics and Its Applications Industrial Postdoctoral Fellowship (1995 and 1996).

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.
• Developed non-standard nonlinear filtering theory for air traffic control and military problems under sponsorship of Lockheed Martin.

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

Recipient, DAAD Study Visit Award (for Professors visiting Germany) (1993)

Visiting Scientist, Advisor: Professor Ernst Eberlein, Universitat Freiburg, Institut fur Mathematische Stochastik (Jan. - Dec. 1993)

Recipient, NSERC Postdoctoral Fellowship (1993-1994)

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.
• Supervised graduate students and graduated a M.A.Sc.

Educational Experience

• Ph.D.  in Electrical Engineering, University of Waterloo, Advisor: Professor Andrew Heunis, Scholarships: NSERC Postgraduate Scholarship, Carl Pollock Scholarship, and Faculty of Engineering Scholarship.
• B.A.Sc. Honours Bachelor of Applied Science, Electrical Eng., University of Waterloo.
• Invented filtering algorithms being used by Lockheed Martin Corp., Invidi Technologies, Acoustic Positioning Research Inc., FTT Inc., and Random Knowledge Inc.
• Two years experience in industry training and product development with Lockheed Martin.
• Two years engineering work experience during undergraduate degree.

Refereed Publications

1. M. A. Kouritzin (2024),   " Sampling and filtering with Markov chains '', to appear in Signal Processing . https://doi.org/10.1016/j.sigpro.2024.109613.
2. M. A. Kouritzin and D. Richard (2023),   " Universal Approximation and the Topological Neural Network '', to appear in IEEE Access . DOI: 10.1109/ACCESS.2023.3342063.
3. M. A. Kouritzin, T. G. Kurtz and J. Xiong (2023),   " Stochastic Differential Equations with Local Interactions '', Electron. Commun. Probab. 28 1-13. DOI: 10.1214/23-ECP559.
4. Y. Hu, M. A. Kouritzin, P. Xia and J. Zheng (2023),   " On mean-field super-Brownian motions '', to appear in Ann. Appl. Probab. 33(5): 3872-3915. DOI: 10.1214/22-AAP1909.
5. Y. Hu, M. A. Kouritzin and J. Zheng (2024),   " Nonlinear McKean-Vlasov diffusions under the weak Hormander condition with quantile-dependent coefficients'', Potential Anal 60: 1093-1119. https://doi.org/10.1007/s11118-023-10080-x.
6. M. A. Kouritzin and S. Paul (2022), " On almost sure limit theorems for long-range dependent, heavy-tailed processes ''. Stochastic Processes and Their Applications 152 208-232. https://doi.org/10.1016/j.spa.2022.06.021
7. I.R. Kouarfate, M. A. Kouritzin and A. Mackay (2021),   " Explicit solution simulation method for the 3/2 model '', Advances in Probability and Mathematical Statistics, Springer Nature 123-146.
8. M. A. Kouritzin, A. Mackay and N. Vellone-Scott (2020),   " New Branching Filters With Explicit Negative Dependence '', IEEE Access 8 157306--157321. doi: https//doi.org/10.1109/ACCESS.2020.3019226.
9. M. A. Kouritzin and K. Le (2020),   " Long-time limits and occupation times for stable Fleming-Viot processes with decaying sampling rates '', Ann. Inst. H. Poincare Probab. Statist. 56(4), 2595-2620.
10. M. A. Kouritzin and A. Mackay (2020),   " Branching particle pricers with Heston examples '', Int. J. Theor. Appl. Finan. 23 , paper 2050003, [29 pages]. doi: https//doi.org/10.1142/S021902492050003X.
11. M. A. Kouritzin and B. Remillard (2019),   " On explicit local solutions of Ito diffusions '', Journal of Mathematical Analysis and Applications 473(1), pp. 534-566. https://doi.org/10.1016/j.jmaa.2018.12.067.
12. M. A. Kouritzin, K. Le and D. Sezer (2019),   " Laws of large numbers for supercrictical branching Gaussian processes'', Stochastic Processes and Their Applications 129(9), pp. 3463-3498. https://doi.org/10.1016/j.spa.2018.09.011.
13. M. A. Kouritzin and A. MacKay (2018),   " VIX-linked fees for GMWBS via explicit solution simulation methods'', Insurance: Mathematics and Economics 81, pp. 1-17. doi: https://doi.org/10.1016/j.insmatheco.2018.04.001.
14. M. A. Kouritzin (2018),   " Explicit Heston solutions and stochastic approximation for path-dependent option pricing '', Int. J. Theor. Appl. Finan. 21 , paper 1850006, [45 pages]. doi: https//doi.org/10.1142/S0219024918500061.
