Michael Sun

Hi! I am a Stanford BS & MS candidate and machine learning engineer. Below are some portfolio projects.

void shortcuts() {LinkedIn; GitHub; Resume;}

Reach out if you want access to private repos of listed projects. Enjoy!

Major Project Experience (to date)

For each of these, see “Longer Summaries” section for more details!

FALL 2021 UPDATE: WOOHOO! I got an offer with TikTok. I will start working in their Search Team as a Machine Learning Engineer next fall in Mountain View!

Machine Learning Engineer Intern @ Spotify

  • One of 3 inaugural interns in Spotify’s ML Platform team
  • Began feature in ML Home, Spotify’s productivity hub for all company applied ML teams, 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

Stanford Network Analysis Project RAship (supervisor 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 the largest anime recommendation dataset featuring 10,000 shows, 13,000+ users, 130,000 reviews and more by crawling online discussion forums
  • Founded and maintaining only existing NLP driven anime recommendation site OtakuRoll built on DeepNaniNet!
  • Submitted manuscript to a conference as Lead Author (contact for preprint)

Machine Learning Intern @ Samsung Research America Think Tank Team

  • Trained the SARAM robot 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

Stanford QIAI Deep Learning RAship (supervisor 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

  • 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 – 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

Quizkly (Live app/demo)– Full-stack React + Django web app with end-to-end deep learning pipeline that auto-generates quizzes from any corpus of text [UPDATE: Service stopped as we ran out AWS credits :(]

aiRoute (App Store) – iOS native app that randomly generates a running route in your area and provides turn-by-turn map and voice navigation

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

Course Final Projects + Misc.

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

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)

Longer summaries

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

I am an undergraduate at Stanford University, pursuing Mathematical and Computational Science with honors, expected 2021/22. I expect to graduate 2022 with a Masters in Computer Science.

I was born in Torrance, California. I am a US citizen and permanent resident.

I studied overseas from elementary to high school, as an expat.

During high school, I:

  • 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 paper in combinatorial graph theory on the Metric Dimension for Planar Graphs, readable here: [1704.04066] Bounds on metric dimension for families of planar graphs (also included below)
  • 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:

  • 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

Choice Set of 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 [certificate]

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)

Technical (non-code) writing samples

  • Analysis paper on Fourier Transform and an application to CNNs
  • ISEF-winning combinatorial graph theory paper back in HS

Mentoring Resources (more to come)

  • Favorite LeetCodes by difficulty and category
  • Collaborative math blog back in HS


Get in Touch

Stanford University
450 Serra Mall
Stanford, California 94305

Send Me a Message

“He who says he can, and he who says he can’t… are both correct.”