Hi, I'm Scott. I'm currently an assistant research scientist in the Computer Science & Engineering Department at Texas A&M University, where I'm working with Dr. Tim Davis on graph analytics problems. I have a background in chemical engineering, and I worked as an Optimization Engineer at Shell for two years. I’m also a licensed Professional Engineer.
My research interests include graph analytics, scientific software, high-performance computing, and software engineering. I also apply numerical optimization algorithms to new and interesting problems, including those listed above. In short, I enable high-performance and large-scale data science and decision-making.
Q. Chemical engineering and computer science? That’s an uncommon combination.
A. You’re right, but you might also be surprised to hear how often my background in chemical engineering helps in my research. I’ve applied numerical optimization to infectious disease modeling, crude oil scheduling, and graph partitioning - and my optimization expertise came from my life as a chemical engineer.
Q. How do you pronounce your last name?
A. koh-LOH-jay. It's Polish for Wheelwright. In proper Polish, it's spelled Kołodziej, and pronounced koh-WOH-jay. If you pronounce the dz like a j, it's not as big of a stretch as it first looks.
2015 - 2019
Texas A&M University, College Station, Texas
Doctor of Philosophy in Computer Science
Advised by Dr. Timothy Davis
Created and implemented novel hybrid algorithmic and heuristic approaches for computing high quality edge cuts and vertex separators in graphs using continuous bilinear and mixed-integer linear optimization formulations.
2010 - 2012
2006 - 2010
Texas A&M University, College Station, Texas
Bachelor of Science in Chemical Engineering, magna cum laude
Mastered the fundamentals of chemical engineering. Sought out research projects in numerical optimization, carbon capture, and biofuels.
2012 - 2014
Shell, Houston, TX
Optimization Engineer in the Process Automation, Control, and Optimization (PACO) group.
While at Shell, I worked in dynamic process simulation. We answered questions and troubleshot problems that couldn't be addressed using steady-state simulation. I contributed to projects involving process safety, energy efficiency, and multi-phase flow.
I also managed reliability, availability, and maintainability (RAM) studies. We used Monte Carlo simulations to estimate the expected downtime of projects, as well as to help inform project decision-making.
2015 - 2019
Optimization Approaches to Graph Partitioning
For my doctoral research, I developed a highly efficient graph partitioning library using continuous and discrete optimization techniques.
Parallel processing of graphs and finite element meshes, sparse matrix orderings, and VLSI chip layouts all use graph partitioning in some form or another.
I've gained a lot of experience using static analysis tools, code coverage, continuous integration, and Git to better engineer the codebase, which is a mix of C and C++ with a MATLAB interface.
Mongoose is available on GitHub.
Davis, T.A., Hager, W.W., Kolodziej, S.P., Yeralan, S.N., Mongoose, A Graph Coarsening and Partitioning Library, ACM Transactions on Mathematical Software.
2015 - Present
SuiteSparse Matrix Collection Web Application
This project started as a team project for the Software Engineering course. We built a Ruby on Rails makeover of a previous website that allows you to browse Dr. Tim Davis's SuiteSparse Matrix Collection, a collection of almost 3000 sparse matrices cataloged by size, sparsity, and other properties.
Kolodziej, S.P., Aznaveh, M., Bullock, M., David, J., Davis, T.A., Henderson, M., Hu, Y., and Sandstrom, R., The SuiteSparse Matrix Collection Website Interface, Journal of Open Source Software 4 (35), 1244, https://doi.org/10.21105/joss.01244.
2011 - 2012
Multiperiod Blending Problem
As a graduate student at Carnegie Mellon University, I developed a better method to solve a class of time-dependent blending optimization problems common to the process industries. Applying this approach led to more than 100x improvement in performance.
Kolodziej, S.P., Castro, P.M., and Grossmann, I.E., Global Optimization of Bilinear Programs with a Multiparametric Disaggregation Technique, Journal of Global Optimization 57 (4), 1039-1063 (2013), http://dx.doi.org/10.1007/s10898-012-0022-1.
Kolodziej, S.P., Grossmann, I.E., Furman, K.C., and Sawaya, N.W., A Discretization-Based Approach for the Optimization of the Multiperiod Blend Scheduling Problem, Computers & Chemical Engineering 53, 122-142 (2013), http://dx.doi.org/10.1016/j.compchemeng.2013.01.016.
2015 - 2016
As President of the Computer Science and Engineering Graduate Student Association, I worked with my team of officers to improve the culture of the Computer Science and Engineering department.
We launched a new biweekly social in the department and invited the faculty to it, and it's been so successful that the department agreed to double the CSEGSA budget.
We also conducted a graduate student climate survey, created a volunteer pool to help out in the department, launched a new website, and held a town hall to better understand the concerns of the graduate student body.
Shell PACO Group HSSE Focal Point
During my time at Shell, I was the Health, Safety, Security, and Environment (HSSE) Focal Point for my group of ~50 engineers. I coordinated HSSE-related programs, such as our HSSE incident reporting database.
2010 - 2012
Carnegie Mellon University AIChE Graduate Advisor
As a graduate student at CMU, I joined the American Institute of Chemical Engineers (AIChE) student chapter there. I encouraged their leadership team to have more industry speakers, and helped them procure industry contacts from the faculty.
Graph Challenge Champions, 2019 IEEE High Performance Extreme Computing Conference (HPEC) Graph Challenge
Awarded for “Write Quick, Run Fast: Sparse Deep Neural Network in 20 Minutes of Development Time via SuiteSparse: GraphBLAS.”
ACM Student Research Competition Grand Finals - 3rd Place, Graduate Category, 2019 ACM Student Research Competition.
Awarded for “Empirical Assessment of Software Documentation Strategies: A Randomized Controlled Trial.” Recognized at the ACM Awards Banquet in San Francisco, California, on June 16, 2019.
ACM Student Research Competition - 1st Place, Graduate Category, SIGCSE 2019, Minneapolis, Minnesota.
Awarded for “Empirical Assessment of Software Documentation Strategies: A Randomized Controlled Trial.”
Travel Funding for the 9th Annual Scientific Software Days, The University of Texas
Received full travel support to attend and present a poster at SciSoft Days at the University of Texas at Austin.
Graduate Leadership Excellence Award, Computer Science & Engineering Department, Texas A&M University
Awarded for excellence in leading the Computer Science & Engineering Graduate Student Association (CSEGSA) and introducing biweekly graduate student socials.
Vantage Award, Shell PACO Group, Houston, TX
Contributed to streamlining the PACO Group Shell Graduate Program.