Ka-Ho Chow

Ph.D. Candidate [LinkedIn]
School of Computer Science
College of Computing
Georgia Tech
Email: khchow@gatech.edu
Office: Room 3337, Klaus Advanced Computing Building
Address: 266 Ferst Dr, Atlanta, GA 30332-0765 USA

News

  • Jan 2022 One paper on resource estimation for microservices with IBM Research accepted by ACM EuroSys 2022
  • Oct 2021 Two papers on federated learning accepted by IEEE TPS-ISA 2021
  • Oct 2021 One paper on network memory storage accepted by IEEE BigData 2021
  • Sep 2021 Released Security4AI vLab and AI-Privacy vLab to demonstrate security and privacy vulnerabilities in AI/ML
  • Jun 2021 Invited to serve as a program committee member for ML4H 2021
  • Jun 2021 One paper on ubiquitous localization accepted by IEEE TMC
  • May 2021 One paper on robust object detection accepted by ACM SIGKDD 2021
  • May 2021 Returned to the Storage Systems Research group at IBM Research as a research intern
  • Apr 2021 Received the Croucher Scholarship 2021
  • Apr 2021 Passed the qualifying examination and now a Ph.D. candidate at Georgia Tech
  • Mar 2021 One paper on ensemble learning accepted by CVPR 2021
  • Feb 2021 One paper on AI-assisted disaster recovery with IBM Research accepted by ACM SIGMOD 2021
  • Oct 2020 Two papers on robust machine learning accepted by IEEE TPS-ISA 2020
  • Oct 2020 One paper on ensemble learning accepted by IEEE CogMI 2020
  • Jun 2020 Two paper on machine learning security accepted by ESORICS 2020
  • May 2020 Joined the Storage Systems Research group at IBM Research as a research intern
  • Apr 2020 Won the best paper award at ACM EdgeSys 2020
  • Mar 2020 One paper on federated learning accepted by ACM EdgeSys 2020
  • Feb 2020 One paper on robust machine learning accepted by IEEE ICNC 2020
  • Oct 2019 One paper on graph mining accepted by IEEE CogMI 2019
  • Oct 2019 One paper on neural networks accepted by IEEE BigData 2019
  • Oct 2019 One paper on robust machine learning accepted by IEEE BigData 2019
  • Jan 2019 Joined Georgia Tech as a Ph.D. student

Ka-Ho Chow

Distributed Data Intensive Systems Lab

I am a Ph.D. candidate in the School of Computer Science at Georgia Institute of Technology (Georgia Tech), under the supervision of Prof. Ling Liu at the Distributed Data Intensive Systems Lab (DiSL). My research makes applied machine learning robust, privacy-preserving, and trustworthy. I am currently a Croucher scholar in machine learning, and my work has been partially supported by the Croucher Foundation in Hong Kong. Apart from conducting research at academic institutions, I also collaborate with Dr. Umesh Deshpande and Dr. Sangeetha Seshadri from the Storage Systems Research Group at IBM Research - Almaden to push the frontiers of machine learning on industrial systems problems. With its significance in academia and industry, my research has been published at premier conferences (e.g., SIGKDD, SIGMOD, CVPR) and adopted by Georgia Tech to nurture the next-generation computer scientists. Before joining DiSL, I obtained my Bachelor's and Master's degrees in Computer Science at the Hong Kong University of Science and Technology, where I worked at the Multimedia Technology Research Center and was supervised by Prof. S.-H. Gary Chan.

Research Interests

Robust Machine Learning; Cybersecurity; Machine Learning for Systems; Mobile Computing

