# William Wu

> Software Engineer at Superscript

Location: New York, New York, United States
Profile: https://flows.cv/williamwu1

## Work Experience
### Senior Software Engineer @ Superscript
Jan 2025 – Present | New York, United States

### Software Engineer @ Superscript
Jan 2024 – Jan 2025 | New York, United States

### Software Engineer @ Acorns
Jan 2023 – Jan 2024 | New York, New York, United States
- Architected an LLM-based chatbot for searching through internal company documents and answering queries with generated factual responses using Python, Event-Driven architecture, and AWS components, slashed engineers’ information retrieval times and drove department-wide adoption.
- Created a Graphql Spring server in Kotlin to trigger Temporal Workflows. Deployed via Harness onto AWS ECS instances and monitored traffic via distributed tracing using Datadog APM.
- Coordinated with compliance and investment stakeholders to build a data ingestion pipeline and scheduled jobs for securely fetching customer SSNs to satisfy FINRA CAIS regulatory requirements, all within a short 2 month notice.
- Built a data pipeline of 28 different models using Airflow, DBT, and Datadog to monitor and alert on invalid customer states, exposing incidents requiring time-sensitive remediation.

### Software Engineer @ Meta
Jan 2022 – Jan 2022 | New York, New York, United States
- Led a research project on the Ego4d team in Meta AI Research to perform object detection on a
video dataset of robot arm movements for typical kitchen actions with different camera perspectives

### MIT Graduate Research Assistant @ Massachusetts Institute of Technology
Jan 2022 – Jan 2022 | Cambridge, MA
- Master's thesis supervised by Muriel Médard in the MIT Research Laboratory of Electronics department
- IEEE International Conference on Acoustics, Speech and Signal Processing 2023 paper submission accepted: "InfoShape: Task-Based Neural Data Shaping via
Mutual Information" (https://arxiv.org/abs/2210.15034)
- Designed and implemented a novel Lagrangian optimization scheme for a neural network encoder with a mutual information estimator, ReMINE (Choi et. al.), using Pytorch, NumPy, and sklearn
- Empirically demonstrated InfoShape's ability to shape synthetic data to achieve both a 35% decrease in privacy leakage and a utility score increase by a factor of 5.1

### MIT Intro to CS and Data Science Graduate TA @ Massachusetts Institute of Technology
Jan 2021 – Jan 2021 | Cambridge, Massachusetts, United States
- Taught weekly recitations, held office hours, and led exam reviews to cover course materials and answer student questions about psets
- Used a "teach one to fish vs giving them a fish" mentality combined with patient, diligent explanations that many students highly appreciated
- Wrote the code, tests, and writeup for a sea level rise and climate change analysis lab from scratch
- Learned common pitfalls for beginner CS students in an intro curriculum and used a variety of teaching strategies to help students understand difficult concepts

### Software Engineer Intern @ Meta
Jan 2021 – Jan 2021 | New York, New York, United States
- Performed an end-to-end research project evaluating a Faster R-CNN model on
egocentric video frames, exposing subpar performance in various settings and
limitations with the rigid COCO object taxonomy
- Developed and tested a pipeline for sampling a well-distributed validation set of
egocentric video frames of different settings, scenarios, and blur and brightness
levels
- Created and outsourced an annotation pipeline that obtained 3000 human-annotated
video frames for object detection

Ego4d: https://ego4d-data.org/

### Undergraduate Researcher @ MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Jan 2020 – Jan 2020 | Cambridge, Massachusetts, United States
- Built simulations in CARLA software to test an autonomous vehicle based on Certified Control: using formal methods in a "trusted base" to verify visual and Lidar-based certificates for certain actions to provide vehicle safety guarantees
- Took the Introduction to Self-Driving Cars course on Coursera
- Implemented a road lane detection algorithm using Canny Edge Detection and the Hough Transform

### Software Engineer Intern @ Facebook
Jan 2020 – Jan 2020 | Greater Boston Area
- Built Python + SQL workflows for Facebook's East Coast Computer Vision team to
match popular, user-uploaded, potentially misinformative videos and images against
untampered "originals" from a curated dataset, recurring daily
- Visualized top matches and uncovered potential areas of improvement for the
underlying ObjectDNA object detection algorithm
- Reduced Chronos resource allocation waste by implementing an intelligent
compute resource allocation algorithm

### Software Engineer Intern @ Apple
Jan 2019 – Jan 2019 | San Francisco Bay Area
- Designed and implemented backend support for the zip download feature in iCloud Drive in the CloudKit Java ecosystem
- Constructed UML and sequence diagrams, learned to write scalable/modular code, and became proficient with the object-oriented paradigm in Java
- Communicated and presented to colleagues across teams to achieve desired API changes + integration

### Computer Vision Extern @ Hosta Labs
Jan 2018 – Jan 2018 | Cambridge, Massachusetts, United States
- Conducted image segmentation on pictures of home interiors from the ImageNet dataset using the Watershed Transform and state-of-the-art models like VGG and ResNet
- Used classification and bounding box results in a pipeline from taking pictures of a renovation space to producing an interactive 3D model capable of adding + removing furniture with real time quote estimates from contractors


## Education
### Master's degree in Computer Science
Massachusetts Institute of Technology
Jan 2021 – Jan 2022

### Bachelor's degree in Computer Science
Massachusetts Institute of Technology
Jan 2017 – Jan 2021


## Contact & Social
- LinkedIn: https://linkedin.com/in/bwu2021

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Source: https://flows.cv/williamwu1
JSON Resume: https://flows.cv/williamwu1/resume.json
Last updated: 2026-04-01