15. M. A. Kouritzin, F. Newton and B. Wu (2017), " A Flexible, Real-Time Algorithm for Simulating Correlated Random Fields and its Properties'', Journal of Mathematics and Statistics 13, pp. 197-208.
16. M. A. Kouritzin (2017),   " Residual and Stratified Branching Particle Filters '', Computational Statistics and Data Analysis. 111, pp. 145-165. doi: 10.1016/j.csda.2017.02.003
17. M. A. Kouritzin (2017),   " Convergence Rates for Residual Branching Particle Filters'', Journal of Mathematical Analysis and Applications .449, pp. 1053-1093. https://doi.org/10.1016/j.jmaa.2016.12.046
18. M. A. Kouritzin and S. Sadeghi (2016),  " Marcinkiewicz Law of Large Numbers for Outer-products of Heavy-Tailed, Long-Range-Dependent Data '', Advances in Applied Probability .48, pp.349-368.
19. M. A. Kouritzin (2016), " On tightness for probability measures on Skorokhod spaces '', the Transactions of the American Mathematical Society. 368(8), pp. 5675-5700.
20. M. A. Kouritzin (2015),  " Microstructure Models with Short-Term Inertia and Stochastic Volatility '', Mathematical Problems in Engineering vol. 2015, Article ID 323475, 17 pages, 2015. doi:10.1155/2015/323475.
21. M. A. Kouritzin and S. Sadeghi (2015),  " Convergence Rates and Decoupling in Linear Stochastic Approximation Algorithms '', SIAM J. Control Optim. 53, pp. 1484-1508.
22. S. Kim, B. Kim, M.A. Kouritzin, and G. Rieger (2014), "System and Method for a Computerized Learning System" US Patent number 8761658 granted June 24, 2014, filed by FastTrack Technologies Inc., 91 pages.
23. M. A. Kouritzin, F. Newton and B. Wu (2014), " A graph theoretic approach to simulation and classification '', Computational Statistics & Data Analysis 70, pp. 281-294.
24. M. A. Kouritzin and Y-X. Ren (2014), " A Strong Law of Large Numbers for Super-stable Processes '', Stochastic Processes Appl. 124, pp. 505-521.
25. M. A. Kouritzin, F. Newton and B. Wu (2013), " On random field CAPTCHA generation '', IEEE Trans. Image Processing 22(4), pp. 1656-1666.
26. M.A. Kouritzin, S. Kim, and J. Hailes (2012), "Method and Apparatus to Perform Real-Time Audience Estimation and Commercial Selection Suitable for Targeted Advertising" Australian Patent number AU2007247995 granted June 28, 2012, Japanese Patent number JP517826 granted Jan. 11,2013 and Canadian Patent number CA2651165 issued Feb. 4, 2014, filed by Invidi Corp., 42 pages.
27. F. Newton and M. A. Kouritzin (2011), "On Grey Levels in Random CAPTCHA Generation", Proc. of SPIE 8056, 80560U Visual Information Processing XX, edited by Zia-ur Rahman, Stephen E. Reichenbach, Mark A. Neifeld
28. D. Blount and M. A. Kouritzin (2010), " On convergence determining and separating classes of functions", Stochastic Processes and their Applications 120 1898-1907
29. D. Crisan, M. Kouritzin and J. Xiong (2009)," Nonlinear filtering with signal depending noise", Electron. J. Probab. 14, 1863-1883.
30. M. A. Kouritzin, D. Luo, F. Newton, B. Wu (2009), "Detecting targets hidden in random forests", Proc. SPIE Int. Soc. Opt. Eng. 7336, 73360N,
31. J. Macki, M.A. Kouritzin, S. Ghosh, J. Liu (2008) "Differential Calculus Workbook" 2008-2009 Edition, ISBN 978-0-981075-61-7, pp 1-125.
32. M.A.Kouritzin and S. Ghosh (2008), "Differential Calculus: Theory for users" 2008-2009 Edition, ISBN 978-0-981075-60-0, pp 1-326.
33. M.A. Kouritzin and H. Long (2008), "On extending classical filtering equations", Statistics and Probability Letters. 78 3195-3202
34. M.A. Kouritzin and B. Wu (2008), "Handling Target Obscuration through Markov Chain Observations" in Signal Processing, Sensor Fusion, and Target Recognition Proceedings of SPIE. 6968, 69680S, 9 pages.
35. M.A. Kouritzin, F. Newton, S. Orsten, D.C. Wilson (2008), "On Detecting Fake Coin Flip Sequences", IMS Collections 4 Markov Processes and Related Topics: A Festschrift for Thomas G. Kurtz, pp. 107-122.
36. M.A. Kouritzin, and S. Kim (2007), "The refining stochastic grid filter and implementation" US Patent Number 7,188, 048 B2 granted March 6, 2007, filed by assignee Lockheed Martin Corp., 37 pages.
