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| Maulik A. Dave completed his PhD in Computer Science at the Indian Institute of Science. Earlier, he completed his BE in Civil Engineering at M.S. University of Baroda. His PhD thesis received an award from the Institute. For the thesis, he designed a new programming language and implemented a compiler for it. At the Indian Institute of Science, he was chairman of the students’ council for a year, and was actively involved in student activities. He has also completed the Madhyama purna exam of Gandharva Mahavidyalay for Indian classical music. After finishing his education, he decided to join industry. In earlier years, he worked at companies such as Sun and IBM, as well as research startups. He established his own company later on. For the last nine years, he has worked as a developer in industry where he has applied his knowledge of programming and systems to develop and maintain various software systems. As part of the commercial world, he has obtained certificates for Java, MySQL, and software development. He has worked with technologies involving systems computing, enterprise computing, and applications. During his education, his research areas of interests were compilers, programming languages, and parallel processing. Later on, his interests also included simulation and software development. His interests further grew when he started reviewing research papers and books. He has reviewed in almost all areas of computer science, as well as in management, engineering, and mathematics. He has written 87 reviews in Computing Reviews. His most active year was 2012, when he wrote more than 25 reviews. He has also written reviews for the ACM SIGACT newsletter, IEEE Computer Society, and Mathematical Reviews. His research-based publications have appeared in the Journal of Indian Institute of Science and the Proceedings of the International Conference on High-Performance Computing. He has volunteered as the director of professional activities at IEEE Atlanta. |
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1 - 10 of 46
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Interpolatory methods for model reduction Antoulas A., Beattie C., Güğercin S., SIAM, Philadelphia, PA, 2020. 232 pp. Type: Book (978-1-611976-07-6)
Interpolation methods are automatic techniques for reducing the size and other complexities of large complicated models. Modeling physical systems using differential equations and geometrical properties has been popular among scientist...
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Oct 26 2021 |
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Foundations of probabilistic programming Barthe G., Katoen J., Silva A., Cambridge University Press, Cambridge, UK, 2021. 582 pp. Type: Book (978-1-108488-51-8)
This book covers various programming languages for probabilistic programming. The languages are described using syntax, semantics, and examples. It also looks at the theories related to the semantics of probability constructs and discu...
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Oct 18 2021 |
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Retrospectives antipatterns Corry A., Addison-Wesley, Boston, MA, 2021. 234 pp. Type: Book (978-0-136823-36-0)
The book is a collection of antipatterns that can emerge while conducting retrospectives in agile environments. The antipatterns discussed are from the author’s experiences. The collection includes structural, planning, and p...
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Sep 13 2021 |
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Essential C# 8.0 (7th ed.) Michaelis M., Addison-Wesley, Boston, MA, 2020. 1043 pp. Type: Book (978-1-359722-64-5)
This book describes the C#, a general-purpose programming language used in the commercial world. The book has a very detailed explanation of various language constructs. The constructs are explained with code listings and their backgro...
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Mar 11 2021 |
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Visual and text sentiment analysis through hierarchical deep learning networks Chaudhuri A., Springer International Publishing, New York, NY, 2019. 120 pp. Type: Book
This book is on the extraction of sentiments from text/image data using machine learning. It describes research related to developing a deep learning technique for the extraction. The technique uses hierarchical gated feedback recurren...
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Jan 25 2021 |
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Variational Bayesian learning theory Nakajima S., Watanabe K., Sugiyama M., Cambridge University Press, New York, NY, 2019. 558 pp. Type: Book (978-1-107076-15-0)
In machine learning, variational Bayesian (VB) learning is one of the most popular methods, according to the back cover of the book. The VB learning framework poses and solves optimization problems. The book explains the optimization o...
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Sep 10 2020 |
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PDE dynamics: an introduction Kuehn C., SIAM-Society for Industrial and Applied Mathematics, Philadelphia, PA, 2019. 245 pp. Type: Book (978-1-611975-65-9)
Interactions between partial differential equations (PDEs) and dynamical systems are explored in this book. PDEs involving time intervals are used to explain many problems. The study of dynamics can help readers understand PDEs via tim...
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Feb 12 2020 |
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Nonlocal modeling, analysis, and computation Du Q., SIAM-Society for Industrial and Applied Mathematics, Philadelphia, PA, 2019. 166 pp. Type: Book (978-1-611975-61-1)
Nonlocal models are models that generalize partial differential equations (PDEs). In PDE-based modeling, for a point, the values can be verified without using any values of other points. In nonlocal modeling, local values and nonlocal ...
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Nov 8 2019 |
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Fractional calculus with its applications in engineering and technology Yang Y., Zhang H., Morgan&Claypool Publishers, San Rafael, CA, 2019. 108 pp. Type: Book (978-1-681735-16-0)
Fractional calculus is three centuries old, but interest in its applications is growing. This is a short book on fractional calculus with some useful mathematics and applications. It describes various definitions for fractional order d...
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Oct 30 2019 |
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Quantum computing: an environment for intelligent large scale real application Hassanien A., Elhoseny M., Kacprzyk J., Springer International Publishing, New York, NY, 2018. 505 pp. Type: Book (978-3-319636-38-2)
The book covers applications in quantum computing, along with some fundamental research. The application areas include cryptography, networking, image processing, optimization, and multi-user systems. The research work includes quantum...
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Nov 26 2018 |
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