N times exceptional performance rating but no further appreciation from senior leadership

Past internal tech talk topics:

* Snowflake Kafka connectors

* Java to Kotlin migration

* Modern Airflow best practice

Responsibility: Working for the team of loans platform, with a concentration on data processing and AI-driven self-service portal. Primarily focusing on full-stack development and data pipeline, using PostgreSQL/MongoDB as db, Kafka as streaming, dbt-core as modeling, Snowflake as a cloud warehouse, gradle-plugin flyway as db migration, AWS Airflow as a data orchestration tool, Monte Carlo & Datadog as monitoring tools, Kotlin/Springboot as microservices, and React.js/MUI as UI.

[2023 Spring] Associate II of ELEN 6889 Large Scale Stream Processing under the supervision of Deepak

[2022 Fall] Teaching assistant of COMS 4995 deep learning for computer vision course under the supervision of Prof. Peter N. Belhumeur

[2022 Spring] Serve as a course assistant of COMS 4732 under the supervision of Prof. Carl Vondrick in 2022 spring

AutoML along with auto data preprocessing and transforming everything into a pipeline, deployed and dockerize model online via microservices with Amazon Web Service Lambda as a S3 proxy in API gateway

Working in the Metropolis team, with a focus on multi-target multi-camera tracking (MTMC) streaming data pipeline with Apache Kafka. We primarily worked with an in-house dataset for people tracking, which was used as the problemset in 2023 AI City Challenge. We set up a baseline for people tracking across the cameras with multi-dimensional associations. This can be found on NVIDIA GTC summit 2022 special track presentation.