# Ethan Hsiao

> CS & DS @ UC Berkeley | SWE @ Verkada, Inc.

Location: Berkeley, California, United States
Profile: https://flows.cv/ethanhsiao

Hello! My name is Ethan Hsiao, and I'm an avid programmer with expertise in Python, Java, C++, full stack development, REST APIs, and ML. I'm passionate about developing world-changing solutions using backend engineering and AI, as well as volunteering and engineering for social good! I enjoy working with others, and am goal oriented, flexible, enthusiastic, proactive, and dedicated. In my free time, I love peer tutoring, cheering on the Steelers, reading, and playing piano, tennis, ping pong, and chess! Feel free to reach me at ethan.hsiao@berkeley.edu.

## Work Experience
### Software Engineer @ Verkada
Jan 2024 – Present | San Mateo, California, United States

### Engineering Intern @ Rivian
Jan 2023 – Jan 2023 | Palo Alto, California, United States
➢ Performed 100+ IR investigations with Splunk, automated and parellelized workflows in Torq, increasing visibility and security, saving 1k+ business hours, filtering out >50% of false positives
➢ SOAR and JIRA automation with Slackbot integration expedited operational responses to threats, enhanced overall DART response by reducing manual intervention and potential errors
➢ Migrated all hive templates/workflows from hive4 to hive5 with AWS, Cribl, Kubernetes, Python

### Software Engineer Intern @ Fidelity Investments
Jan 2022 – Jan 2022 | Durham, North Carolina, United States
➢ Migrated 10 onboarding and security APIs from C# to Python for ECS PAM (Enterprise Cybersecurity Privileged Access Management) team; resolved bug fixes, added exhaustive unit tests (PyTest), & added automation, significantly improving code readability, scalability, and performance by >90%
➢ Flask app deployed using Docker, tested using Postman, pipelined and productionalized using Jenkins, hosted on cloud using AWS; repository serving as model for numerous other migration projects

### Research Intern @ NASA Jet Propulsion Laboratory
Jan 2022 – Jan 2022 | Pasadena, California, United States
➢ Developed python APIs to determine spatial coverage & revisit frequency for NASA satellites using GeoPandas, Bokeh, QGIS; works for any region-of-interest (spatial area) and temporal window
➢ The APIs leveraged a JPL database of footprints from multiple satellites (e.g. Landsat and Sentinel-2), synced these footprints to the acquisition frequency, & performed relevant queries to determine the revisit frequency, coverage within a temporal window and spatial area, & study surface water, surface disturbance, and surface deformation products

### Machine Learning Intern @ Beauty For All Industries (BFA)
Jan 2021 – Jan 2021 | San Mateo, California, United States
➢ Developed & pipelined ML model categorizing users’ complaints using PySpark, AWS, Jenkins
➢ Model’s accuracy over 93% (BERT), tuned hyperparameters (batch size, learning rate, # epochs) 
➢ BERT model currently used by Merchandising team to provide automated insights into NPS & user comments, driving business investments and more effective business strategy
➢ AI model also utilized to analyze difference in distribution of complaints between brands, subscription programs, & root and subcategories of makeup
➢ AI classifier highlighted frequency of repetitiveness complaints about brushes, leading Merchandising team to decrease number and frequency of brushes, improving customer experience
➢ Demoed model at Tech Demos and All Hands Meeting (~500 people, including CEO & CTO)

### Software Engineer Intern @ Qualtrics
Jan 2020 – Jan 2020 | Reston, Virginia, United States
➢ Built a humor detection model with an accuracy of over 95%, using a combination of naive rules, Random Forest Classifier, and FastText (uses Word2Vec)
➢ Implemented a Flask application service deployed using Docker to train ML models, make predictions, and test trained models using k-folds cross validation
➢ Presentation: https://www.youtube.com/watch?v=eiJ8as6wXRE
➢ Github: https://github.com/ETH88/Humor_Detection

### Research Intern (City Science Lab) @ MIT Media Lab
Jan 2019 – Jan 2019 | Cambridge, Massachusetts, United States
➢ Member of team creating ride-sharing self-driving bike (LiDAR), instrumental in testing vehicle
➢ Improved autonomous bike simulation, refactored code, and created recharge/wait model, adding realism to model
➢ Persuasive Electric Vehicle (PEV) project overview: www.media.mit.edu/projects/pev/overview


## Education
### Bachelor of Arts - BA in Computer Science and Data Science
University of California, Berkeley

### High School Diploma
BASIS Independent McLean


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

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Source: https://flows.cv/ethanhsiao
JSON Resume: https://flows.cv/ethanhsiao/resume.json
Last updated: 2026-03-29