Selected Publications

[Google Scholar]
  • Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, and Ling Liu, "DeepRest: Deep Resource Estimation for Interactive Microservices," ACM European Conference on Computer Systems (EuroSys), Rennes, France, Apr. 5-8, 2022. [PDF]
  • Ka-Ho Chow and Ling Liu, "Robust Object Detection Fusion Against Deception," ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), Singapore, Aug. 14-18, 2021. [PDF] [CODE]
  • Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, and Ling Liu, "SRA: Smart Recovery Advisor for Cyber Attacks," ACM SIGMOD International Conference on Management of Data (SIGMOD), Xi'an, Shaanxi, China, Jun. 20-25, 2021. [PDF]
  • Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka-Ho Chow, and Wenqi Wei, "Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, Jun. 19-25, 2021. [PDF] [CODE]
  • Jiajie Tan, Hang Wu, Ka-Ho Chow, and Shueng-Han Gary Chan, "Implicit Multimodal Crowdsourcing for Joint RF and Geomagnetic Fingerprinting," IEEE Transactions on Mobile Computing (TMC), to appear. [PDF]
  • Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, and Yanzhao Wu, "Understanding Object Detection Through An Adversarial Lens," European Symposium on Research in Computer Security (ESORICS), Guildford, United Kingdom, Sep. 14-18, 2020. [PDF] [CODE]
  • Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, and Ling Liu, "Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks," IEEE International Conference on Big Data (BigData), Los Angeles, CA, USA, Dec. 9-12, 2019. [PDF]
  • Ka-Ho Chow, Suining He, Jiajie Tan, and Shueng-Han Gary Chan, "Efficient Locality Classification for Indoor Fingerprint-based Systems," IEEE Transactions on Mobile Computing (TMC), Vol. 18, No. 2, pp. 290-304, February 2019. [PDF]

Full Publication List

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Research and Teaching Experience

  • Georgia Institute of Technology, Atlanta, Georgia, United States
    • Graduate Research Assistant (Jan. 2019 - Present)
      Distributed Data Intensive Systems Lab
    • Graduate Teaching Assistant (Sep. 2019 - Present)
      CS 6220: Big Data Systems and Analytics (Fall 2020, Fall 2019)
  • IBM Research - Almaden, San Jose, California, United States
    • Research Intern (Summer 2020, Summer 2021, Summer 2022)
      Storage Systems Research Group
  • Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
    • Graduate Research Assistant (Sep. 2016 - Dec. 2018)
      Multimedia Technology Research Center
    • Graduate Teaching Assistant (Sep. 2016 - Jun. 2018)
      COMP 2012: Object-Oriented Programming and Data Structures (Spring 2018)
      COMP 1021: Introduction to Computer Science (Spring 2017)
      COMP 1029P: Python Programming Bridging Course (Fall 2016)

Awards and Achievements

  • Croucher Scholarship for Doctoral Study, 2021-2022
  • Best Paper Award, ACM International Workshop on Edge Systems, Analytics and Networking, 2020
  • Student Travel Award, IEEE International Conference on Big Data, 2019
  • Chair's Fellowship, Georgia Tech, 2019
  • Postgraduate Studentship, HKUST, 2016-2017, 2017-2018
  • Dean's List, HKUST, 2015-2016
  • Hang Lung: Chan Tseng-Hsi Foundation Scholarship, Hong Kong, 2013-2014
  • Sir Edward Youde Memorial Prize, Hong Kong, 2009-2010

Presentations

  • ACM European Conference on Computer Systems, Rennes, France, Apr. 5-8, 2022.
  • IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, Virtual Conference, Dec. 13-15, 2021.
  • ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Singapore, Aug. 14-18, 2021.
  • ACM SIGMOD International Conference on Management of Data, Xi'an, Shaanxi, China, Jun. 20-25, 2021.
  • Ph.D. Visit Day, College of Computing, Georgia Institute of Technology, Atlanta, GA, USA, Mar. 4, 2021
  • IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, Atlanta, GA, USA, Dec. 1-3, 2020.
  • European Symposium on Research in Computer Security, Guildford, United Kingdom, Sep. 14-18, 2020.
  • IEEE International Conference on Cognitive Machine Intelligence, Los Angeles, CA, USA, Dec. 12-14, 2019.
  • IEEE International Conference on Big Data, Los Angeles, CA, USA, Dec. 9-12, 2019.
  • Cybersecurity Summit, Institute for Information Security & Privacy, Atlanta, GA, USA, Sep. 10, 2019.

Academic Services

  • Program Committee
    • Machine Learning for Health (ML4H) 2021
  • Invited Reviewer
    • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2022
    • AAAI Conference on Artificial Intelligence (AAAI) 2022
    • ACM/IFIP Middleware Conference (Middleware) 2021
    • Machine Learning for Health (ML4H) 2020
    • IEEE International Conference on Computer Communications (INFOCOM) 2017, 2018
    • IEEE Transactions on Mobile Computing (TMC)
    • ACM Transactions on Internet Technology (TOIT)