About
Highly motivated and results-driven Electrical Engineering student with a strong foundation in Machine Learning, AI, and Data Science. Proven ability to apply advanced analytical techniques to solve complex problems, as demonstrated through technical research internships at Siemens and Tata Consultancy Services. Skilled in developing innovative solutions, optimizing processes, and leading initiatives, with a commitment to leveraging technology for impactful outcomes.
Work
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Summary
Focused on improving power system state estimation accuracy by integrating diverse data sources using advanced machine learning techniques.
Highlights
Addressed the challenge of enhancing power system state estimation accuracy by integrating abundant SCADA data with precise PMU measurements, overcoming PMU deployment limitations.
Designed and implemented a machine learning algorithm utilizing Gaussian Process Regression to synthesize PMU-like values from SCADA data, significantly improving state estimation accuracy for robust power grid monitoring.
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Summary
Contributed to enhancing software compliance workflows and ensuring ethical AI behavior by developing advanced algorithms and conducting in-depth research on LLM guardrails.
Highlights
Identified and addressed a critical inefficiency in FOSSology's copyright analysis, where false positives led to significant manual review effort and slowed compliance workflows.
Engineered and implemented a novel algorithm leveraging distance methods and lexical analysis to accurately detect and flag false positive copyright cases, reducing manual validation needs.
Significantly streamlined copyright validation processes, enhancing tool efficiency and reducing manual effort for software compliance teams.
Conducted comprehensive research and evaluation of Large Language Model (LLM) "guardrail" frameworks and open-source tools, focusing on mechanisms to prevent harmful outputs and ensure ethical AI behavior.
Analyzed critical challenges and limitations within existing guardrail implementations, proposing actionable improvements to enhance the effectiveness and robustness of Siemens' AI safety protocols.
Volunteer
Education
Awards
CP101
Awarded By
IIT Mandi
Ranked in the top 10 in a competitive programming contest among 300 participants, demonstrating strong algorithmic and problem-solving skills.
E-cell Business Case Study Competition
Awarded By
IIT Mandi
Secured 1st place in the Business Case Study competition, showcasing strong analytical and strategic capabilities.
ACM-W Debugging Contest
Awarded By
IIT Mandi
Secured 4th Position in a challenging Debugging contest, highlighting proficiency in code analysis and error resolution.
Languages
English
Fluent
Skills
Programming Languages
Python, C++, HTML/CSS, Javascript, Verilog.
Machine Learning & Data Science
Machine Learning, Deep Learning, Natural Language Processing (NLP), Gaussian Process Regression, Naive Bayes, XGBoost, Random Forest, Logistic Regression, K-Means, Scikit-learn, Numpy, Pandas, Matplotlib.
Developer Tools & Platforms
VS Code, Git, GitHub, Xilinx Vivado, MATLAB, LT Spice.
Web Development
HTML, CSS, Front-end Development.
Database Management
DBMS.