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Jaroslaw Zola, Ph.D.

Department of Computer Science and Engineering

Center for Analytics Research and Applications (CARA)

University at Buffalo

Davis Hall

Buffalo, NY, 14260-2500



 jzola@buffalo.edu

 +1 (716) 645-3187

www.jzola.org




SCoRe Location

We are located in</description>
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Current members of the SCoRe Group.

PI

	*  Jaroslaw Zola -- the group is lead by Dr. Jaroslaw &#039;Jaric&#039; Zola, who has decades of professional experience developing algorithms and methods for solving compute-intensive and data-driven problems in life sciences and engineering.</description>
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SMARTEn

CNS Core: Small: Rethinking the Software Architecture for Mobile DNA Analysis

To learn more, please visit the official project web page: &lt;https://cse.buffalo.edu/~jzola/smarten/&gt;.

CAREER

CAREER: Scalable Software and Algorithmic Infrastructure for Probabilistic Graphical Modeling

Probabilistic Graphical Models (PGMs) remain key machine learning technique, and are especially popular in biomedical domains. This project responds to the recognized and growing demand for scalab…</description>
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Visit this web page for more SCoRe related publications!




Selected SCoRe Posters

	*  S. Karan, J. Zola: High Performance Algorithms for Learning Exact Bayesian Networks, CSE50 Graduate Symposium 2017</description>
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Visit our GitLab repository to see latest software development activities!



	*  SCoOL A simple programming model designed to facilitate and accelerate the search space exploration phase of the optimization processes.
	*  SMARTEn Framework for mobile DNA analytics. This software suite aims to provide new ways to analyze metagenomic DNA using fully mobile setups. It is foundation for the</description>
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        <description>Scalable Computing Research








At SCoRE, we focus on accelerating scientific discovery and innovation by leveraging advanced cyberinfrastructures to enable fast and accurate exploration of large-scale biological and engineering data collections. We design algorithms, data structures and implementations that scale from multi- and many-core desktops to large clusters and edge systems. We love problems at the intersection of scalable computing, life sciences, and data-driven scientific computi…</description>
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