Qian ZhangMy name is pronounced "ch-i-an j-ah-ng"
Computer Science and Engineering
University of California, Riverside
Email: qzhang AT cs.ucr.edu
I have moved to University of California, Riverside as an assistant professor in July 2022. This website is no longer maintained. Please check my new homepage.
I am a Tenure-Track Assistant Professor in Computer Science and Engineering at University of California, Riverside. Prior to that, I was a Postdoctoral Researcher at UCLA during 2019-2022. I worked with Prof. Miryung Kim on software developer tools for democrotizing heterogeneous computing. I got my Ph.D. from The Chinese University of Hong Kong in 2018, adviced by Prof. Johnny Qiang Xu.
My research lies at the intersection of software engineering, heterogeneous hardware design, and data-intensive scalable computing (DISC) systems. I have been selected as one of the eight MIT EECS rising stars in Systems (broadly defined).
- May 2022: I am serving on the ICPADS 2022 program committee.
- May 2022: I am serving on the FSE 2022 Tool Demonstration Track program committee.
- Jan 2022: I am serving on the ICSME 2022 program committee.
- Dec 2021: I am serving on the FUZZING'22 program committee. This event is co-located with NDSS 2022.
- Nov 2021: Our paper on C to HLS-C transpiler is accepted to ASPLOS 2022!
- Oct 2021: I was invited to give a talk on efficient fuzz testing at Technology Innovation Institute, Abu Dhabi.
- Sep 2021: I am chairing the Smell / Debt session in ICSME 2021!
- Aug 2021: Selected as one of the EECS Rising Stars, 2021, hosted by MIT!
- Jul 2021: Our paper on differential testing for quantum software stacks is accepted to ASE 2021!
- Jun 2021: NSF funded my research on reinventing fuzz testing for data and compute intensive applications! I am participating as a senior personnel.
- May 2021: Our paper on fuzz testing for heterogeneous applications is accepted to FSE 2021!
- Jan 2021: I am serving on the ICSME 2021 program committee!
Emerging hardware, like FPGAs and quantum circuits, is shaping the future of heterogeneous computing; however, the use of such extraordinary computing power is restricted to a few software developers with microprocessor expertise.
The vision of my research is to democratize the use of heterogeneous computing with re-designed developer productivity tools. I am particularly interested in developing techniques that lower the barriers of porting traditional software to heterogeneous platforms, and making emerging hardware resources equally accessible across a diverse range of developers. This includes research over reinventing testing, refactoring, program transformation, and interactive programming tools.
- HeteroGen: Transpiling C to Heterogeneous HLS Code with Automated ASPLOS'22
Test Generation and Program RepairAcceptance Rate: 20%
by Qian Zhang, Jiyuan Wang, Harry Xu, Miryung Kim
The 27th ACM International Conference on Architectural Support for
Programming Languages and Operating Systems, 13 pages, 2022
- QDiff: Differential Testing of Quantum Software Stacks ASE'21
by Jiyuan Wang, Qian Zhang, Harry Xu, Miryung KimAcceptance Rate: 20%
The 36th IEEE/ACM International Conference on Automated
Software Engineering, 13 pages, 2021
- HeteroFuzz: Fuzz Testing to Detect Platform Dependent Divergence ESEC/FSE'21
by Qian Zhang, Jiyuan Wang, Miryung KimAcceptance Rate: 24.5%
The 29th ACM Joint European Software Engineering Conference
and Symposium on the Foundations of Software Engineering, 13 pages, 2021
- Efficient Fuzz Testing for Apache Spark Using Framework AbstractionICSE'21 Demonstration
by Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung KimAcceptance Rate: 37%
The 43rd IEEE/ACM International Conference on Software Engineering,
4 pages, Demonstrations, 2021
- BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework AbstractionASE'20
by Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, Miryung KimAcceptance Rate: 22.5%
The 35th IEEE/ACM International Conference on Automated
Software Engineering, 13 pages, 2021 [slides][video][tool]
- HeteroRefactor: Refactoring for Heterogeneous Computing with FPGA ICSE'20
by Jason Lau*, Aishwarya Sivaraman*, Qian Zhang*, Muhammad Ali Gulzar,Acceptance Rate: 20.9%
Jason Cong, Miryung Kim
[* are equal co-first authors, ordered alphabetically by their last names.]
The 42nd IEEE/ACM International Conference on Software Engineering,
13 pages, 2020 [slides][video][tool]
- ApproxIt: A Quality Management Framework of Approximate Computing for Iterative Methods TCAD Journal'20
by Qian Zhang, Qiang Xu
The IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020
- ARSketch: Sketch-Based User Interface for Augmented Reality Glasses ACM MM'20
by Zhaohui Zhang*, Haichao Zhu*, Qian ZhangAcceptance Rate: 27%
[* are equal co-first authors, ordered alphabetically by their last names.]
