Yunfan Zhang

About Me

I am a PhD student in Computer Science at Columbia University. I am advised by Prof. Ethan Katz-Bassett. I work on Internet measurements and performance. My current research involves using public services and datasets to estimate activity levels for Internet users around the world, eventually building a traffic map for the Internet. Check out our related papers in IMC 2021 and HotNets 2021 for our research direction.

Prior to Columbia, I was an undergraduate student at Duke University, advised by Prof. Maria Gorlatova and Prof. Guohao Lan. I worked on a number of projects related to computer vision, applied machine learning, augmented reality, and mobile computing.

Here is my CV.

Research Interests

• Networked Systems: Network Performance and Measurements, Datacenter Networks, Programmable Networks.
• Computer Vision & Deep Learning: Depth Perception, 3D Computer Vision, Image Reconstruction and Denoising.
• Mobile & Edge Computing: Augmented Reality, Edge Offloading, Efficient Inference of Deep Neural Networks.

News

• [Mar. 2022] Our paper Optimal Network Protocol Selection for Competing Flows via Online Learning appears in TMC 2022!
• [Mar. 2022] Our paper InDepth: Real-time Depth Inpainting for Mobile Augmented Reality appears in IMWUT/UbiComp 2022!
• [Nov. 2021] Our paper Towards Identifying Networks with Internet Clients Using Public Data appears in IMC 2021!
• [Nov. 2021] Our paper Towards a Traffic Map of the Internet appears in HotNets 2021!
• [Oct. 2021] Our paper Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality appears in TOSN 2022!

Publications

• InDepth: Real-time Depth Inpainting for Mobile Augmented Reality
  Y. Zhang, T. Scargill, A. Vaishnav, G. Premsankar, M. Di Francesco, M. Gorlatova
  Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Mar. 2022 IMWUT/UbiComp 2022
  [PDF]

• Optimal Network Protocol Selection for Competing Flows via Online Learning
  X. Zhang, S. Chen, Y. Zhang, Y. Im, M. Gorlatova, S. Ha, C. Joe-Wong
  IEEE Transactions on Mobile Computing, 2022 TMC 2022
  [PDF]

• Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality
  G. Lan, Z. Liu, Y. Zhang, T. Scargill, J. Stojkovic, C. Joe-Wong, M. Gorlatova
  ACM Transactions on Sensor Networks, Vol. 18, No 1, Feb. 2022 TOSN 2022
  [PDF]

• Towards Identifying Networks with Internet Clients Using Public Data
  W. Jiang, T. Luo, T. Koch, Y. Zhang, E. Katz-Bassett, M. Calder
  21st ACM Internet Measurement Conference IMC 2021
  [PDF]

• Towards a Traffic Map of the Internet: Connecting the Dots between Popular Services and Users
  T. Koch, W. Jiang, T. Luo, P. Gigis, Y. Zhang, K. Vermeulen, E. Aben, M. Calder, E. Katz-Bassett, L. Manassakis, G. Smaragdakis, N. Vallina-Rodriguez
  20th ACM Workshop on Hot Topics in Networks HotNets 2021
  [PDF]

• CollabAR: Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality
  Z. Liu, G. Lan, J. Stojkovic, Y. Zhang, C. Joe-Wong, M. Gorlatova
  19th ACM/IEEE International Conference on Information Processing in Sensor Networks IPSN 2020
  [PDF]

• Edge-based Provisioning of Holographic Content for Contextual and Personalized Augmented Reality
  M. Glushakov, Y. Zhang, Y. Han, T. Scargill, G. Lan, M. Gorlatova
  2020 IEEE International Conference on Pervasive Computing and Communications Workshops PerCom Workshops 2020
  [PDF]

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