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

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). I am also a Croucher scholar, and my research has been partially supported by the Croucher Foundation. Before joining DiSL, I obtained my Bachelor's and Master's degrees in Computer Science at the Hong Kong University of Science and Technology (HKUST) where I worked at Multimedia Technology Research Center (MTrec) and was supervised by Prof. S.-H. Gary Chan. I also work closely with Dr. Umesh Deshpande and Dr. Sangeetha Seshadri from the Storage Systems Research group at IBM Research - Almaden on machine learning for systems. My research has been used at Georgia Tech as teaching materials through Security4AI vLab and AI-Privacy vLab.

News

  • September 2021: We have released Security4AI vLab and AI-Privacy vLab to demonstrate security and privacy vulnerabilities in AI/ML
  • June 2021: Our paper on ubiquitous localization has been accepted by IEEE Transactions on Mobile Computing
  • May 2021: I will be joining IBM Research - Almaden as a research intern this summer
  • May 2021: Our paper on robust object detection has been accepted by SIGKDD 2021
  • April 2021: I have been awarded the Croucher Scholarship for Doctoral Study 2021-2022
  • March 2021: Our paper on ensemble learning has been accepted by CVPR 2021
  • February 2021: Our demo paper on smart recovery advisor with IBM Research has been accepted by SIGMOD 2021

Research Interests

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

Publications

[Google Scholar]
  • 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 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]
  • Ka-Ho Chow, Ling Liu, Margaret Loper, Juhyun Bae, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei and Yanzhao Wu, "Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems," IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Atlanta, GA, USA, Dec. 1-3, 2020. [PDF] [CODE] 🎮 Security4AI vLab
  • Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex and Yanzhao Wu, "Adversarial Deception in Deep Learning: Analysis and Mitigation," IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Atlanta, GA, USA, Dec. 1-3, 2020. [PDF] [CODE]
  • Yanzhao Wu, Juhyun Bae, Ka-Ho Chow, Wenqi Wei and Ling Liu, "EnsembleBench: An Evaluation Framework for Ensemble Learning," IEEE International Conference on Cognitive Machine Intelligence (CogMI), Atlanta, GA, USA, Dec. 1-3, 2020. [PDF] [CODE]
  • 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]
  • Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex and Yanzhao Wu, "A Framework for Evaluating Gradient Leakage Attacks in Federated Learning," European Symposium on Research in Computer Security (ESORICS), Guildford, United Kingdom, Sep. 14-18, 2020. [PDF] [CODE] 🎮 AI-Privacy vLab
  • Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy and Wenqi Wei, "LDP-Fed: Federated Learning with Local Differential Privacy," ACM International Workshop on Edge Systems, Analytics and Networking (EdgeSys), Heraklion, Crete, Greece, Apr. 27, 2020. [PDF] [CODE] 🏆 Best Paper Award
  • Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex and Yanzhao Wu, "Cross-Layer Strategic Ensemble Defense Against Adversarial Examples," IEEE International Conference on Computing, Networking and Communications (ICNC), Big Island, Hawaii, USA, Feb. 17-20, 2020. [PDF] [CODE]
  • Lei Yu, Ling Liu, Calton Pu, Ka-Ho Chow, Mehmet Emre Gursoy, Wenqi Wei, Ming Hong, Arun Iyengar, Gong Su, Qi Zhang and Donna Dillenberger, "GRAHIES: Multi-Scale Graph Representation Learning with Latent Hierarchical Structure," IEEE International Conference on Cognitive Machine Intelligence (CogMI), Los Angeles, CA, USA, Dec. 12-14, 2019. [PDF]
  • 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, Los Angeles, CA, USA, Dec. 9-12, 2019. [PDF]
  • Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu and Qi Zhang, "Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks," IEEE International Conference on Big Data, Los Angeles, CA, USA, Dec. 9-12, 2019. [PDF] [CODE]
  • Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex and Yanzhao Wu, "Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness," IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS), Monterey, CA, USA, Nov. 4-7, 2019. [PDF] [CODE]
  • 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]
  • Ka-Ho Chow, Anish Hiranandani, Yifeng Zhang and Shueng-Han Gary Chan, "Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder," Technical Report, Hong Kong University of Science and Technology, Nov. 20, 2018. [PDF]

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)
      Storage Systems Research Group
      Mentors: Dr. Umesh Deshpande, Dr. Wil Plouffe, Dr. Sangeetha Seshadri
  • 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 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. (Systems) 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.

Program Committee

  • Machine Learning for Health (ML4H) 2021

Reviewer

  • ACM/IFIP Middleware Conference 2021
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021
  • Machine Learning for Health (ML4H) 2020
  • ACM Transactions on Internet Technology (TOIT)
  • IEEE Transactions on Mobile Computing (TMC)
  • IEEE International Conference on Computer Communications (INFOCOM) 2017, 2018
  • MDPI ISPRS International Journal of Geo-Information (IJGI)
  • MDPI Sensors