Graduated with a BS in Computer Science specialized in Machine Learning and a BS in Psychology from the University of Maryland: College Park.
Experience
2024 — 2026
New York, New York, United States
Built a distributed, multi-region ML ETL orchestration framework using SNS/SQS fan-out scheduling and Lambda state-based workflow
orchestration, automating EMR and SageMaker jobs with automatic retries, idempotent execution, and cross-region VPC networking to
deliver a fault-tolerant, highly-available pipeline.
Designed reusable backend microservices and APIs, enabling downstream teams to integrate with our system and allowing our pipeline to
consume upstream team services with minimal onboarding effort.
Implemented infrastructure-as-code using AWS CDK, improving deployment consistency.
Added dashboards, alarms, and automated ticketing using CloudWatch, improving system observability and reducing on-call noise.
Modernized legacy Sponsored Brand Ads services, reducing maintenance effort across internal ad platforms.
Developed new UI cards and a recommendations page in Sponsored Brands’ Campaign Builder (TypeScript/JavaScript), surfacing
ML-generated campaign recommendations from our ETL pipeline and enabling broader advertiser adoption of automated campaign setup.
Transitioned infrastructure to a serverless micro-service architecture using ECS Fargate, ECR, Lambda, and Docker
Implemented CI/CD for ElasticBeanstalk using CodePipelines/Github and for ECS/ECR using Github Workflows
Fullstack development with ReactJS frontend and Flask backend
Implemented best practices for security using IAM
Made AWS infrastructure highly available and scalable using load balancing and auto scaling
Implemented metrics and alarms using AWS Cloudwatch
Created and maintained EC2 servers
2022 — 2022
New York, New York, United States
Implemented closed captions support on Sponsored Brand Video Ads on multiple video ad widgets
Implemented frontend framework for captions as well as a captions button
Implemented backend metadata parsing
Gated all changes behind a Weblab
Implemented metrics to track, analyze, and monitor the use of these features
Used AWS services such as S3, EC2, Athena, CloudSearch, and Lambda
Used Git for version control
Performed necessary testing and debugging in pre-prod/gamma stage
Used mock requests and responses to test end to end throughout all services
Fullstack development in HTML/Kata, Typescript, and Java
Worked on creating the Hardhat development environment for the Zap platform with a focus on oracle services.
Helped to develop and stress test a miner for mining zap tokens
College Park, Maryland, United States
Worked on the Convective Cores project focusing on using unsupervised clustering to automatically label which convective core a particular pixel belongs to and then track them through time. Once labeled we determined the average statistics of these cores and the sensitivity of the results in regard to our algorithm.
Mentored younger students helping them with python skills as well as plans to approach tasks and how to organize team dynamics for group projects.
Researched the role of clouds in weather and climate through computational analysis of very large datasets of cloud properties collected by national research institutions such as NOAA and NASA.
Coded in python to create models from big datasets to show the discrepancies between ground cloud observers and satellite cloud observations.
Studied Polar Lows in the Arctic and Antarctic regions and helped to develop a database of polar lows to be used by a machine learning algorithm to identify polar lows using object recognition and computer vision.
R Singh, E Schneider, A Friedman, R Panickar. Investigating Convective Cores in Time and Space. Presented at: FIRE Summit. November 16, 2020. University of Maryland, College Park.
Education
2019 — 2022
University of Maryland
Undergraduate
2019 — 2022
2015 — 2019
South Brunswick High School
2015 — 2019