Boleslaw K. Szymanski
- 518 • 276 • 6838
- MRC 335A • RPI • 110 8th St. • Troy NY 12180
Dr. Szymanski's research interests span from network science, with emphasis on social networks and computer wireless and sensor networks to analysis and design of distributed and parallel algorithms, simulation of computers, networks and biological/ecological phenomena.
His projects include spread of opinion and other dynamic processes on networks, communities in social networks, and large-scale parallel and distributed computing and simulation. Dr. Szymanski led the development of the GANXIS and SpeakEasy community detection algorithms; the SENSE simulator for sensor network simulation, and VOGUE and Conceptor-based innovative HMM models.
The three most recent Ph.D. Graduates
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- Alaa Moussawi (Ph.D. Defense, March, 2018)
- Failure Mitigation, Vulnerability Detection and Persistence of Network Flows in Complex Systems
- Chief Data Scientist, The New York City Council, New York, NY
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- Konstantin Kuzmin (Ph.D. Defense, November, 2017)
- New Approaches to Efficient Structural Analysis of Social and Biological Networks
- Lecturer, Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY
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- Panagiotis Karampourniotis (Ph.D. Defense, June, 2017)
- The Impact of Heterogeneity in Thresholds of Opinion Dynamics, and in Crowd Decision-Making
- Postdoc, IBM, Inc., Boston, MA
Projects & Software
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MetPetDB
MetPetDB is a database for metamorphic petrology that is being designed and built by a global community of metamorphic petrologists and computer scientists at Rensselaer Polytechnic Institute as part of the National Cyberinfrastructure Initiative and supported by the NSF.
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MilkyWay@home
A research project that uses Internet-connected computers to do research in determining the evolution of the Milkyway galaxy.
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Mutual Exclusion Algorithm
Algorithm with linear wait that solved the open problem posed by Lamport in 1978.
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Parallel Toolkit for Community Quality Metrics
Software for a Parallel Toolkit for Community Quality Metrics, including modularity Q and modularity density Qds for researchers interested in in community detection.
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FineTuned Community Detection Algorithm
Software for a novel fine-tuned community detection algorithm (FineTunedAlg) which optimizes modularity density for the given network.
Current Postdocs
- Diego Fregolent
Current Graduate Students
- Ashwin Bahulkar
- Xiaoyan Lu
- Xiang Niu
- James Flamino
- Matthew V. Mohr
Current Positions
- Claire and Roland Schmitt Distinguished Professor of Computer Science
- Professor of Physics, Applied Physics, and Astronomy
- Director, Social Cognitive Network Academic Research Center, NS CTA
- Director, Network Science and Technology Center (NeST)
- Foreign Member, Polish Academy of Sciences
- Board Member, Network Science Society
- Associate Editor, IEEE Transactions on Computational Social Systems
- Editorial Board, Computational Methods in Science and Technology (CMST)
- Editorial Board, Computer Science Journal
Courses
| Fall 2017 | |
| CSCI-6250/4250 | Frontiers of Network Science |
| Fall 2016 | |
| CSCI-6250/4250 | Frontiers of Network Science |