As Computer Science kept doubling its volume every 2.5 years, Vlad grew with it. Consequently, Vlad’s interests are varied and somewhat encyclopaedic in nature.
His main interests are computer vision, parallel computing and simulation, with visual machine learning and parallel simulation of parallel systems to boot!
Other computing research interests include: artificial intelligence, pattern recognition and classification, evolution of expert systems, object orientation and software engineering (Ada95, Ada2005, CASE), networking and operating systems.
Vlad has strong mathematical background which supports his research interests in operations research, statistics and simulation.
In particular, Vlad finds Artificial Intelligence to be in a in a state of great potential. Mathematical theories, heuristics and findings are rather plentiful and very promising, but the current state of computing technology does not allow (yet!) to verify all the theories and findings experimentally. Hence his focus on parallel processing, especially as it applies to Artificial Intelligence.
Consequently Vlad and his students wrote (in Ada95 for smooth handling of parallelism) a parallel simulator of parallel systems of arbitrary topology, running synthetic programs of arbitrary levels of parallelism, and putting arbitrary loads on simulated processors and inter-CPU communication channels. All this with hope of finding practical guidelines for construction of operating systems for parallel computers, as well as classifying arbitrary algorithms into affinity groups of preferences to various classes of parallel systems. Lots of experimentation is ahead … especially in search of parallel computer architectures conducive to visual machine learning.
Vlad’s interest in machine vision led him to collaboration with another student, Behzad “Ben” Salami (now a graduate student at U. of Guelph) formulate a theory regarding the vision systems of vertebrates. Part of this work, applicable to robotics, is being investigated for patent potential now.. All this started by attacking and solving problems related to automatic identification of birefringent, thin petrographic sections using a special polarizing microscope, designed by Dr. Frank Fueten (ERSC).
- An Algorithm for Adaptive Maximization of Speedup, with J. Martin, Brock Technical Report # CS-03-09, September 2003.
- Recursive Problem of Calibration of Expert Systems, January 1998.
- The Structure of the Brain and of the Adaptive Computer Architectures, January 1998.
- A Criterion for Resolution of Ambiguity of Raster Images
Proceedings of the IEEE International Symposium on Industrial Electronics, Warsaw, June 17-20, 1996.
- Library of Anticipatory Random Number Generators
Proceedings of the Summer’95 Conference of the Society for Computer Simulation, Ottawa, July 24-26, 1995, pp. 120-130.
- On Resolution of Ambiguity of Raster Images, Technical Report # CS-95-01
Dept. of Computer Science, Brock University, St.Catharines, Ontario, 1995.