Career Profile
Hi, I’m a software engineer interested in anything AI & ML related. I have recent experience working with Airflow and standing up data and model update pipelines. Have also taken various courses at Stanford and earned a few graduate certificates along the way.
Experiences
- Established Airflow orchestration for updating machine learning models and periodic tasks
- Created daily model updates for similarity recommendations with Airflow and Docker
- Simplified alert and trigger management to assist in alert triage and incident response
- Adapted network namespaces in Linux cgroups for use in acceleration layer virtualization
- Virtualized software acceleration layer for the security appliance
- Authored OS configuration pages for network management protocols (SNMP, VRRP, IGMP, PIM)
Education
Studied relational systems, query languages, and system implementations.
- CS145 - Data Management and Data Systems
- CS245 - Principles of Data-Intensive Systems
Covered deep learning and worked on projects with multi-modal architectures.
- CS221 - Artificial Intelligence: Principles and Techniques
- CS224N - Natural Language Processing with Deep Learning
- CS231N - Convolutional Neural Networks for Visual Recognition
Learned machine learning techniques, social networks, and search algorithms.
- CS224W - Analysis of Networks
- CS229 - Machine Learning
- CS246 - Mining Massive Data Sets
- CS276 - Information Retrieval and Web Search
Studied the theory behind most data science models.
- STATS202 - Data Mining and Analysis
- STATS216V - Introduction to Statistical Learning
- STATS315B - Modern Applied Statistics: Data Mining
Projects
Interesting projects from Insight's Data Engineering fellowship and graduate courses at Stanford
Fast Fashion Recognition
- Streaming image classification with Inception Neural Network using Kafka, Spark, and Cassandra
Network Anomaly Detection with GCNs and GATs
- Graph Convolutional Networks and Graph Attention Networks to detect fake Twitter users
Pix2Code
- Automatic Code Generation from UI Screenshots
Attention on Attention
- Attention Architectures for Visual Question Answering (VQA)
Bitcoin Trust Networks
- Network Analysis of Weighted, Signed Bitcoin Networks
Deep Q-Learning with RNNs
- Attention Mechanisms in DQN/DRQNs for Atari Games