Klaus 2337 CRNCH Lab
266 Ferst Dr NW, Atlanta, GA 30332 USA
I am a Ph.D. student in Computer Science at the Georgia Institute of Technology advised by Dr. Vivek Sarkar in the Habanero Extreme Scale Software
Laboratory. In addition, I am a research intern at the Lawrence Berkeley National Lab, working with several researchers in the Performance and Algorithms Research Lab (PAR). My main concentration is in
High Performance Computing, and
Deep Learning (AI/DL).
I received both my B.S. in Computer Science (concentration in Artificial Intelligence and Computer Modeling) in 2021 and my M.S. in Computer Science (concentration in High Performance Computing) in 2022 from Georgia Tech.
Recently, I’ve been working on distributed graph algorithms in the actor-based programming system, distributed training for deep learning workflows (DL), hybrid communication strategies for computation intensive applications, enabling resiliency in Asynchronous Many-Task (AMT) programming models, automatic termination graph detection, approximation algorithms, and graph-based blockchain transaction forecasting.>
Distributed systems, deep learning / machine learning, parallel systems, High Performance Computing, GPU programming, communication models, cloud computing, and performance of applications in heterogeneous computing environments.
Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial ForensicsACM KDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
An Asynchronous Distributed Actor-based Approach to Jaccard Similarity for Genome Comparisons(under submission), 2023
Highly Scalable Large-Scale Asynchronous Graph Processing using ActorsIEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID), 2023
A Fine-grained Asynchronous Bulk Synchronous parallelism model for PGAS applicationsJournal of Computational Science, 2023
Diagnosing the interference on CPU-GPU Synchronization Caused by CPU Sharing in Multi-Tenant GPU CloudsIEEE International Performance, Computing, and Communications Conference (IPCCC), 2021
Anomaly Detection on Bitcoin, Ethereum Networks Using GPU-accelerated Machine Learning MethodsIEEE International Conference on Computer Theory and Applications (ICCTA), 2021