Arizona State University Tempe, Arizona, US

Data Visualization, Python for Rapid Engineering, Data Processing at Scale, Machine Learning, Knowledge Representation, Artificial Intelligence, Statistical Machine Learning, Game Theory

PES University Bengaluru, Karnataka, India

Data Structures, Algorithms, Database Management, Introduction to Computing, Digital Image Processing, Embedded Systems, Logic Design, Computer Networks, VLSI, Signal Processing

Altium (acquired by Renesas in 2024) La Jolla, California, US

• Built custom AI tools for automated component classification, datasheet parsing and enrichment, reference design recommendation, and block diagram extraction. Implemented knowledge base generation to accelerate engineering workflows.

• Designed intelligent automation pipelines for electronic design, including CNN–based schematic and component detection, schematic retrieval, and processing workflows for LLM distillation.

• Performed Total Addressable Market (TAM) analysis by integrating third-party LinkedIn user data with Altium's first-party software usage data using Python and SQL in Snowflake. Analyzed user job descriptions to identify potential users and categorized them into specific personas by leveraging LLMs for classification to target relevant users for marketing strategies.

• Developed an end-to-end caricature drawing system to demonstrate Renesas 365 using Python, OpenCV, and G-code generation to convert camera images into SVG drawings for a Rotrics DexArm, controlled by a Renesas RZ/V2L processor. Integrated paper detection via VL6180 time-of-flight sensor with Renesas RA0E1 microcontroller (I2C/UART).

• Created a unified Employee Entity in Snowflake by establishing link tables using Data Vault 2.0 methodology, integrating and deduplicating user data from multiple sources, including UKG, Jira, and Salesforce.

• Conducted discrepancy analysis between Salesforce Opportunities data and corresponding Snowflake database, identifying and resolving inconsistencies in counts and opportunity close dates to ensure accurate daily data integration for reporting.

• Integrated an AI chatbot (Anything LLM-GPT 3.5) within the company intranet to answer queries based on the documentation hosted on the website. The Python-based tool was containerized as a Docker image for deployment.

• Drove Altium's market penetration with data driven strategic marketing by securing partnerships with 40+ prominent colleges, facilitating Altium's curriculum integration, and expanding the company's operations footprint with enduring commercial impact.

ChemCopilot (Technical Contribution) Remote, California, US

• Developed AI tools for chemical sustainability (BOM generation, toxicity analysis, CO₂ estimation, chemical substitutions) using Python, LangChain, OpenAI, Streamlit, Tavily and SQLite. Built context-aware natural language to SQL/web search translation with advanced prompt engineering for real-time data retrieval.

• Implemented advanced analytics enabling "what-if" analyses and chemical process modeling, allowing users to instantly assess environmental and financial impact for sustainable formulation decisions. Integrated external beauty product and toxicity datasets with automated ingestion pipelines for comprehensive ingredient analysis.

• Architected vector-based knowledge retrieval system using FAISS for document search across thousands of chemical specifications, enabling accurate toxicity profiling and regulatory compliance validation through document parsing and semantic matching.

Arizona State University Tempe, AZ, US

• Conducted an extensive analysis of COVID-19 trends, with a particular focus on the years 2020 to 2023. My research delved into the dynamics of the pandemic, the effectiveness of measures implemented, and their influence on different U.S. states. Specifically Arizona, Alabama, and Vermont served as insightful case studies.

• Leveraged spatial-temporal data analysis to explore the relationships between COVID-19 vaccinations, masking policies, and case trends. We aimed to determine the extent to which these interventions contributed to reducing the spread of the virus.

• Explored trends, spikes, and declines in COVID-19 cases, hospitalizations, and deaths. My work shed light on the complexities of the pandemic and the multifaceted factors influencing its trajectory.

• Identified and depicted critical hospital staffing shortage data, providing valuable insights into the challenges faced by healthcare facilities during the pandemic.

Deloitte India (Offices of the US) Bengaluru, Karnataka, India

• Built and delivered 20+ comprehensive reports (time series charts, graphs, maps, KPIs) using Power BI and SQL (Azure Databricks Spark), providing stakeholders with actionable business insights and guiding strategic decision-making.

• Transformed unstructured data into detailed data models and mappings to track and analyze spend, payments, and supplier utilization, achieving 100% compliance and enhancing operational efficiency.

• Optimized SQL query performance using Joins, CTE's, window functions and sub-queries resulting in increased interface responsiveness of dashboards related to Procurement, Legal, Security by 40%.

• Automated integration of 8 public datasets on immunocompromised individuals using AWS lambda (Python), Power Query to establish real-world evidence (RWE) and assess COVID-19 impact in devising vaccination strategies.

• Configured source-to-target connection and designed data flow mappings in Informatica BDM for ETL jobs. Achieved 100% workload automation by scheduling and supervising Tidal data lake job loads, ensuring seamless integration.

• Led user acceptance and A/B testing to implement 200+ critical feature enhancements. Documented technical design to support data management and guide future developments.

Nokia Solutions and Networks Bengaluru, Karnataka, India

• Revamped a tool from Go language to Python to accept a template Call Session Control Function (CSCF) file used for managing signaling from end users to generate 10 generic XMLs and eliminate manual efforts.

• Wrote Bash scripts to perform MD5 checks for four file systems to ensure information is in the same state.