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Alexander T Tzanov
New York University
New York, New York

Alexander Tzanov has a background in various medical and nuclear electronics (applied physics), environmental protection and sustainable development, chemistry, and computer science.

He started his professional life in 1984 when he graduated in electronics and started as a research associate in the Department of Electronics at the Technical University (TU) of Sofia (Bulgaria). In 1987, he became an assistant professor in the Department of Computer Science. For the next 12 years, he taught undergraduate and graduate courses in object-oriented programming, functional programming, and generic programming. He also taught a course on microprocessors, which covered computer system architectures, microprocessors’ organization, assembly language, and computer on a chip; he developed a new curriculum for the discipline within the MS program in automation and control at TU. His research interests evolved toward machine learning, specifically algorithms and models for inductive learning, learning by example, and pattern recognition.

In 1993, he joined the Department of Computer Science at Queen’s University (Belfast, UK) as a research scientist and did research in pattern recognition and quantitative management systems. At that time, his research interests shifted toward high-performance computing. In 1996, as a visiting professor at Buckingham University (UK) in the Department of Computer Science, he became involved in research on massive parallel numerical algorithms and got hooked on accelerators. At the same time, he completed his second MS degree in environmental protection and sustainable development. His research interests leaned toward the development of massive parallel algorithms and models for environmental issues, specifically the development of models for build up and distribution of secondary air pollutants. He developed a system for modeling the distribution of secondary air pollution over regions with complex orography in collaboration with the Institute of Meteorology and Hydrology at the Bulgarian Academy of Sciences. The software utilized a data mining algorithm for meteorological data over a 100-year period, an inductive learning algorithm for decision making, and real-time measurements for sampling.

In 1998, Tzanov joined the Department of Biochemistry and Biophysics at Columbia University (NY) as research scientist, where he researched applications of high-performance computing architectures and machine learning in computational biology and biophysics. In 2002, he joined the high-performance computing group at New York University (NYU) as a faculty technology specialist. Within this environment, he provided support for various research projects at NYU and became an expert in grid computing, shared memory servers, and clusters. He developed, tuned, ported, and benchmarked codes for molecular modeling and simulation, computational biology, and computational chemistry. Tzanov then moved to the Department of Chemistry at NYU and currently researches massive parallel computing algorithms for quantum computational chemistry.

He is the author of a book on systems programming, co-author of a book on object-oriented generic programming, and co-author of several papers in the scientific computing, modeling, data mining, and computational chemistry areas.


ß-barrel channel proteins as tools in nanotechnology: biology, basic science and advanced applications
Fioroni M., Dworeck T., Rodriguez-Ropero F.,  Springer Publishing Company, Incorporated, New York, NY, 2013. 200 pp. Type: Book (978-9-400774-28-5)

This short text addresses the topic of -barrel membrane proteins, which can be used as models or components in nanotechnology. Although the title suggests a focus on -barrel membrane proteins as tools, the actual text focuses more on...


Modern computer algebra
von zur Gathen J., Gerhard J.,  Cambridge University Press, New York, NY, 2013. 808 pp. Type: Book (978-1-107039-03-2)

Computer algebra is a relatively new field providing a framework for developing code that finds exact solutions to equations. Obviously, many problems do not have exact solutions at all, such as in quantum chemistry and physics. Others, such as...


Graphs, networks and algorithms (4th ed.)
Jungnickel D.,  Springer Publishing Company, Incorporated, Berlin, Germany, 2013. 695 pp. Type: Book (978-3-642322-77-8)

Without any doubt, this fourth edition of a long-respected resource will become an indispensable reference for any researcher, teacher, or student who deals with problems of combinatorial optimization. The book qualifies as a first-class...


CUDA programming: a developer’s guide to parallel computing with GPUs
Cook S.,  Morgan Kaufmann Publishers Inc., Waltham, MA, 2013. 600 pp. Type: Book (978-0-124159-33-4), Reviews: (2 of 2)

There are many books on different aspects of programming with CUDA. However, this book differs from the others in terms of its practicality. The book does not require preliminary knowledge about CUDA devices, either as hardware or as a software...


Nonparametric inference on manifolds: with applications to shape spaces
Bhattacharya A., Bhattacharya R.,  Cambridge University Press, New York, NY, 2012. 252 pp. Type: Book (978-1-107019-58-4)

This monograph represents a systematic introduction to the general theory of the statistics of manifolds, with special emphasis on the manifolds of shapes. The statistics of shapes is a relatively new area of research, with only 30 to 40 years of ...


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