Multiple CS PhD positions with full financial support at UT Dallas
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Multiple PhD positions with full financial support are now available (starting from Fall 2018) with Dr. Cong Liu in the department of Computer Science at UT-Dallas.
Dr. Liu’s research focuses on the areas of Real-Time Systems, GPGPU, and Data-driven Cyber-Physical Systems. According to csrankings.org, UT-Dallas is ranked No. 8 nationally in the general area of embedded & real-time systems due to Dr. Liu’s contribution. His supervised PhD students are publishing at top conferences such as RTSS and RTAS, and interning at industry research labs including IBM T.J. Watson research center and HuaWei-US research laboratory. His graduated students are now working in famous companies, such as IBM and Amazon.
Recently, several of his PhD students got awards such as the Outstanding Paper Award at RTSS’17 and the Top 10 Papers at INFOCOM’17. His research is funded by both NSF (including the prestigious NSF CAREER award) and industry. For more information, please visit: utdallas.edu/~cong
UT-Dallas is a fast-growing Research-I University, located in the heart of Dallas area, Texas. Its computer science program is ranked top 70 according to the latest US news ranking. Admitted PhD students will receive rather competitive stipend at UT-Dallas CS (over $2000 per month, considering there is no state tax in Texas and the relatively low living cost in Dallas area).
There are currently three general projects to be worked on:
1. Predictable GPGPU computing, e.g., how to ensure predictable and timely processing of DNN workloads in autonomous driving systems adopting GPU-accelerated platforms such as the NVIDIA Drive PX2?
2. Real-time multicore resource management, e.g., how to design efficient scheduling algorithms whose timing correctness can be analytically verifiable on the current and future complex heterogeneous multicore platforms?
3. Data-driven design of cyber-physical systems, e.g., given access to real-world datasets on ShenZhen’s electric taxi fleets or Beijing’s Mobike bike sharing systems, how to identify potential shortcomings of current system design through mining and analyzing the dataset, and then develop smarter and practical solutions accordingly?
Dr. Liu is particularly interested in working with both 'provers' and 'hackers' (i.e., strong theory-inclined students and strong systems students), as you may tell from the above-mentioned three research projects that require different expertise. If you are interested in working together, please send your resume, transcripts, and everything else (e.g., sample publications or open source contributions) that you believe will help your application as attachments in a single email to:[email protected]
Dr. Liu’s research focuses on the areas of Real-Time Systems, GPGPU, and Data-driven Cyber-Physical Systems. According to csrankings.org, UT-Dallas is ranked No. 8 nationally in the general area of embedded & real-time systems due to Dr. Liu’s contribution. His supervised PhD students are publishing at top conferences such as RTSS and RTAS, and interning at industry research labs including IBM T.J. Watson research center and HuaWei-US research laboratory. His graduated students are now working in famous companies, such as IBM and Amazon.
Recently, several of his PhD students got awards such as the Outstanding Paper Award at RTSS’17 and the Top 10 Papers at INFOCOM’17. His research is funded by both NSF (including the prestigious NSF CAREER award) and industry. For more information, please visit: utdallas.edu/~cong
UT-Dallas is a fast-growing Research-I University, located in the heart of Dallas area, Texas. Its computer science program is ranked top 70 according to the latest US news ranking. Admitted PhD students will receive rather competitive stipend at UT-Dallas CS (over $2000 per month, considering there is no state tax in Texas and the relatively low living cost in Dallas area).
There are currently three general projects to be worked on:
1. Predictable GPGPU computing, e.g., how to ensure predictable and timely processing of DNN workloads in autonomous driving systems adopting GPU-accelerated platforms such as the NVIDIA Drive PX2?
2. Real-time multicore resource management, e.g., how to design efficient scheduling algorithms whose timing correctness can be analytically verifiable on the current and future complex heterogeneous multicore platforms?
3. Data-driven design of cyber-physical systems, e.g., given access to real-world datasets on ShenZhen’s electric taxi fleets or Beijing’s Mobike bike sharing systems, how to identify potential shortcomings of current system design through mining and analyzing the dataset, and then develop smarter and practical solutions accordingly?
Dr. Liu is particularly interested in working with both 'provers' and 'hackers' (i.e., strong theory-inclined students and strong systems students), as you may tell from the above-mentioned three research projects that require different expertise. If you are interested in working together, please send your resume, transcripts, and everything else (e.g., sample publications or open source contributions) that you believe will help your application as attachments in a single email to:[email protected]
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