I am Clark(Yao) Fu, a PhD student of the
Computer and Data Sciences Department at Case Western Reserve University.

I'm a 1st year PhD student in the Computer and Data Sciences(CDS) department at Case Western Reserve University(CWRU) working with Prof.Li in his Network, Energy, Security, and big daTa(NEST) research group. I'm currently interested in security and privacy issues in blockchain such as detecting vulnerability and bugs of smart contracts using Deep Learning techniques.

Before reaching CWRU, I obained my master degree of Electrical and Computer Engineering (ECE, Machine Learning and Data Science track) from University of Southern California(USC), where I have worked as a research member of Data Science Lab, Hardware Accelerated Learning(HAL) Research Group, and Neuro Image Computing Research(NICR) Group. During my academical life at USC, I was devoted to using PyTorch to focus on cutting-edge topics of applied Machine Learning such as missing data imputation, privacy study on knowledge distillation, and tractography filtering.

What's more, I received my Bachelor's degree on Automation from Nanjing University of Science and Technology. I once spent a fall semester as a transfer graduate student at ECE Department of North Carolina State University(NCSU), where I attained familiarity with probability and improved my coding ability. My high schoold is Chengdu NO.7 High School(成都市第七中学).

Education

• Case Western Reserve University(CWRU), Cleveland, OH                               Aug. 2022 – May 2027 (Expected)
      Doctor of Philosophy in Computer and Data Sciences, current GPA /4.00
• University of Southern California (USC), Los Angeles, CA                               Jan. 2020 – Dec. 2021 (Graduated)
      Master of Science in Electrical and Computer Engineering, totel GPA 4.00/4.00
• North Carolina State University (NCSU), Raleigh, NC                                        Aug. 2019 - Dec. 2019 (Transfer)
      Master of Science in Electrical and Computer Engineering, total GPA 4.00/4.00
• Nanjing University of Science and Technology (NJUST), Nanjing, China         Sep. 2015 - Jun. 2019 (Graduated)
      Bachelor of Engineering in Automation, total GPA 3.39/4.00 (43/175)

Publications

Journal

Conference

[1] Souvik Kundu, Yao Fu, Bill Ye, Peter A. Beerel, and Massoud Pedram. Towards Adversary Aware Non-Iterative Model Pruning Through Dynamic Network Rewiring of DNNs. Association for Computing Machinery (ACM), August 2021.
[2] Souvik Kundu, Qirui Sun, Yao Fu, Massoud Pedram, and Peter A. Beerel. Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation. Conference and Workshop on Neural Information Processing Systems (NeurIPS), May 2021.
[3] Sanmukh R. Kuppannagari, Yao Fu, Chung Ming Cheung, and Viktor K. Prasanna. Spatio-Temporal Missing Data Imputation for Smart Power Grids. 3rd International Workshop on Applied Machine Learning for Intelligent Energy Systems (AMLIES 2021), May 2021.
[4] Souvik Kundu, Qirui Sun, Yao Fu, Peter Anthony Beerel, and Massoud Pedram. Skeptical Student: Diminishing the Effect of Nasty Teacher in Knowledge Distillation. 1st Responsible Computer Vision workshop at CVPR, April 2021.

Skills

• Programming Languages: Python, Java, MATLAB, C/C++, JavaScript, Solidity R, SQL, HTML, CSS
• Tools: PyTorch, TensorFlow, Keras, OpenCV, Scikit-Learn, Numpy, Pandas, Git, Linux/Unix commands
• IDEs: PyCharm, Jupyter Notebook, IntelliJ IDEA, VS code, Visual Studio

Courses

USC

• EE-510: Linear Algebra for Engineering. (my grade: A)
• EE-546: Mathematics of High-Dimensional Data. (my grade: A)
• EE-559: Machine Learning 1: Supervised Methods - basics of Supervised classification and regression. (my grade: A)
• EE-569: Introduction to Digital Image Processing. (my grade: A)
• EE-660: Machine Learning 2: Mathematical Foundations and Methods - Semi-supervised, and unsupervised machine learning; domain adaptation and transfer learning; and techniques for interpretable machine learning. Feasibility of learning, model complexity, and performance (error) on unseen data. (my grade: A)
• CSCI-455x: Introduction to Programming System Design - basics of Java, C++ and Unix/Linux. (my grade: A)
• CSCI-570: Analysis of Algorithms. (my grade: A)

NCSU

• ECE-513: Digital Signal Processing. (my grade: A)
• ECE-514: Random Process - basics of probability, statistics, and random process. (my grade: A)
• ECE-558: Digital Imaging Syetems - basics of digital image processing and computer vision. (my grade: A)

Honors

• MS Honors Program: USC Ming Hsieh Department of Electrical Engineering, Fall 2021.

Contact

• Email address: yxf484@case.edu
• Google Scholar
• LinkedIn
• Github
• Twitter