Michael Sun

Hi! I am a ’22 Stanford BS & MS graduate and machine learning researcher.

Update: I will be an EECS PhD student at MIT CSAIL this fall!

Major Project Experience

For some of these, see Project reflections section for more details. Most code repos are public. Reach out if you want to see the private ones. For specific dates, see resume or LinkedIn. Enjoy!

Machine Learning Engineer @ TikTok

  • Onboarded the team powering the search engine for >10B videos and >1B users on TikTok
  • Got bored, realized what I really wanted, and left

Research @ Stanford Artificial Intelligence Laboratory (SAIL)

  • Supervised by Ananya Kumar and Percy Liang
  • Devise SOTA representation learning approaches to continual learning settings

Research @ SLAC National Accelerator Laboratory (feat. SNAP)

  • Supervised by Tailin Wu and Jure Leskovec
  • Accelerating large-scale laser particle acceleration simulations with deep learning
  • Devised approach can model complex physical phenomena at multiple scales

Machine Learning Engineer Intern @ Spotify

  • Supervised by Brian Martin and Funmi Doro
  • One of 3 inaugural interns in Spotify’s ML Platform team
  • Began feature in ML Home, Spotify’s productivity hub for all applied ML teams in the company, on Bayesian optimization over pipeline parameters
  • Proposed pipeline to identify causes for underperforming user segments, using Kubeflow Pipelines for orchestrating end-to-end ML workflows

Research @ Stanford Network Analysis Project (SNAP)

  • Supervised by Antoine Bosselut and Jure Leskovec
  • Surpassed SOTA results on the “cold start” problem in recommendation systems via a hybrid matrix factorization and “content basket” approach
  • Introduced a novel deep autoencoder architecture DeepNaniNet using jointly learned graph and language encoders for reconstructing user-item preferences
  • Compiled largest anime recommendation dataset featuring 10,000 shows, 13,000+ users, 130,000 reviews, etc. by crawling online discussion forums (data)
  • Founded and maintaining only existing NLP driven anime recommendation site OtakuRoll built on DeepNaniNet!
  • Published in Springer‘s special issue on recommender systems

Machine Learning Intern @ Samsung Research America Think Tank Team (deck)

  • Supervised by Curt Aumiller and Kate Hajash
  • Trained the SARAM robot to stir kitchen pots in a goal-based OpenAI gym environment
  • Replicated two OpenAI papers on dexterous hand solving a Rubik’s cube and ran hundreds of experiments with policy gradient actor-critic algorithms
  • Developed a new exploration-based environment for more human-like movements and presented successful PoC to team including SRA VP Joon Lee
  • Worked on practical methods to making RL policies transfer sim2real

Research @ Quantitative Imaging and AI Laboratory

  • Supervised by Daniel Rubin
  • Applying techniques of multi-modal representation learning on chest X-ray images, following this dataset with ideas from this paper (some initial code)
  • Training object detection models on Stanford’s largest video/EEG dataset for seizure detection with SOTA video understanding technologies, like this unsupervised deep tracker to track patients and this for video event composition

Software Engineer – Machine Learning Intern @ Synaptics (demo/code/deck)

  • Supervised by Utkarsh Guar and Gaurav Arora
  • Replicated the SOTA paper (SSD) in object detection
  • Engineered datasets and data pipeline for the task of logo detection
  • Developed a high-recall end-to-end realtime logo detection pipeline for smart TV
  • Experimented and tested deployment on Synaptics VSR 371 SoC
  • Presented findings to company AI/CV team and CTO

Co-Founder, CTO @ Demodraft (site/demo/code/deck) – Led a team of part-time volunteers to deploy our Beta within 1.5 months, got accepted into Berkeley Sky Deck, one of nation’s top college accelerators with <10% acceptance rate [update: exited by merging with OTP! see legacy landing page]

