Amazon | Research Engineer | Seattle, WA
July 2020 - present
- Doing computer vision research with a current focus on video understanding for Prime Video.
- Submitted paper to CVPR 2021 about contrastive learning for long-form videos (i.e. movies).
Amazon Web Services (AI) | Software Engineer | Seattle, WA
August 2019 - July 2020
- Elastic Inference reduces inference costs by enabling users to flexibly provision GPU compute.
- Added logging metrics and launched canaries to support new EC2 G4 instance family.
- Launched Elastic Inference-enabled PyTorch framework for SageMaker, EC2, and ECS (see my AWS blog post). Implemented TorchScript graph validation, shipped updated AWS Deep Learning Conda environments and Docker containers, benchmarked performance for vision and NLP models on multiple platforms, and wrote technical blog post.
- Created proof-of-concept for building and integrating TensorRT-enabled TensorFlow 2.1 into the inference engine. Reduced latency by up to 70% compared to FP32 native TensorFlow in benchmarks.
Amazon Web Services (Databases) | Software Engineering Intern | East Palo Alto, CA
June - August 2018
- Worked on Aurora, a distributed cloud-native relational database, and AWS’ fastest growing service.
- Developed production cluster service to automate ticket resolution using Java, DynamoDB, and internal service APIs. Improved on-call engineer productivity.
- Wrote tool for enabling/disabling autoscaling policies and provisioning IOPS on pre-prod clusters.
Phosphorus | Software Engineering Intern | New York, NY
May - August 2017
- One of 30 Princeton Start-up Immersion Program participants placed at early-stage or series A startups.
- Redesigned management portal and implemented custom UI/UX components in admin dashboard using Wicket and Scala.
- Created distributor preference scoping model in Scala, Spring Boot, Hibernate, and PostgreSQL. Wrote AWS Cloud Formation templates.
Princeton Vision and Learning Lab | Undergrad Researcher | Princeton, NJ
September 2018 - current
- Did an undergraduate senior thesis in computer vision and deep learning, related to single-view 3D vision.
- Paper accepted to CVPR 2020 conference.
Harvard-MIT HST | Bioinformatics Research Intern | Boston, MA
June - August 2016
Claims-wide Association Study (CWAS)
- Worked with Prof. Isaac Kohane and Dr. Arjun Manrai to develope a new association study called “claims-wide association study (CWAS)” - like genome-wide association studies (GWAS), but for insurance claims.
- Built a data visualization tool for plotting heatmaps of the USA from parsed AETNA insurance claims, at multiple levels of geographic specificity (zipcode, county, state, regional)
- Used R, MySQL, and the Shiny web framework; code here.
- Worked with Dr. Jean Fan to develop an open-source web application for client-side RNA-seq and qPCR data analysis.
- All computation and data visualization is done client-side, thus providing a secure and fast environment for bioinformatics that involves no server.
- Submitted manuscript to bioRxiv.
Rutgers New Jersey Medical School | HS Research Intern | Newark, NJ
June - August 2014
- Investigated effects of the Ras•GTP-Raf-MEK-ERK signaling pathway in Drosophila fruit flies on organismal and organ senescence.
- Conducted lifespan and stress (starvation, oxidative and heat) assays on flies with transgenes expressing varied levels of Rpd3 protein in the heart tissue.
- Conducted heartbeat measurements on flies throughout various stages in their lifespan to analyze heart-function decline with age.
- Co-authorship in a paper published in Aging, and semifinalist status in the 2015 Intel Science Talent Search (STS).
Rutgers Dept. of Physics | HS Research Intern | Piscataway, NJ
June - August 2013
- Explored symmetry-breaking phase transitions in multiferroic materials (i.e. rare-earth hexagonal manganites).
- Polished and imaged these materials.
- Analyzed topological defect distribution using published theoretical results.
- Co-authorship in a paper published in Nature Physics.