37. M.A. Kouritzin (2006), "Selectively resampling particle filter and implementation", US Patent Number 7,058,550 granted June 6, 2006, filed by assignee Lockheed Martin Corp., 41 pages.
38. M.A. Kouritzin and W. Sun (2005) " Rates for branching particle approximations of continuous discrete filters '',   The Annals of Applied Probability, 15 2739-2772.
39. M.A. Kouritzin, D. Ballantyne, Y. Hu and H. Kim (2005); "On sonobuoy placement for submarine tracking."  Proc. SPIE Int. Soc. Opt. Eng. 5809,  244-252.
40. M.A. Kouritzin, Y. Zeng (2005), "Bayesian model selection via filtering for a class of micro-movement models of asset price",  the International Journal of Theoretical and Applied Finance, 8 97-121.
41. M.A. Kouritzin, and Y. Zeng (2005), "Weak convergence for a type of conditional expectation: application to the inference for a class of asset price models", Nonlinear Analysis, Theory, Methods & Applications, Series A, 60 231-239.
42. J. Hoffman, C. Ketelsen, M. Kouritzin, A. Limon, Y. Mileyko and K. Yewchuk (2004); "Tracking and identifying Multiple Targets."  Canadian Applied Mathematics Quarterly, 12 Number 1 pp. 103-124.
43. J. Kim, S. Kim, M.A. Kouritzin, and W. Sun (2004), "Detecting network portscans through anomaly detection", in Signal Processing, Sensor Fusion and Target Recognition XIII, the 2004 Proceedings of SPIE, 5429, 254-263.
44. J. Hailes, M.A. Kouritzin, R. Marsh, and J. McCrosky (2004), ""Tracking promyelocytic leukemia nuclear bodies concept via filtering", Proceedings of ICMENS 2004, 433-437.
45. D. Blount, N. Hu, M.A. Kouritzin, and J. McCrosky (2004), "Artificial learning approaches for multi-target tracking", in Automatic Target Recognition XIV, edited by F.A. Sadjadi, 2004 Proceedings of SPIE, 5426: 293-304.
46. S. Kim, M.A. Kouritzin, H. Long, J. McCrosky, W. Sun, and X. Zhao (2004), "A stochastic grid filter for multi-target tracking", in Signal Processing, Sensor Fusion and Target Recognition XIII,2004 Proceedings of SPIE, 5429: 245-253.
47. M.A. Kouritzin, W. Sun, and J. Xiong (2004), ""Nonlinear filtering for reflecting diffusions in random environments by nonparametric estimation". Electronic Journal of Probability, Vol. 9, Paper no. 18, 560-574.
48. M.A. Kouritzin, H. Long, and W. Sun (2004), " Markov chain approximations to filtering equations for reflecting diffusion processes". Stochastic Processes and Applications, 110 275-294.
49. M.A. Kouritzin, H. Long, X. Ma, and W. Sun (2003), "Non-recursive and recursive methods for parameter estimation in filtering problems" in Signal Processing, Sensor Fusion, and Target Recognition XII, 2003 Proceedings of SPIE 5096, 585-596.
50. D.J. Ballantyne, J. Hailes, M.A. Kouritain, H. Long, and J. Wiersma (2003), "A hybrid weighted interacting particle filter for multi-target tracking", in Signal Processing, Sensor Fusion, and Target Recognition XII, 2003 Proceedings of SPIE 5096, 244-255.
51. M.A. Kouritzin, H. Long, and W. Sun (2003), "On Markov chain approximations to semilinear partial differential equations driven by Poisson meaure noise", Stochastic Analysis and Applications21, 419-441.
52. M.A. Kouritzin, H. Long, and W. Sun (2003), "Nonlinear filtering for diffusions in random environments'', Journal of Theoretical Probability, 16 1-20.
53. D.J. Ballantyne, S. Kim, and M.A. Kouritzin (2002), "Weighted-interacting particle-based nonlinear filters" in Signal Processing, Sensor Fusion, and Target Recognition XI, Ivan Kadar, Editor,2002 Proceedings of SPIE 4729, 236-247.
54. D.J. Ballantyne, M.A. Kouritzin, H. Long, and W. Sun (2002), "Discrete-space particle filters for reflecting diffusions", Proceedings of the 2002 IEEE Aerospace Conference, Big Sky, Montana . IEEE Catalog Number: 02TH8593C, ISBN: 0-7803-7232-B March 9-16, 2002.
55. W. Bauer, S. Kim, and M.A. Kouritzin (2002), "Continuous and discrete space particle filters for predictions in acoustic positioning'', in Image Reconstruction from Incomplete Data II, 2002 Proceedings of SPIE 4792, 193-206.
56. M.A. Kouritzin, B. Remillard, and C.P. Chan (2001), "Parameter estimation for filtering problems with stable noise'', Target Tracking III, Fusion 2001, WeB1 Ed. P. Valin, 27--30.
