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Asgari Selected for Rising Stars 2019
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Bahar Asgari has been selected to participate in Rising Stars 2019, hosted by the University of Illinois at Urbana-Champaign (UIUC). Asgari is a Ph.D. student in the Georgia Tech School of Electrical and Computer Engineering (ECE).
Rising Stars is an intensive workshop for women graduate students and postdocs who are interested in pursuing academic careers in computer science, computer engineering, and electrical engineering. The workshop will be held from October 29-November 1 at the UIUC campus.
Asgari joined the Georgia Tech School of ECE in fall 2015. She has worked in the Computer Architecture and Systems Lab under the supervision of ECE Regents’ Professor Sudhakar Yalamanchili and Hyesoon Kim, an associate professor in the School of Computer Science.
Asgari earned both her bachelor’s and master’s degrees in Computer Engineering from Iran University of Science and Technology (IUST) in Tehran, Iran. Her Ph.D. thesis research includes, but is not limited to, designing efficient specialized hardware for compute- and memory-intensive algorithms that comprise a high level of parallelism and/or specific patterns of data reuse.
Such algorithms with a wide range of applications in on-demand fields–such as machine learning, autonomous technologies, modeling physical-world phenomena, and graph analytics–encounter performance limitations when running on the current compute platforms such as GPUs and CPUs. Specialized hardware, designed to accelerate the bottleneck-prone parts of an algorithm, continue delivering high performance for target memory- and compute-intensive applications.
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Summary
ECE Ph.D. student Bahar Asgari has been selected to participate in Rising Stars 2019, hosted by the University of Illinois at Urbana-Champaign.
Status
- Workflow Status:Published
- Created By:Jackie Nemeth
- Created:08/19/2019
- Modified By:Jackie Nemeth
- Modified:08/22/2019
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Keywords
- Bahar Asgari
- graduate students
- Rising Stars 2019
- Georgia Tech
- School of Electrical and Computer Engineering
- Computer Architecture and Systems Lab
- Hyesoon Kim
- School of Computer Science
- hardware
- compute-intensive algorithms
- memory-intensive algorithms
- parallelism
- data reuse
- machine learning
- autonomous technologies
- physical-world phenomena
- graph analytics
- GPUs
- CPUs