Feb 2025 – Present · 1 yr 4 mos · Remote

• Research collaboration with NASA Ames and the University of Idaho, focused on structural bioinformatics and AI/ML applications:
• Developed Conducted bioinformatics-driven analysis of atomic structures of amino acids within protein chains using Chimera, PyMol and BioPython to extract 3D spatial and chemical features
• Engineered atomic-level graph embeddings from PDB kinase structures using Graph2Vec and Graph Neural Networks (GNNs) as part of a structural bioinformatics pipeline
• Constructed molecular graphs with NetworkX and Karateclub, testing use-cases like Graph2Vec, MEGNet and SE3 Transformers, to encode structural similarities for unsupervised Geometric Graph Neural Network based clustering of active/inactive protein conformations
• Applied statistical modeling and dimensionality reduction (PCA/UMAP/t-SNE) to validate embedding quality and optimize clustering in bioinformatics workflows

Feb 2024 – Present · 2 yrs 4 mos · Remote

• • Collaborated on an open-source protein research project at NASA Ames Research Center using AlphaFold and machine learning for protein structure analysis

Oct 2024 – Oct 2025 · 1 yr · Piscataway, New Jersey, United States · Remote

• Gosalus Project:
• Led a multi-phase HR–provider data integration project, building MSSQL backend, data models, and API integrations improving system interoperability by 30%
• Built Power BI dashboards and SQL analytics that identified data integrity issues and improved reporting accuracy by 25%.
• Implemented Azure Synapse RBAC, compliance workflows, and automation, reducing manual effort by 15+ hrs/week and ensuring secure deployments

Mar 2024 – Jan 2025 · 10 mos · Fremont, California, United States · On-site

• Client: Fremont Unified School District
• (via SkyTech Services Inc from Oct 2024 on Corp-to-Corp)
• Led a team of 6 to deploy scalable ETL pipelines Python, SQL, Azure Synapse, and Power Platform, cutting runtime by 25 hours/week and boosting data reliability
• Boosted cross-platform data exchange efficiency by 30% through strategic API integrations and schema mapping, streamlining legacy- to-cloud migration
• Designed ERP-integrated dashboards and automated pipelines with Power Platform and SharePoint, using A/B testing to align KPIs and boost finance reporting transparency
• Built automated software for 2,500+ laptop allocations and HR data via automated Google Sheets, Power Platform and SharePoint, saving $100K+ annually and adopted as a lighthouse project statewide
• Mentored team members on Power Platform, saving 2 hours daily through improved workflows and scalable BI practices

May 2023 – Aug 2023 · 3 mos · San Ramon, California, United States · On-site

• Analyzed Pole and Tree inspection data using Power BI for PG&E, achieving a 70% reduction in dashboard data load time.
• Integrated SQL, Python, and Power Automate for an ~80% weekly performance boost in workflow automation.
• Administered Power BI, managing access and controls based on role and designation.
• Assisted fellow teammates in debugging errors and resolving DAX issues to ensure efficient and optimized functioning of dashboards.

May 2022 – Dec 2022 · 7 mos · Fremont, California, United States · On-site

• Monitored infrastructure project invoices using a MySQL database and an interactive Tableau dashboard, delivering weekly email updates on payment dues to the teams.
• Crafted a visually captivating Power BI dashboard, enhancing the re-entry process by providing executives with valuable insights for office space planning and capacity management across a workforce of 110,000 employees.
• Engineered an optimized data model to streamline the collection of procurement and project data from diverse databases, significantly reducing Power BI data load time.
• Utilized SQL and Python to analyze procurement data from multiple databases, presenting insights through Power Query, DAX, and Power BI to Tesla leadership, identifying profit opportunities.
• Researched and analyzed 100+ construction projects, applying statistical analysis. Developed an efficient financial automation tool with PowerApps and Power BI, saving 4 hours monthly.
• Integrated Power Apps and Power Automate Flows with Power BI to track metrics, leading the rollout of a notification workflow for efficient team updates.
• Streamlined user access and maintenance of Power BI and Power Apps using Azure Active Directory.
• Mentored and managed new hire interns and teammates, overseeing tasks, providing query support, and assisting with debugging to ensure a smooth learning curve.
• Collaborated with engineering and supply chain teams to enhance a construction project's bill of materials (BoM), resulting in a 25% improvement in cost, quality, and delivery efficiency for optimized vendor quotes.

Feb 2022 – May 2022 · 3 mos · Dallas, Texas, United States · Remote

• Conducted data preprocessing on floor plan images using Computer Vision Annotation Tool.
• Utilized OpenCV Python for precise image processing and annotation of floor plan elements.
• Developed a Mask R-CNN machine learning model for automated blueprint labeling, achieving a 90% improvement in entity identification.

Jan 2022 – Sep 2022 · 8 mos · Dallas, Texas, United States

• Machine Learning Super-Resolution for Remote Sensing and OpenDataCubes
• Working in the Lary Research Group:
• https://davidlary.info/
• Developed a containerized instance of the Open Data Cube and associated data ingestion scripts to enable collection and processing of imagery with machine learning from NASA satellites like Landsat, Modis, and Sentinel.
• Performed data ingestion in Docker Container and indexed the images on longitudes and latitudes using Jupyter Notebook and Ubuntu WSL, starting from Richardson, TX.

Sep 2021 – Dec 2021 · 3 mos · Dallas, Texas, United States

• Effects of COVID-19 on Accident Severity
• Focused on the research developments of risk factors associated with road accident severity, feature selection methods in the field of traffic safety, and classification algorithms for the prediction of accident severity.
• Verified machine learning models like Support Vector Machine, Neural Networks, and Logistic Regression using feature selection algorithms on factors that can contribute to predicting road accident severity.
• Performed research on stacking model in machine learning, to improve the accuracy of prediction of road accident severity by at least 70% to 80%.

Aug 2018 – Aug 2019 · 1 yr · Hyderabad, Telangana, India

• Contributed to an 80% improvement in Flex onboarding efficiency while overseeing daily reporting for diverse businesses, leveraging Advanced Excel Functions for metric crafting.
• Enhanced team efficiency by 75%, skillfully resolving on-site issues during customer deliveries.
• Implemented Microsoft Power Automate and Python, streamlining processes and enhancing metrics visibility, significantly contributing to organizational growth and operational efficiency by 40%.

Jan 2018 – Mar 2018 · 2 mos · Bengaluru, Karnataka, India

• Designed and implemented conference hall booking system using Sybase, MySQL, HTML and Java technologies for ISRO employees that eliminated conflicting booking for conference rooms and improved the process by 99%.

May 2017 – Jun 2017 · 1 mo · Bengaluru, Karnataka, India

• Created a materialized view project using multidimensional data modeling using procurement data by extracting data from Sybase and used interface with COWAA, by writing MySQL queries in SQLdbx, and designing a user interface HTML, CSS, and JAVA helping ISRO to make efficient business decisions by analyzing the data generated in the result.