57. M.A. Kouritzin and H. Long (2002), " Convergence of Markov chain approximations to stochastic reaction diffusion equations'', Annals of Applied Probability, 12, 1039-1070.
58. D.J. Ballantyne, H.Y. Chan, and M.A. Kouritzin (2001), "A branching particle-based nonlinear filter for multi-target tracking" Distributed Tracking I, Fusion 2001, WeA2 Ed. J. Llinas 3--10.
59. P. Del Moral, M.A. Kouritzin, and L. Miclo (2001), "On a class of discrete generation interacting particle systems'', Electronic Journal of Probability , Vol. 6 Paper no. 16, 1-26.
60. H.Y. Chan, and M.A. Kouritzin (2001), "Particle filters for combined state and parameter estimation'', in  Signal Processing, Sensor Fusion, and Target Recognition X 2001, Proceedings of SPIE,4380 Ed. I. Kadar 244--252.
61. D.J. Ballantyne, J. Hoffman, and M.A. Kouritzin (2001), "Practical applications of a branching particle-base filter'', in Signal Processing, Sensor Fusion, and Target Recognition X 2001,Proceedings of SPIE 4380 Ed. I. Kadar 253--260.
62. D. Blount and M.A. Kouritzin (2001), "Holder continuity for spatial and path processes via spectral analysis'', Probability Theory and Related Fields 119, 589--603.
63. D.J. Ballantyne, H.Y. Chan, and M.A. Kouritzin (2000), "A novel branching particle method for tracking'', in  Signal and Data Processing of Small Targets 2000, Proceedings of SPIE, 4048  Ed. Oliver E. Drummond 277--287.
64. M.A. Kouritzin (2000), "Exact infinite dimensional filters and explicit solutions'', in  Stochastic Models Eds. Luis G. Gorostiza and B. Gail Ivanoff 265--282.
65. M.A. Kouritzin and D. Li (2000), "On explicit solutions to stochastic differential equations'', Stochastic Analysis and Applications, 18 (4), 571--580.
66. M.A. Kouritzin (2000), "Approximations for singularly-perturbed parabolic equations of arbitrary order'', Nonlinear Studies  7 (2) pp 179--210.
67. M.A. Kouritzin (1998), "On exact filters for continuous signals with discrete observations'', IEEE Trans. on Auto Contr., AC-43 pp. 708--715.
68. D.A. Dawson and M.A. Kouritzin (1997), " Invariance principles for parabolic equations with random coefficients '', Journal of Functional Analysis 149 (2) pp. 377-414.
69. M.A. Kouritzin (1997), "Stochastic processes and perturbation problems defined by parabolic equations with a small parameter'', Nonlinear Analysis, Theory, Methods & Applications, 30, 4089--4099.
70. M.A. Kouritzin (1997), "Arbitrary order parabolic stochastic partial differential equations with general Hilbert-space-valued noise'',  The IMS Bulletin 26 pp. 322-323.
71. M.A. Kouritzin (1997), " Averaging for fundamental solutions of parabolic equations'', Journal of Differential Equations 136 pp. 35--75.
72. K. Kastella, M.A. Kouritzin, and A. Zatezalo (1996), "A nonlinear filter for altitude tracking'', October 1996 Proceedings of the Air Traffic Control Association  pp.1--5.
73. M.A. Kouritzin (1996), "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)pp. 811--840.
74. M.A. Kouritzin (1996), "On the convergence of linear stochastic approximation procedures'', IEEE Trans. Inform. Theory IT-42(4) pp. 1305--1309.
75. M.A. Kouritzin (1995), " Strong approximation for cross-covariances of linear variables with long-range dependence'', Stochastic Processes Appl. 60 pp. 343--353.
76. M.A. Kouritzin (1995), "Parabolic equations with random coefficients'', The IMS Bulletin 24(5) pp.  462--463.
77. M.A. Kouritzin (1994), "Inductive methods and rates of r^th-mean convergence in adaptive filtering'', Stochastics and Stochastics Reports 51 pp. 241--266.
78. A.J. Heunis and M.A. Kouritzin (1994), " Strong convergence in the stochastic averaging principle'', Math. Anal. Appl. 187(1) pp.134--155.
79. M.A. Kouritzin and A.J. Heunis (1994), " A law of the iterated logarithm for stochastic processes defined by differential equations with a small parameter'', Ann. Probab 22(2) pp. 659--679.
80. M.A. Kouritzin (1994), "On almost sure bounds for the LMS algorithm'' , IEEE Trans. Inform. Theory IT-40(2), pp.372--383.
81. M.A. Kouritzin and A.J. Heunis (1992), " Rates of convergence in a central limit theorem for stochastic processes defined by differential equations with a small parameter'', J. Multivariate Analysis,43(1) pp.58--109.