Quizkly (Live app/demo/code)– Full-stack React + Django web app with end-to-end deep learning pipeline that auto-generates quizzes from any corpus of text [update: service no longer sponsored or maintained]

aiFood (App Store/demo/code) – iOS native app that automates macro-counting and meal preparation with custom made API (code)

aiRoute (App Store/demo/code) – iOS native app that randomly generates a running route in your area and provides turn-by-turn map and voice navigation [update: some SDKs since 2018 have changed and may not work on new devices/OS anymore]


  • PP-GNN: From Learning NP-Hard to Position-aware Graph Neural Networks (solo author, under review at Elsevier Neurocomputing) [preprint]
  • Learning Efficient Hybrid Particle-continuum Representations of Non-equilibrium N-body Systems (2nd author, NeurIPS 2022 AI4Science) [poster, preprint]
  • Privacy Preserving Inference of Personalized Content for Out of Matrix Users (1st author, Springer publication) [link]
  • Improving Representational Continuity with Supervised Continued Pretraining (1st author, CVPR 2023 CLVISION)
  • X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents (co-author, ACL 2023)
  • (Dataset) User-Item Feature Graph for Content Based Recommendations of Japanese Anime Shows [DOI]
  • (Industry) Teaching the Samsung Bot Chef to Stir in a Open-Ended Environment (Samsung Research America Think Tank Team presentation)
  • (Industry) Logo Detection with VGG/MobileNet SSD (Synaptics R&D presentation)
  • (Misc.) Bounds on metric dimension for families of planar graphs (ISEF 2017 2nd Grand Award) [abstract, preprint]
  • (Misc.) Investigating Effect of Dialogue History in Multilingual Task Oriented Dialogue Systems [preprint]
  • (Misc.) Alpha-Mini: Minichess Agent with Deep Reinforcement Learning [preprint]
  • (Misc.) Do Neural Networks Generalize from Self-Averaging Sub-classifiers in the Same Way As Adaptive Boosting? [preprint]
  • (Misc.) Almost-Nash Sequential Bargaining [preprint]
  • (Misc.) How Fourier Transform Can Speed Up Training CNNs (Towards Data Science) [link]
  • (Misc.) LightGCN for MovieLens-100K (Medium) [link]

Project reflections

  1. Stanford MS RA
  2. TikTok
  3. OtakuRoll (NLP Rec Sys)
  4. Demodraft
  5. Samsung Research
  6. Stanford QIAI
  7. Synaptics
  8. aiFood + MealApp
  9. aiRoute
  10. Quizkly
  11. KnowledgeTree

Code Samples

PixelCNN (GitHub) – Experimentation/evaluation of better ways to project caption embeddings for the PixelCNN conditional generative model (report/poster)

LightGCN for MovieLens-100K – Tutorial and Colab walkthrough for movie recommendations using GNN (final draft/code)

KnowledgeTree (GitHub) – Console C++ and Python application that builds a high-to-low level concept tree from scraping Wikipedia pages with NLP techniques (poster)

GoodNews (GitHub)  – Machine learning project that predicts news article virality and popularity using its content and metadata (report/poster/code)

aiFriend (GitHub) – Website that generates reports (in R Markdown) analyzing and visualizing Messenger conversations (code)

Monetic (GitHub) – Funding platform to help struggling individuals during COVID-19 raise funds by sharing linked TikToks (devpost)

YangNoYang (GitHub) – Inspired to Silicon Valley’s “Hot Dog”, uses FaceID to detect faces of Andrew Yang in pictures (site)

InstaBot (GitHub) – Bot that can auto-login, auto-click posts, send follow requests, and auto grow following on Instagram (devpost)

OtakuRoll (GitHub) – Implementation of AnimeRecSys (see below), uses variety of algorithms to generate recommendations based on past shows enjoyed (prototype)

Education history

I am a US citizen. I was born in LA, California. Go Lakers!

My family moved and I studied overseas from elementary to high school, as an expat.

