Home

Dr. Yanzhi Wang

Associate Professor and Faculty Fellow

Department of Electrical & Computer Engineering, College of Engineering,

Khoury College of Computer Science (Affiliated),

Northeastern University

B.S. (Tsinghua), Ph.D. (University of Southern California)

329 Dana, 360 Huntington Avenue
Boston, MA 02115
Phone: 617.373.8805
Email: yanz.wang@northeastern.edu

Youtube channel and Bilibili channel:


About:

Yanzhi Wang is currently an Associate Professor and Faculty Fellow in the Department of Electrical and Computer Engineering, and Khoury College of Computer Science (Affiliated) at Northeastern University. He has received his Ph.D. Degree in Computer Engineering from University of Southern California (USC) in 2014, under the supervision of Prof. Massoud Pedram. He received the Ming Hsieh Scholar Award (the highest honor in the EE Dept. of USC) for his Ph.D. study. He received his B.S. Degree in Electronic Engineering from Tsinghua University in 2009 with distinction from both the university and Beijing city.

Dr. Wang’s current research interests are the following. His group works on both algorithms and actual implementations (mobile and embedded systems, FPGAs, circuit tapeouts, GPUs, emerging devices, and UAVs).

  • Real-time and energy-efficient deep learning and artificial intelligence systems
  • Model compression and mobile acceleration of deep neural networks (DNNs)
  • Deep learning acceleration for autodriving
  • Neuromorphic computing and non-von Neumann computing paradigms
  • Cyber-security in deep learning systems

For a brief list of technical achievements, his research (i) achieves and maintains the highest model compression rates on representative DNNs since 09/2018 (ECCV18, ASPLOS19, ICCV19, ISLPED19, ASP-DAC20, AAAI20-1, AAAI20-2, DAC21, CVPR21, ICLR22, etc.), (ii) achieves, for the first time, real-time and fastest execution of representative large-scale DNNs on an off-the-shelf mobile device (ASPLOS20, AAAI20, ICML19, IJCAI20, ECCV20, DAC20, AAAI21-1, AAAI21-2, NeurIPS21, PLDI21, MICRO22, CACM, TPAMI, etc.), (iii) achieves the highest performance/energy efficiency in DNN implementations on many platforms (FPGA19, ISLPED19 , AAAI19, HPCA19, ISSCC19, ASP-DAC20 , DATE20, AAAI20, PLDI20, ICS20, IJCAI20, PACT20, HPCA21, JSSC21). It is worth mentioning that his work on AQFP superconducting based DNN inference acceleration, which is validated through cryogenic testing, has by far the highest energy efficiency among all hardware devices (ISCA19, ICCAD18, ICCAD20, DAC22).

His research works have been published broadly in top conference and journal venues, ranging from (i) EDA, solid-state circuit and system conferences such as DAC, ICCAD, DATE, ISLPED, FPGA, LCTES, ISSCC, RTAS, etc., (ii) architecture and computer system conferences such as ASPLOS, ISCA, MICRO, HPCA, CCS, VLDB, PLDI, ICS, CGO, PACT, INFOCOM, ICDCS, etc., (iii) machine learning algorithm conferences such as AAAI, CVPR, NeurIPS, ICML, ICCV, ICLR, IJCAI, ECCV, KDD, ACM MM, ICDM, etc., and (iv) IEEE and ACM transactions (including Communications of ACM, Proc. of IEEE, JSSC, TPAMI, etc.) and Nature and Science series journals. He ranks No. 2 in CSRankings at Northeastern University in the past 10 years, and around No. 35 throughout the U.S. His research works have been cited for above 17,200 times according to Google Scholar with H-index 65.

He has received six Best Paper or Top Paper Awards (ISLPED’14, IEEE CLOUD’14, ISVLSI’14, ICASSP’17, KDD Workshop’19, ICLR Workshop’21), one Communications of ACM Featured Article (Article) (Interview Video), has another 12 Best Paper Nominations (GLS-VLSI’13, IEEE TCAD’13, ASP-DAC’15, ISLPED’17, ASP-DAC’17, ISQED’18, ASP-DAC’18, DATE’19, ICCAD’19, DATE’20, DATE’21, ICLR Workshop’22) and four Popular Papers in IEEE TCAD. He received the U.S. Army Research Office Young Investigator Award, IEEE TC-SDM Early Career Award, Faculty Fellow Award, Asia Pacific Signal and Information Processing Association (APSIPA) Distinguished Industrial Leader award, Constantinos Mavroidis Translational Research Award, Martin W. Essigmann Excellence in Teaching Award, etc. Besides, his group has received Massachusetts Acorn Innovation Award, Google Equipment Research Award, MathWorks Faculty Award, MIT Tech Review TR35 China Finalist, Ming Hsieh Scholar Award, Young Student Support Award of DAC (for himself and six of his Ph.D. students), DAC Service Award, etc. His group and students have received first place in ISLPED Design Contest twice (2012, 2020), first place in Student Research Competition at CGO 2021, and awards in multiple other contests such as Low Power Computer Vision Challenge 2019 and NeurIPS MicroNet Challenge 2019.

