Angus Fung

I completed my Ph.D at the University of Toronto, Robotics Institute, advised by Goldie Nejat, where I work on robot perception and control using self-supervised learning and generative AI.

Previously, I worked on learning algorithms at the Vector Institute where I was advised by Jimmy Ba. Currently, in my free-time, I am building Syncere AI with Aaron Tan to bring consumer robots into society.

Outside of research:
  1. Music: I am active as a church organist having held positions at the Metropolitan United Church (under Dr. Patricia Wright) and St. Michael's Cathedral Basilica. I received my ARCT Diploma in Piano and Organ Performance in 2013 at the Royal Conservatory of Music.
  2. Medicine: I build AI models to tackle open questions in neuroscience and neuro-ophthalmology with Dr. Anthony Lang and Dr. Edward Margolin.
  3. Gaming: I am a hobbyist game developer with experience at deploying games at scale, specifically in game design, load balancing, DDoS mitigation, security protocols, and anti-cheat mechanisms.
  4. Startups: I co-founded Scholarply and ONE800 with Aaron Tan, leveraging LLMs for scholarship applications and personal companionship.
  5. Entertainment: I worked with 2x Grammy Award recipient Sean Leon to build AI technology for their God's Algorithm Project.

Updated: 10/01

Email  /  CV  /  Google Scholar  /  Github

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Research | SaaS Products | Recognition | Teaching | Mentoring
Research
LDTrack: Dynamic People Tracking by Service Robots using Diffusion Models
Angus Fung, Beno Benhabib, Goldie Nejat
arXiV (Under Review), 2024
Paper

We present a novel people tracking architecture for mobile service robots using conditional latent diffusion models, which we name Latent Diffusion Track (LDTrack), to solve the robotic problem of tracking multiple dynamic people under intraclass variations.

Robots Autonomously Detecting People: A Multimodal Deep Contrastive Learning Method Robust to Intraclass Variations
Angus Fung, Beno Benhabib, Goldie Nejat
IEEE Robotics and Autonomation Letters + IROS, 2023
Paper / Talk / Abstract / Poster

We present a novel multimodal person detection architecture to address the mobile robot problem of person detection under intraclass variations (e.g. partial occlusion, varying illumination, pose deformation) by introducing our Temporal Invariant Multimodal Contrastive Learning (TimCLR) method.

A Multi-Robot Person Search System for Finding Multiple Dynamic Users in Human-Centered Environments
Sharaf C Mohamed, Angus Fung, Goldie Nejat
IEEE Transactions on Cybernetics, 2022
Paper / Video

We present a novel multi-robot person search system to generate search plans for multi-robot teams to find multiple dynamic users before a deadline.

Robots Understanding Contextual Information in Human-Centered Environments using Weakly Supervised Mask Data Distillation
Daniel Dworakowski, Angus Fung, Goldie Nejat
International Journal of Computer Vision (IJCV), 2022
Paper

We present the novel Weakly Supervised Mask Data Distillation architecture for autonomously generating pseudo segmentation labels.

AC/DCC : Accurate Calibration of Dynamic Camera Clusters for Visual SLAM
Jason Rebello, Angus Fung, Steven Waslander
IEEE International Conference on Robotics and Automation (ICRA), 2020
Paper

We present a method to calibrate the time-varying extrinsic transformation between any number of cameras and achieves measurement excitation over the entire configuration space of the mechanism resulting in a more accurate calibration.

Using Deep Learning to Find Victims in Unknown Cluttered Urban Search and Rescue Environments
Angus Fung, Beno Benhabib, Goldie Nejat
Springer Nature, 2020
Paper

We investigate the first use of deep networks for victim identification in Urban Search and Rescue, for cases of partial occlusions and varying illumination, on a RGB-D dataset obtained by a mobile robot navigating cluttered USAR-like environments.


SaaS Products
Scholarply
Angus Fung (Founder), Aaron Tan (Founder)
  • Accelerating the scholarship application process via LLM agents to help students secure funding while focusing on their studies.
  • Selected by Microsoft Startup Hub Program, receiving grants worth $150k.
ONE800
Angus Fung (Founder), Aaron Tan (Founder)
  • An all-in-one service built in to iMessage aimed at lowering the barrier of entry for LLMs and Generative AI.
  • Launched multi-modal conversations with proprietary model 4 months before GPT-4V.
  • Gained significant traction with thousands of monthly active users.

Recognition
2024: Doctoral Completion Award ($4k)
2024: LocalHost Fellowship ($3k)
2024: Microsoft Startup Hub Program ($150k)
2023: Ontario Graduate Scholarship - University of Toronto ($15k)
2022: Rimrott Memorial Graduate Scholarship - University of Toronto ($4k)
2021: RO-MAN Roboethics Competition, McGill University - 1st Place ($1k)
2021: University of Toronto MIE Fellowship ($14k)
2020: Queen Elizabeth II Graduate Scholarship - University of Toronto ($15k)
2020: University of Toronto MIE Fellowship ($14k)
2019: University of Toronto MIE Fellowship ($14k)
2019: Healthcare Robotics NSERC Fellowship ($10k)
2014-2018: Dean's Honour List
2014: Delta Tau Delta Award ($3k)
2014: University of Toronto Scholars (Academic Excellence) ($7.5k)
2014: University of Toronto Scholar ($5k)
2013: ARCT Diploma - Piano Performance
2013: ARCT Diploma - Organ Performance

Teaching
2024F: ROB501: Computer Vision for Robotic, TA, University of Toronto
2024W: MIE443: Mechatronics Systems: Design & Integration Head Tutorial TA, University of Toronto
2023F: MIE443: Mechatronics Systems: Design & Integration Head Tutorial TA, University of Toronto
2022F: ROB501: Computer Vision for Robotic, TA, University of Toronto
2022W: MIE443: Mechatronics Systems: Design & Integration Head Tutorial TA, University of Toronto
2021W: MIE443: Mechatronics Systems: Design & Integration Head Tutorial TA, University of Toronto
2020W: MIE443: Mechatronics Systems: Design & Integration Head Tutorial TA, University of Toronto

Mentoring
2023-2024: Undergraduate Thesis Student: Michelle Quan (Thesis)
2022-2023: Undergraduate Thesis Student: Grace Bae (Thesis)
2021-2022: Undergraduate Thesis Student: Giro Ele (Thesis)