Sartaj Bhuvaji

Developing and scaling machine learning models into production.

• Developed machine learning models to predict hypervisor failures proactively, improving system reliability. • Designed and prototyped solutions that laid the foundation for scalable production systems.

• LLM class (5910) labs and demos. (July-204 - July2025) • Explored LLM Fine-Tuning, LORA, PEFT, RLHF, RAG, vLLM Research Guide: Dr. Steve Hanks Explored ways to improve classification performance in data-starved medical applications. • Pioneered a selection-based boosting framework for SMOTE variants, delivering up to 7.8% sensitivity gains on minority classes. • Designed and benchmarked single-encoder, balanced, and heavy-decoder models—achieving a 28% boost in sensitivity in low-data settings. • Applied KL divergence, KDE and Gretel scoring to verify realistic, diverse synthetic samples that outperform CTGAN and vanilla SMOTE. • Validated improvements across Decision Trees, K-NN, Logistic Regression, Naive Bayes and transfer-learning classifiers on a 26-patient asthma cohort. Research Guide: Dr. Wan Bae

CPSC 5330 Big Data Analytics (Mar 2023 - Jun 2024) • Professor: Dr. Steve Hanks CPSC 5200 Software Architecture and Design (Mar 2023 - Jun 2024) • Professor: Dr. Xin Zhao CPSC 5910 Software Refactoring & Design (Jan 2023 - Mar 2024) • Professor: Dr. Xin Zhao CPSC 5610: Artificial Intelligence (Sep 2023 - Jan 2024) • Professor: Dr. Wan Bae

In my role as a Software Developer Engineer at Tata Consultancy Services, I contributed to designing and optimizing mission-critical systems for financial institutions, specifically focusing on Anti-Money Laundering (AML) processes for CIBC Bank. I developed components of the AML platform, optimized ETL pipelines, and led the development of RESTful APIs, achieving significant improvements in processing time and data retrieval speed. • Enhanced ETL workflows using Informatica PowerCenter and SQL procedures • Optimized CI/CD pipelines using Jenkins and Docker for zero-downtime releases • Partnered with business stakeholders to deliver 20+ enhancements in production

Courses: Machine Learning, Distributed Systems, Big Data Analytics, Visual Analytics

Courses: Machine Learning, Data Analytics, Operating Systems, Database Systems, Data Structures