CDSS

Cortex Data Lake- Stream Services

Teaching Assistant for CSE 347 Analysis of Algorithms, CSE247 Data Structure and Algorithms.

Tutor for Math 217 Differential Equations, Math 309 Matrix Algebra.

Conducted projects on Principal Component Analysis, Auto Encoders, Supervised Algorithm, and Information Processing in Artificial Neural Networks using Python. Read and discuss neuroscience, information theory, and machine learning papers. Analyze encoding, decoding and propagation algorithms used in papers.

• Implemented and emitted metrics for streaming services to capture data flow job behaviors using Java, Spring, Kubernetes. Create Grafana dashboards to visualize and monitor services latency, availability and customers activities.

• Designed and implemented algorithms for a better logging rate limiter to suppresses logs up to 87%. Added TraceID to logs to chain the entire streaming service and capture critical log information.

• Used feature engineering and feature selection on JD SMS service data. Used Variance method and XGBoost Model to rank and select ideal features for model input. Implement DeepFM and DNN model with low-api and high-api to test on the SMS data to predict Click Through Rate for SMS Product Advertising business with AUC of 76%.

• Read and discussed Transformer and Informer Paper. Implemented Deep Interest Network and used open source Movie dataset to test model behavior with accuracy of 96% and AUC of 74%.