Raviteja Nandam

Developed a client-facing loan repayment risk assessment system, implemented Logistic Regression and integrated multiple ML models for next-month EMI prediction, and exposed REST endpoints while coordinating frontend integration and IIS deployment for client demonstrations.

Designed and implemented a GPU-accelerated matrix-profile framework for time series anomaly detection, achieving up to 6.76× speedup over state-of-the-art methods while preserving detection accuracy on benchmark datasets.

Maintained and validated production-critical mainframe systems, executing low-level system and integration testing using structured test cases and debugger-assisted inspections to ensure stability of C-based components.

Designed and built a stock portfolio management backend with RESTful APIs, integrated external broker APIs for real-time order placement, and designed a relational schema to manage portfolios, transactions, and trade history.

Grade: 9.11 / 10

Activities and societies: Master's thesis research, Teaching Assistant for C Programming, Compiler Design, Operating Systems, and GPU Computing.

Completed M.Tech with thesis on GPU-accelerated time series anomaly detection, focusing on matrix-profile-based discord discovery and large-scale GPU implementations.

Grade: 7.87 / 10

Activities and societies: Undergraduate coursework and lab projects in programming and core CS concepts.

Completed B.Tech with coursework and lab-based learning in core computer science subjects and foundational programming.