Yanzhi has delivered over 130 invited technical presentations on research of real-time and efficient deep learning systems. His research works have been broadly featured and cited in around 600 media, including Boston Globe, Communications of ACM (three times), VentureBeat, The Register, Medium, The New Yorker, Wired, NEU News, Import AI, Italian National TV, MRS TV, Quartz, ODSC, MIT Tech Review, TechTalks, IBM Research Blog, ScienceDaily, AAAS, CNET, ZDNet, New Atlas, Tencent News, Sina News, to name a few.

The first Ph.D. student of Yanzhi, Caiwen Ding, has graduated in June 2019, and has become a tenure-track assistant professor in Dept. of CSE at University of Connecticut. The second Ph.D. student, Ning Liu, will start as a superstar employee at DiDi AI Research (DiDi Inc.). The third Ph.D. student, Ao Ren, is currently joining School of CS at Chongqing University as full professor (with tenure). The fourth Ph.D. student, Ruizhe Cai, has joined Facebook Infrastructure. The fifth Ph.D. student, Sheng Lin, has joined Tencent U.S. as research scientist. The postdoc/visiting scholar, Chen Pan, has joined Dept. of CSE at Texas A&M Corpus Christi, as tenure-track assistant professor. His co-advised Ph.D. student, Tianyun Zhang, has joined Dept. of ECE at Cleveland State University as assistant professor. Recently, his Ph.D. student Xiaolong Ma joined Dept. of ECE at Clemson University as assistant professor, and Ph.D. student Geng Yuan joined Dept. of CS at University of Georgia as assistant professor.

Ph.D., Postdoc, and Visiting Scholar/Students Positions Available: Northeastern University has been rising thanks to the strong leadership and efforts from faculty members. The university is located in between the famous Museum of Fine Arts (MFA) and Boston Symphony and Berkelee College of Music, the Best Location at Boston! Please apply to NEU.


CoCoPIE (A Representative Contribution):

Assuming hardware is the major constraint for enabling real mobile intelligence, the industry has mainly dedicated their efforts to developing specialized hardware accelerators for machine learning inference. Billions of dollars have been spent to fuel this intelligent hardware race. We challenge this assumption. By drawing on a recent real-time AI optimization framework CoCoPIE, it maintains that with effective compression-compiler co-design, it is possible to enable real-time artificial intelligence (AI) on mainstream end devices without special hardware.

The principle of compression-compilation co-design is to design the compression of Deep Learning Models and their compilation to executables in a hand-in-hand manner. This synergistic method can effectively optimize both the size and speed of Deep Learning models, and also can dramatically shorten the tuning time of the compression process, largely reducing the time to the market of AI products. CoCoPIE holds numerous records on mobile AI: the first time to support all kinds of DNNs including CNNs, RNNs, transformer and language models, etc.; the fastest DNN pruning and acceleration framework, up to 180X faster compared with current frameworks such as TensorFlow-Lite; a majority of representative DNNs and applications can be executed in real-time, for the first time, in off-the-shelf mobile devices; CoCoPIE framework on general-purpose mobile devices even outperforms a number of representative ASIC and FPGA solutions in terms of energy efficiency and/or performance.

More Info about CoCoPIE: Official webpage https://www.cocopie.ai/; CoCoPIE Youtube Channel here and Bilibili Channel here.



Recent News:  

  • 12/2023 [Award] Yanzhi receives the Constantinos Mavroidis Translational Research Award.
  • 10/2023 [Award] Yanzhi receives Top 100 Chip Achievement Award.
  • 10/2023 [Award] Yanzhi receives the Highly Cited Scholar from Stanford University.
  • 09/2023 [Award] Ph.D. student Peiyan Dong receives the EECS Rising Star Award, 2023.
  • 05/2023 [Grant] We are awarded an NSF CSR grant for the continual learning. Thanks NSF!
  • 04/2023 [Student] Ph.D. student Geng Yuan has accepted an offer as a Tenure-Track Assistant Professor in Department of Computer Science at University of Georgia, starting at Fall 2023.
  • 01/2023 [Award] Ph.D. student Zhengang Li receives the ACM Student Research Competition 1st Place at ASP-DAC 2023.
  • More news

Research Sponsors: