Rishit Dagli

1st year CS Undergrad @ UofT, ML and Vision Research @ SpaceX, DGP Lab

rishit [at] cs [dot] toronto [dot] edu

I also maintain rishit.tech and this is a smaller version of it.

I am a CS Freshman at The University of Toronto. I love researching and working with Machine Learning, especially Computer Vision. Coming from the software and robotics background, I contribute extensively to/ maintain popular open-source projects like TensorFlow, PyTorch, Kubernetes, Kubeflow, PapersWithCode, freeCodeCamp among others. I also love building open-source projects (usually related to Kubernetes and Machine Learning), some of which have been pretty popular which could be found on my GitHub. Seeing my work at a rather young age, I was invited to speak at 2 TEDx and 1 TED-Ed events. Furthermore, I have also represented my country in international olympiads. Feel free to talk with me about anything CS, Math, Robotics, or Physics.

I am advised by Prof. David Lindell as a part of the DGP Lab at the University of Toronto where I research Diffusion. I am currently working as a Research Intern at SpaceX, where I am researching Computer Vision and Machine Learning before which I held the same position on NASA JWST (Exoplanet Detection Proposal) before which I have also been a research intern at Google AI under a grant.

My research community service can be summarized as being a Program Committee member for ICLR Tiny Papers 2023. Reviewer for ICLR 2023, ICLR PML4DC 2023, CVPR 2023, ICCV 2023, and NeurIPS 2023.

As to why I got drawn to Computer Vision, I do believe it is one of the richest modalities but also read this excerpt when I was quite young, from the book, “Visual Reconstruction” by Andrew Blake and Andrew Zisserman, some of my favourite researchers:

We count it a great privilege to be working in a field as exciting as Vision. On the one hand there is all the satisfaction of making things that work - of specifying, in mathematical terms, processes that handle visual information and then using computers to bring that mathematics to life. On the other hand there is a sense of awe (when time permits) at the sheer intricacy of creation. Of course it is the Biological scientists who are right in there; but computational studies, in seeking to define Visual processes in mathematical language, have made it clear just how intrinsically complex must be the chain of events that constitutes “seeing something”.

I deeply thank the following organization for current/ in the past supporting my research either through scholarships or research grants: Linux Foundation, Google AI, Google Cloud, University of Toronto, Vector Institute, Stanford, CNCF, and Intel AI.


Apr 11, 2023 Joining the Medical Imaging Group at UofT as a vistor.
Apr 1, 2023 Area Chair for ICLR Tiny Papers.
Mar 15, 2023 Soon joining Civo, a startup as one of the first ML research scientists.
Mar 2, 2023 1 paper accepted to ICLR.
Jan 17, 2023 Recipient of the Google AI Research Grant for 2023.
Dec 15, 2022 Stealth startup accepted to YCombinator.

selected publications

  1. astroformer.png
    Astroformer: More Data Might Not be All You Need for Classification
    Rishit Dagli
    In International Conference on Learning Representations, Apr 2023
  2. cppe5.png
    CPPE-5: Medical Personal Protective Equipment Dataset
    Rishit Dagli, and Ali Mustufa Shaikh
    SN Computer Science, Mar 2023
  3. q.png
    Deploying a smart queuing system on edge with Intel OpenVINO toolkit
    Rishit Dagli, and Süleyman Eken
    Soft Computing, Aug 2021
  4. b.png
    Job Descriptions Keyword Extraction using Attention based Deep Learning Models with BERT
    Hussain Falih Mahdi, Rishit Dagli, Ali Mustufa, and 1 more author
    In 2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Jun 2021
  5. fastformer.png
    Fast Transformer
    Rishit Dagli
    Sep 2021
  6. perceiver.png
    Rishit Dagli
    Apr 2021
  7. gctf.png
    Gradient Centralization
    Rishit Dagli, and Shaikh Ali Mustufa
    Mar 2021