During high school (2014-2018):

  • Second Place Grand Award in Mathematics Category at Intel International Science and Engineering Fair (ISEF) 2017
    • Project was a conjecture and proof of new upper bounds on the metric dimension for planar graphs with applications to GPS-less navigation systems
  • Ranked top ~100 2017 United States of America Mathematical Olympiad (USAMO),
  • one of only three from China and first qualifier in high school’s history
  • Co-authored ISEF-winning paper in combinatorial graph theory on the Metric Dimension for Planar Graphs (arxiv)
  • Distinguished Honor Roll (top 1%) on both AMC 12 and AMC 10
  • Top 30 in the national American Invitational Mathematics Examination (AIME)
  • Ross Mathematics Camp at Ohio State University 2017 (one of USA’s oldest, most prestigious pure math summer programs)
  • Founded school’s only math club, grew to 20+ members as president, lecturer, problem writer, organizer and promoter
  • Started collaborative blog  for math olympiad topics, becoming one of the most popular blogs on AoPS.com the biggest online forum for math problem solvers around the world (fun fact: where I met my ISEF partner)

In college (2018-2022):

  • Pear VC Garage Fellow program (one of three freshmen in cohort of two dozen out of hundreds of Stanford applicants)
  • Published two iOS apps on App Store
  • Launched Quizkly with partner, ML MCQ quiz generator (funded by Pear VC)
  • Forum moderation in China-US student conferences (Stanford FACES)
  • Effective Altruism fellowships (Stanford EA)
  • Undergrad RA at the QIAI Lab (PI Dr. Rubin) on deep learning in medical applications
  • Undergrad RA in the SNAP Group on deep NLP recommender systems and knowledge-augmented language models
  • MCS Student Advisor senior year
  • Grad RA in US-Asia Tech Center studying high tech startups in Asia

I graduated from Stanford University in June 2022 with BS (Honors) in MCS and MS in Computer Science.

Relevant coursework:

  • Computer Science
    • CS 103 Mathematical Foundations for Computing, CS 106L Standard C++ Programming Laboratory, CS 106X Programming Abstractions Accelerated, CS 107 Computer Organization & Systems, CS 110 Principles of Computer Systems, CS 145 Data Management and Data Systems, CS 154 Introduction to the Theory of Computation, CS 161 Design and Analysis of Algorithms, CS 199 Independent Research (2x), CS 221 Artificial Intelligence: Principles and Techniques, CS 224N Natural Language Processing with Deep Learning, CS 224V Conversational Virtual Assistants with Deep Learning, CS 224W Machine Learning with Graphs, CS 246 Mining Massive Data Sets, CS 229 Machine Learning, CS 236 Deep Generative Models, CS 238 Decision Making Under Uncertainty, CS 261 Optimization and Algorithmic Paradigm, CS 330 Deep Multi-task and Meta Learning (audited), CS 47 Cross Platform Mobile Development (audited)
  • Mathematics + Statistics
    • MATH 104 Applied Matrix Theory, MATH 171 Fundamental Concepts of Analysis, MATH 61DM, 62DM, 63DM Modern Mathematics: Discrete Methods
    • STATS 116 Theory of Probability, STATS 200 Introduction to Statistical Inference
  • Others
    • MS&E 111X Introduction to Optimization (Accelerated), MS&E 221 Stochastic Modeling, PHIL 150 Mathematical Logic
  • deeplearning.ai Deep Learning Specialization [certificate]
  • Alberta Machine Intelligence Institute Reinforcement Learning Specialization

Alumni programs:

  • AwesomeMath Summer Program twice – an Olympiad-prep math camp
  • Worldwide Online Olympiad Training – high school online Olympiad-prep math camp
  • Ross Mathematics Camp 2017 – one of US’s oldest/most prestigious math enrichment camps, guiding students on proof-based exploration from classical to modern number theory results
  • Summer Program on Applied Rationality and Cognition 2018 – a highly selective program of nationwide’s top STEM talent
  • Make School Summer Academy 2018 – program with curriculum in iOS app dev and design thinking in which students ship apps by the end
  • Multiple Stanford Effective Altruism Fellowships (2019)

Mentoring Resources (more to come)


Get in Touch

Stanford University
450 Serra Mall
Stanford, California 94305

Send Me a Message

I ❤ solo car drives with Angela and solo traveling Japan.