The 28th ACM International Conference on Multimedia, 9 pages, 2020
- Lookup Table Allocation for Approximate Computing with Memory Under Quality Constraints DATE'18
by Ye Tian, Qian Zhang, Ting Wang, Qiang XuAcceptance Rate: 24%
The Design, Automation and Test in Europe Conference and Exhibition, 2018
- ApproxLUT: A Novel Approximate Lookup Table-Based AcceleratorICCAD'17
by Ye Tian, Ting Wang, Qian Zhang, Qiang XuAcceptance Rate: 26%
The IEEE/ACM International Conference on Computer-Aided Design, 2017
- ApproxQA: A Unified Quality Assurance Framework for Approximate ComputingDATE'17
by Ting Wang, Qian Zhang, Qiang XuAcceptance Rate: 24%
The Design, Automation and Test in Europe Conference and Exhibition, 2017
- ApproxEigen: An Approximate ComputingTechnique for Large-Scale Eigen-DecompositionICCAD'15
by Qian Zhang, Ye Tian, Ting Wang, Feng Yuan, Qiang XuAcceptance Rate: 22.6%
The IEEE/ACM International Conferenceon Computer-Aided Design, 2015
- ApproxANN: An Approximate ComputingFramework for Artificial Neural NetworkDATE'15
by Qian Zhang, Ting Wang, Ye Tian, Feng Yuan, Qiang XuAcceptance Rate: 22.4%
The Design, Automation and Test in Europe Conference and Exhibition, 2015
- ApproxIt: An Approximate Computing Framework for Iterative MethodsDAC'14
by Qian Zhang, Feng Yuan, Rong Ye, Qiang XuAcceptance Rate: 22.1%
The IEEE/ACM Design Automation Conference, 2014
- ApproxMA: Approximate Memory Accessfor Dynamic Precision Scaling GVLSI'15
by Ye Tian, Qian Zhang, Ting Wang, Feng Yuan, Qiang Xuinvited
The Great Lakes Symposium on VLSI, 2015
- On Effective and Efficient Quality Management for Approximate ComputingISLPED'16
by Ting Wang, Qian Zhang, Nam Sung Kim, Qiang XuAcceptance Rate: 32%
The IEEE/ACM International Symposium on Low Power Electronicsand Design, 2016
- On Resilient Task Allocation and Scheduling with Uncertain Quality CheckersASPDAC'17
by Qian Zhang, Ting Wang, Qiang XuAcceptance Rate: 30%
The IEEE/ACM Asia and South Pacific Design Automation Conference, 2017
- ApproxMap: On Task Allocationand Scheduling for Resilient ApplicationsASPDAC'16
by Yi Juan, Qian Zhang, Ye Tian, Ting Wang, Weichen Liu, Edwin H.-M. Sha, Qiang XuAcceptance Rate: 31%
The IEEE/ACM Asia and South Pacific DesignAutomation Conference, 2016
- On hybrid memory allocation for FPGA behavioral synthesisFPGA'14
by Qian Zhang, Chenfei Ma, Qiang Xuposter track
The ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2014
- Session Chair:
ICSME Research Track, Smell/Debt session, 2021
- Program Committee:
ICSME Research Track, 2021
SIGDA Student Research Forum at ASP-DAC, 2020, 2021, 2022
- Journal Reviewer:
IEEE Transactions on Software Engineering and Methodology (TOSEM), 2021
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2019, 2020, 2021
IEEE Transactions on Computers (TC), 2019
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2019
- External Reviewer: ICFPT'2013, ICCD'2013, ICCD'2014, AC'2016, DFT'2017
Teaching and Mentoring
- Teaching Assistant:
CUHK ENGG 5101 Advanced Computer Architecture Spring 2015, Spring 2016
CUHK CMSC 5719 Seminar Fall 2014
CUHK CENG 3420 Computer Organization and Design Spring 2014
CUHK ENGG 2020 Digital Logic and Systems Fall 2012, Fall 2013
CUHK ENGG 1410b Engineering Mathematics I Spring 2013
CUHK ENGG 1000 IT Foundation 2012-2016
I have been lucky to work with the following undergraduate and graduate students at CUHK and UCLA. Female students are highlighted in bold.
- Jason Teoh, PhD student at UCLA: fuzz testing for detecting performance issues in Apache Spark.
- Jiyuan Wang, PhD student at UCLA: testing for quantum computing and heterogeneous computing.
- Ayushi Agarwal, master student at UCLA: input generation for debloating Java bytecode.
- Aditya Jain, master student at UCLA: input generation for debloating Java bytecode.
- Harini Suresh, master student at UCLA: detecting numerical errors in python data science.
- Apoorv Garg, master student at UCLA: detecting numerical errors in python data science.
- Xilai Zhang, master student at UCLA, now at Google.
- Aishwarya Sivaraman, PhD student at UCLA.
- Ye Tian, PhD student at CUHK, now at HiSilicon.
- Juan Yi, visiting PhD student at CUHK, now at Tencent.
- Minhao Liu, undergraduate student at CUHK, now PhD student at CUHK.
- Chenfei Ma, master student at CUHK, now at Wells Fargo.