Hello World! I'm David Krasowska.
david:~$ summary
David Krasowska is a Ph.D. student at Northwestern University, advised by Dr. Peter Dinda. His research journey began during his undergraduate studies at Clemson University with Dr. Jon C. Calhoun. He collaborated with Argonne National Laboratory under Dr. Julie Bessac and Dr. Franck Cappello to explore lossy compression for optimizations in HPC scientific applications. This research has led to publications and awards. He received the DOE Computational Science Graduate Fellowship to fund his graduate studies. Currently, David is exploring performance portability for data centric architectures. He is working on Legion with Dr. Pat McCormick at Los Alamos National Laboratory.
david:~$ location
Chicago, IL
david:~$ education
Northwestern University (2023-Current) | Computer Science Ph.D. Student
Clemson University (2019-2022) | Computer Engineering BS | GPA: 3.7
david:~$ interests
Running. Biking. Hiking. Outdoors. Coding. Friendship. Achievement.
david:~$ number
+1 (843) 283-7758

Undergraduate Student Researcher
Clemson University
January 2022 - May 2022
Region of interest compressibility research in collaboration with Los Alamos National Laboratory. Determining methods to achieve the highest compressibility for images from a Laser Powdered Fusion EOS X printer in the SIGMA division within LANL.

High Performance Computing Creative Inquiry
Clemson University
June 2021 - December 2022
Participant in the Student Cluster Competition (SCC) at SC '21 and INDY SCC at SC '22. Collaboration with Dell and Intel to build a cluster with greatest performance per watt. Set up a distributed cluster with package managers, applications, and benchmarks. Gained knowledge of parallel computing with MPI.
Django TRACE Camp Student
Clemson University
June 2020
Bootcamp developed multiple projects using Django. Created a chat system, a blog site, and a portfolio. Hosted with AWS Lightsail using NGINX server.

Peer-Reviewed Publications
2023   PDF
A. Ganguli, R. Underwood, J. Bessac, D. Krasowska, J. C. Calhoun, S. Di, and F. Cappello. "A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression," IEEE International Conference on Cluster Computing (CLUSTER), Santa Fe, NM, 2023, pp. 247-258, doi:10.1109/CLUSTER52292.2023.00028
2023   PDF
R. Underwood, J. Bessac, D. Krasowska, J. C. Calhoun, S. Di, and F. Cappello. "Black-box statistical prediction of lossy compression ratios for scientific data," The International Journal of High Performance Computing Applications (IJHPCA), 2023, pp. 412-433, doi:10.1177/10943420231179417
2021   PDF Slides
D. Krasowska, J. Bessac, R. Underwood, J. C. Calhoun, S. Di, and F. Cappello. "Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets," 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7), St. Louis, MO, USA, 2021, pp. 47-53, doi:10.1109/DRBSD754563.2021.00011