Hang Zhang

Ph.D. student

Department of Electrical & Computer Engineering (ECE)
Department of Radiology at Weill Cornell Medical College (WCM)
Cornell University
Membership:ACM, IEEE, AAAI, MICCAI, CCF member

Email: hz459[at]cornell.edu / hzhang[at]cse.cuhk.edu.hk
Office: Suite 104, 515 East 71st St, New York, NY 10021.




                                                                                                  "If not now, when ? If not you, who?"

Biography

Hang Zhang is currently a 3rd-year Ph.D. student at Department of Electrical & Computer Engineering of Cornell University, under the supervision of Prof. Yi Wang. His Ph.D. committee includes Prof. Mert R. Sabuncu and Prof. Peter Doerschuk , and he is also working closely with Prof. Thanh Nguyen and Prof. Pascal Spincemaille . He earned his Master of Philosophy (M.PHIL) degree from the Department of Computer Science & Engineering, The Chinese University of Hong Kong, under the supervision of Prof. Evangeline F. Y. Young. Before that, he received his B.Eng degree from Sichuan University (SCU) in 2015, where he worked with Prof. Xiaohai He.

His previous research in the area of Computer-aided Design (CAD) has been recognized with a Best Paper Award (Cornell ECE News) from the 26th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM'2018), and a Best Paper Award (CUHK CSE News) from the ACM International Symposium on Physical Design 2017 (ISPD'2017).

His research interests lie in machine/deep learning algorithms, theories and their applications in medical image analysis, MRI image reconstruction, intelligent computer-aided clinical tools. (He is now looking for students to work on projects involving deep learning and medical image analysis for summer research; please do not hesitate to drop an email with your CV/Resume)

Recent Updates

  • [ 04/2020 ] Our work on Quantitative Susceptibility Mapping (QSM) has been accepted to Neuro Image and International Conference on Medical Imaging with Deep Learning (MIDL) 2020.

  • [ 06/2019 ] Our paper RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation has been early accepted to MICCAI 2019.

  • [ 01/2019 ] Our Quantitative Research Club, Cornell Quant, was founded formally under the supervision of Prof. Sumanta Basu. Cornell Quant focus on cutting-edge multidisplines involving quantititave computations. Areas include but not limited to deep/machine learning and its applications in finance, data mining etc. Interested students/professors/sponsors, please do not hesitate to contact.

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  • [ 09/2018 ] Our BigRedLidar dataset regarding point cloud segmentation will be released soon via our website.

  • [ 05/2018 ] Our paper Fast and Accurate Estimation of Quality of Results in High-Level Synthesis with Machine Learnin has won Best Paper Award at FCCM2018 (News link: News)

  • Archived updates

Papers

Publications

Manuscripts

Selected Honors & Awards

HP Fellowship at Cornell University, 2018.
Best Paper Award at FCCM' 2018.
Merit-based Graduate School Fellowship at Cornell University, 2017.
Best Paper Award at ISPD' 2017.
Second Place Award in CAD contest at ISPD, held by Xilinx, 2016.
The Championship Award of CAD Contest at ICCAD, held by Stanford & IBM, 2015.
Full Postgraduate Studentship at CUHK, 2015-2017.

Excellent Bachelor Thesis Award at SCU (Top 1%), 2015.
Talents Project at Wu Yuzhang Honors College of SCU (Top 0.1%), 2013-2015.

Services

Teaching/Grading

TA  2015-2016  fall  CUHK  ENGG 2440A  Discrete Mathematics for Engineers
Instructor: Bogdanov Andrej

Grader  2018-2019  fall  Cornell  ECE 2720  Data Science for Engineers
Instructor: Aaron Wagner

Program Committee Members

ACM International Conference on AI in Finance (ICAIF), 2020

Reviewers

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020

 

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