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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.


Murach’s beginning Java with NetBeans
Murach J., Urban M.,  Mike Murach & Associates, Inc., Fresno, CA, 2015. 660 pp. Type: Book (978-1-890774-84-4)

Java is a programming language that gained popularity in recent years because it became a standard language in many computer science (CS) curricula. Because Java as a language is not specifically difficult, sometimes the teaching process simplifie...


Parameterized algorithms
Cygan M., Fomin F., Kowalik Ł., Lokshtanov D., Marx D., Pilipczuk M., Pilipczuk M., Saurabh S.,  Springer Publishing Company, Incorporated, New York, NY, 2015. 613 pp. Type: Book (978-3-319212-74-6)

The topic of parameterized algorithms is one of the main subjects in modern computer science. In this type of algorithm analysis, the running time is a function of the size of the input data and of a set of one or more parameters. The theory of pa...


Quantum chance: nonlocality, teleportation and other quantum marvels
Gisin N.,  Springer, Cham, Switzerland, 2014. 109 pp. Type: Book (978-3-319054-72-8)

Though very short--at only around 100 pages--this is one of the most enjoyable books I’ve read recently. Its central concept is non-local correlation (nonlocality). In chapter 2, the author introduces the concept of correlation as ...


Advanced C and C++ compiling
Stevanovic M.,  Apress, Berkeley, CA, 2014. 340 pp. Type: Book (978-1-430266-67-9)

The title of this book is a bit misleading since it implies a book presenting a detailed explanation of compiler documentation often skipped or misunderstood by most users. This is not true. Instead, this book is a comprehensive reference to compi...


The development of an integrated planning and decision support system (IPDSS) for land consolidation
Demetriou D.,  Springer Publishing Company, Incorporated, Cham, Switzerland, 2014. 333 pp. Type: Book (978-3-319023-46-5)

This distinguished PhD thesis contains reviews of three main interrelated issues: land fragmentation, land consolidation, and land relocation. Land fragmentation is a major problem in many countries....


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