About me

Hey there! I'm Alex, currently a student at Harvard College studying Computer Science and Statistics, expected to graduate in Spring 2024. Previously, I've worked at Amazon AWS, Lucid Software, and Cedar. I'm interested in Machine Learning/AI, Computer Vision, and all things data.

I am currently researching AI/ML methods to analyze medical images at Cardiovascular Imaging Research Center @ MGH. I have 4+ years of AI/ML research experience, researching previously at Scientific Computing and Imaging Institute @ University of Utah, Research Science Institute @ MIT, and the Moran Eye Center @ University of Utah. I enjoy using computer science to improve other fields, especially medical research, sports, and music. In my free time, I enjoy playing soccer, hiking, and music.

Resume

Education

  1. Harvard University

    2019 — Expected 2024

    BA in Computer Science and Statistics. Gap year taken in Fall 2020 - Fall 2021 to work at Lucid Software.
    Activities and Socities: Harvard Computer Society, Harvard Open Data Project, CrimsonEMS

  2. Hillcrest High

    Graduated 2019

Work Experience

  1. Software Engineer Intern - Cedar

    Internship · May 2022 — Aug 2022

    Worked on the Data Engineering/MLOps team
    - Created production ready AWS Lambda infrastructure to ETL data from S3 to Snowflake for 2 ML models
    - Performed full-stack work on internal tools to measure ML model performance and with changes having 0% negative measured impact on latency and performance using Django and Streamlit
    - Conducted feature engineering work to improve ML model and prevent overfitting

  2. Software Development Engineer Intern - Amazon AWS

    Internship · Jun 2021 — Aug 2021

    Worked on the AWS Lambda team
    - Designed and implemented fail-safe mechanism feature to stop fraud detection from interrupting AWS Lambda functionality in cases of fraud compromise for all customer accounts using Java
    - Created metric and alarming system to ensure proper functionality of fraud risk status verification for AWS Lambda using SNS, ECS and S3

  3. Associate Software Engineer - Lucid Software

    Full Time · May 2020 - Jun 2021

    Worked on the Data Engineering team
    - Designed and implemented AWS architecture (Lambda, Fargate, EC2, ECS, SQS, S3, DynamoDB) for 2 major customer facing data science projects through Terraform
    - Developed a machine learning model using NLP (transformers, NLTK) and clustering algorithms to analyze and group customer data and documents for customer facing feature
    - Implemented 25+ metrics through AWS Lambda and SNS to track users and internal Lucid services
    - Created and maintained 20+ ETL jobs in Scala and SQL as a part of data warehousing solution
    - Full-stack engineering support for internal tools used by business analysts and data scientists using React, Python, and Typescript

  4. Automation Engineer Intern - Lucid Software

    Internship · Jun 2019 - Sept 2019

    Worked on the Automation team
    - Designed/Implemented 15+ automated Selenium tests using Scala to reduce manual testing of LucidChart and LucidPress
    - Gained hands-on experience with industry standard frameworks/tools, Agile development, source control (Git), and coding best practices with a large code base

Personal Projects

  1. Datamatch - President

    Aug 2019 — Present

    Datamatch is an annual college matchmaking service that matches users based on a humorous survey. As the current President of Datamatch and lead of the technical teams this year, I drive the overall tech direction for the website built using React, Firebase and D3, and develop strategies to expand Datamatch that have helped increase our user base from 20,000 to 50,000+ and to 40+ colleges campuses worldwide in previous years.

  2. Harvard Computer Society - Director of Recruiting

    May 2021 — May 2022

    HCS is Harvard's largest and oldest computing club. As the director of recruiting, I helped members find internships, put on events for practicing technical interviews, and helped members find jobs after graduation interviews, and organized events with outside speakers to discuss the interviewing process for SWE, Data Science, Startups, and Finance.

  3. Major League Soccer Player Analysis

    Jun 2020 — Jul 2020

    From personal interest, I conducted an analysis of the MLS player performance/game impact by scraping data from FBref and analyzed the data through nearest neighbor clustering using Python and visualized through d3.

  4. Stor

    Nov 2019 — Dec 2019

    Stor is a prototype peer-to-peer storage iOS app developed to allow people to sell their extra space as storage space to other people, specifically geared towards college students. Built using Firebase and Swift.

Research

Publications

  1. Deep Learning to Predict Mortality After Cardiothoracic Surgery Using Preoperative Chest Radiographs

    May 2022 - The Annals of Thoracic Surgery

  2. Deep Learning to Estimate COVID-19 Mortality Risk from Chest Radiographs

    Nov 2021 - AHA Journals

  3. Deep learning to distinguish COVID-19 from influenza on chest x-rays

    May 2021 - American Thoracic Society

  4. Automatic analysis of the retinal avascular area in the rat oxygen-induced retinopathy model

    Dec 2018 - Molecular Vision

Research Experience

  1. Cardiovascular Imaging Research Center @ Massachusetts General Hospital

    Jan 2020 — Present

    Researched under Dr. Michael T. Lu and Dr. Vineet Raghu
    - Conducting research to develop neural networks to predict lung cancer incidence/mortality and COVID-19 using PyTorch and OpenCV
    - Gain experience with AI methods and data processing through Python and R

  2. Research Science Institute @ MIT

    Jun 2018 - Aug 2018

    Researched under Dr. Howard S. Ying
    - Researched at the Boston Eye Care Center in computer science and ophthalmology and worked closely with Harvard and MIT professors
    - Developed algorithm to help detect diabetic complications outside of the eye through images of the eye using MATLAB

  3. Scientific Computing and Imaging Institute @ University of Utah

    Sept 2016 - Jun 2018

    Researched under Dr. Tolga Tasdizen
    - Developed algorithm to analyze retinal fundus images for diabetic retinopathy using C/C++ and OpenCV with artificial intelligence
    - Presented at International Science and Engineering Fair (3rd place in category) and National Junior Science and Humanities Symposium

  4. John A. Moran Eye Center @ University of Utah

    Oct 2015 — Jun 2019

    Researched under Dr. Mary Elizabeth Hartnett
    - Developed 2 machine learning methods to analyze blood vessels in retinal images for abnormal growth from multiple diseases using Java, C/C++
    - Published work in Molecular Journal and presented at ARVO Annual Conference, International Science and Engineering Fair, and National Junior Science and Humanities Symposium