Areas of Expertise (7)
Computation & Information Technology
Energy and the Environment
Dr. Szymanski's research interests span from network science, with an emphasis on social networks and computer wireless and sensor networks, to analysis and design of distributed 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 developed a novel Mutual Exclusion algorithm and 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.
Polish Academy of Sciences: Ph.D., Computer Science 1976
Warsaw University of Technology: M.Sc., Electronics 1973
Media Appearances (8)
RPI professor designs computer system to eliminate plane delays
Times Union print
If you’re stuck waiting out a flight delay at an airport -- and thinking there must be a better way -- you’re right. A Rensselaer Polytechnic Institute computer science professor says he worked out a system by which 80 percent of airline delays would be eliminated. Boleslaw Szymanski, the director of the Network Science and Technology Center at RPI, published a paper describing how to solve the most vexing holiday flight problem.
How to Tell When Your Country Is Past the Point of No Return
New York Times online
Political analysts, scholars and close observers of government are explicitly raising the possibility that the polarized American electoral system has come to the point at which a return to traditional democratic norms will be extremely difficult, if not impossible.
‘Tipping point’ makes partisan polarization irreversible
Cornell Chronicle online
As polarization has escalated in the U.S., the question of if and when that divide becomes insurmountable has become ever more pressing. In a new study, researchers have identified a tipping point, beyond which extreme polarization becomes irreversible.
The political divide in the United States has become irreconcilable, study says
Politics in the United States have become an increasingly polarized affair for decades, driven largely by the right moving further to the right. Observation of political polarization is not merely anecdotal; studies repeatedly bear this out. "We see this very disturbing pattern in which a shock brings people a little bit closer initially . . . but if polarization is too extreme, eventually the effects of a shared fate are swamped by the existing divisions and people become divided even on the shock issue," said network scientist Boleslaw Szymanski, a professor of computer science and director of the Army Research Laboratory Network Science and Technology Center at Rensselaer Polytechnic Institute. "If we reach that point, we cannot unite even in the face of war, climate change, pandemics, or other challenges to the survival of our society."
When It Comes to Politics, Americans Are Divided. Can Data Change That?
As the ideological gaps between Democrats and Republicans appear to grow increasingly wider, there is now new data that shows what could be driving that political divide. “We tend to think humans behave unpredictably, but more and more we see that, in a lot of settings, human choices can be explained by abstract and elegant models,” said Boleslaw Szymanski, a computer science professor at Rensselaer Polytechnic Institute.
Weeks before Midterms, Independents Vastly Outnumber Party Members
IVN News online
In the latest Gallup poll taken from August 1-12, 2018, independents outnumbered members of either major party by at least 15 percentage points, but politicians continue to tailor their messages for the most extreme wings of a polarized two-party system.
How Innovators Choose Their Next Career Move
Kellogg Insight online
What do online financial services, commercial spacecraft, and mass-market electric cars all have in common? Other than being industries shaped by serial entrepreneur Elon Musk, not a whole lot.
Key to Swaying Mass Opinion Found
Live Science online
For an opinion or belief, 10 percent is critical mass. If that proportion of the population emphatically embraces an idea, then it will spread rapidly to the majority of the population, scientists have found.
Analyzing and predicting success of professional musiciansScientific Reports
Inwon Kang, Michael Mandulak, and Boleslaw K. Szymanski
The emergence of streaming services, e.g., Spotify, has changed the way people listen to music and the way professional musicians achieve fame and success. Classical music has been the backbone of Western media for a long time, but Spotify has introduced the public to a much wider variety of music, also opening a new venue for professional musicians to gain exposure. In this paper, we use open-source data from Spotify and Musicbrainz databases to construct collaboration-based and genre-based networks. We call genres defined in these databases primary genres. Our goal is to find the correlation between various features of each professional musician, the current stage of their career, and the level of their success in the music field.
Resource-Mediated Consensus FormationProceedings of the SIGSIM-PADS'22: SIGSIM Conference on Principles of Advanced Discrete Simulation
Omar Malik, James Flamino, and Boleslaw K. Szymanski
In social sciences, simulating opinion dynamics to study the interplay between homophily and influence, and the subsequent formation of echo chambers, is of great importance. As such, in this paper we investigate echo chambers by implementing a unique social game in which we spawn in a large number of agents, each assigned one of the two opinions on an issue and a finite amount of influence in the form of a game currency.
Modelling epidemic spread in cities using public transportation as a proxy for generalized mobility trendsScientific Reports
Omar Malik, Bowen Gong, Alaa Moussawi, Gyorgy Korniss, and Boleslaw K. Szymanski
We study how public transportation data can inform the modeling of the spread of infectious diseases based on SIR dynamics. We present a model where public transportation data is used as an indicator of broader mobility patterns within a city, including the use of private transportation, walking etc. The mobility parameter derived from this data is used to model the infection rate.
Polarization and tipping pointsProceedings of the National Academy of Sciences
Michael W. Macy, Manqing Ma, Daniel R. Tabin, Jianxi Gao, and Boleslaw K. Szymanski
Our study was motivated by a highly disturbing puzzle. Confronted with a deadly global pandemic that threatened not only massive loss of life but also the collapse of our medical system and economy, why were we unable to put partisan divisions aside and unite in a common cause, similar to the national mobilization in the Great Depression and the Second World War? We used a computational model to search for an answer in the phase transitions of political polarization. The model reveals asymmetric hysteresis trajectories with tipping points that are hard to predict and that make polarization extremely difficult to reverse once the level exceeds a critical value.
Characterizing Topics in Social Media Using Dynamics of ConversationEntropy
James Flamino, Bowen Gong, Frederick Buchanan, Boleslaw K. Szymanski
Online social media provides massive open-ended platforms for users of a wide variety of backgrounds, interests, and beliefs to interact and debate, facilitating countless discussions across a myriad of subjects. With numerous unique voices being lent to the ever-growing information stream, it is essential to consider how the types of conversations that result from a social media post represent the post itself. We hypothesize that the biases and predispositions of users cause them to react to different topics in different ways not necessarily entirely intended by the sender. In this paper, we introduce a set of unique features that capture patterns of discourse, allowing us to empirically explore the relationship between a topic and the conversations it induces.
Optimizing Edge Sets in Networks to Produce Ground Truth Communities Based on ModularityNetworks
Daniel Kosmas, John E. Mitchell, Thomas C. Sharkey, and Boleslaw K. Szymanski
We consider two new problems regarding the impact of edge addition or removal on the modularity of partitions (or community structures) in a network. The first problem seeks to add edges to enforce that a desired partition is the partition that maximizes modularity. The second problem seeks to find the sparsest representation of a network that has the same partition with maximum modularity as the original network.