Srinadh Alugu

• Working as a student researcher on applied machine learning and deep learning projects in the context of robotics and intelligent systems • Designing and implementing data-driven solutions for time-series and sensor data, including model development, evaluation, and optimisation • Contributing to research and prototype development involving deep learning architectures and decision-support systems • Collaborating in an academic research environment to document results and support experimental validation •

• Conducting Master’s thesis on Human Activity Recognition (HAR) using sensor data and Large Language Models (LLMs) • Designing time-series data processing pipelines, including windowing and extraction of time-domain and frequency-domain features • Implementing zero-shot and few-shot LLM-based classification approaches through prompt engineering • Analyzing the impact of feature representation and prompt structure on classification performance • Evaluating experimental results using accuracy, F1-score, and

• Conducted data-driven analysis of automotive engine management systems, including fuel injection and ignition parameters • Analyzed sensor and system-level data to support optimization of engine and powertrain performance • Performed data preprocessing, exploratory data analysis (EDA), and feature engineering for automotive applications • Evaluated operational characteristics of manual and automatic transmission systems using quantitative performance metrics • Documented insights and data analysis workflo

- Completed an intensive MATLAB Master Class, gaining expertise in data analysis, signal processing, image processing, and control system design. - Worked on hands-on projects to develop algorithmic problem-solving and simulation skills using MATLAB. - Applied MATLAB for numerical computing, visualization, and automation in engineering applications.

- Underwent industrial training on "Study on Foundry", gaining insights into metal casting, molding, and production processes. - Observed casting techniques, furnace operations, and material selection for manufacturing industrial components. - Studied quality control measures and defect analysis in foundry production to ensure high-precision manufacturing. - Learned about melting, pouring, and solidification processes used in heavy machinery production at BHEL.

- Underwent industrial training on "Study on Boiler and Overview", gaining hands-on exposure to thermal power plant operations and energy generation processes. - Analyzed the working principles of boilers, turbines, condensers, and heat exchangers used in large-scale power generation. - Studied steam generation, fuel combustion, and efficiency optimization techniques in thermal power plants. - Observed safety protocols, maintenance strategies, and operational best practices in a real-time power plant enviro