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

• Devised custom AI tools for computerized 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 and datasheets retrieval, and processing workflows for LLM distillation.

• Developed a Python based system that translates natural language queries into Altium Designer's PCB Query format using EDIF netlist analysis and custom scoring, implementing intelligent component filtering on Altium's Filter pane.

• Performed Total Addressable Market (TAM) analysis by integrating 330M+ LinkedIn profiles with Altium's 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 informing strategic market entry decisions.

• Programmed 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 by establishing link tables using Data Vault 2.0, deduplicating data from 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 streamlined deployment.

• Drove Altium's market penetration through data-driven strategic marketing, securing 40+ college partnerships and integrating Altium's curriculum, which expanded the company's operational footprint with enduring commercial impact.

ChemCopilot (Technical Contribution) Remote, California, US

• Architected 7 AI agents using LangGraph for chemical sustainability workflows (BOM generation, toxicity analysis, CO₂ estimation, ingredient substitution, ESG reporting) with multi-agent orchestration, state management, and parallel processing across database queries, web search, and vector similarity matching. Created using Python, LangChain, OpenAI, Streamlit, Tavily, and SQLite.

• Engineered context-aware natural language to SQL translation system with prompt engineering for real time data retrieval from 50k+ beauty product records and 600k+ chemical toxicity datasets. Implemented FAISS-based RAG system for semantic document search across thousands of chemical specifications, enabling accurate toxicity profiling and regulatory compliance validation.

• Designed molecular similarity search engine using SMILES fingerprinting for intelligent ingredient substitution recommendations. Built what-if analysis engine enabling instant environmental and financial impact assessment for sustainable formulation decisions, with automated sustainability scoring algorithms, interactive visualization generation (Sankey diagrams, decomposition charts).

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.