Galav Bhatt

● Analyzed the correlation between blockchain network modularity and market volatility spikes to identify structural indicators of liquidity shocks. ● Modeled systemic risk in digital assets using flow concentration and centrality metrics to predict how shocks propagate across address networks.

● Developed ClimaCity, a spatial visualization tool, by engineering a data pipeline in Python (GeoPandas, Rasterio) to process and reproject 100GB+ of environmental and demographic raster data into web-compatible GeoJSON formats. ● Integrated RCP 4.5 and RCP 8.5 climate frameworks and calculated precise pixel counts for 19 distinct land-use types across 32,000+ US cities for decadal comparative analysis of urban heat risks from 2010 to 2100.

At L&T Special Steels and Heavy Forgings, serving nuclear, defense, aerospace, and energy sectors, I lead Industry 4.0 initiatives as a Senior Engineer integrating shop-floor data with enterprise systems to deliver digital solutions that enhance visibility, efficiency, and decision-making. Key Digital Initiatives to enhance plant productivity: • Directed the Steel Melting Shop digitalization initiative, leading a 10-member developer team to integrate over 1000 field sensors with PLC controllers and MS SQL Server, enabling 25 web application pages for real-time liquefying process analysis critical for executing nuclear sector jobs worth $10 million. • Led the digitalization of over 30 forging process logsheets using the Django web framework, cutting 10 hours/week in ISO reporting and enabling actionable insights for $100K-per-cycle forging processes. • Spearheaded the development of a Machine Shop Tools Spare Management System to track ~$50K/month tool consumption and enable project-wise material usage analysis for the estimation department. • Oversaw the development of a maintenance module to manage electrical, mechanical, power, and utility preventive schedules, providing detailed analysis for 110+ pieces of equipment and plant-wide production efficiency for senior management. • Optimized machine shop cutting time by integrating 23 lathe machines with PLC and MS SQL Server; automated utilization reports and email alerts for senior management which boosted shop efficiency from 46% to 64% through active monitoring and 5S methodology implementation in Job alignment. • Designed network architecture to integrate over 250 NG flow meters with PLC and MS SQL Server, and developed a Power BI dashboard to monitor $900k/month natural gas consumption and assist the estimation team with project-wise NG utilization analysis.

Began my career as a graduate engineer trainee in the Electrical & Automation Department at LTSSHF • Trained on Steel Melting Shop manufacturing processes and managed preventive and breakdown maintenance for over 200 critical electric equipment associated with the Electric Arc Furnace, Ladle Refining Furnace, Vacuum Degassing, and Vacuum Oxygen Degassing System. • Developed a Python solution to automate the heat treatment cycle analysis for NPCIL nuclear reactor components, which cost approximately $1 million each, by integrating temperature recorders with MS SQL and visualizing the data using Matplotlib. • Ensured government regulatory compliance by transmitting 10 furnace emission data (NOx, SO2, SPM) to the Central Pollution Control Board (CPCB) using an IoT device. • Trained in electrical & automation technology, manufacturing processes, project management , and software skills including MS SQL Server, Python, Django, CAD and data analysis.

• Managing internal and external affairs associated with IEEE BVM Student Branch. • Organizing mentor of flagship event on International Colloquium on Emerging Technologies (ICET’2021), which had renowned international speakers to impart knowledge on cloud computing, artificial intelligence, and blockchain technology to over 1000 academicians and professionals. • Organizing Co-Lead at an international event on Virtual Visit on Modern Physics 2020, which enabled more than 2000 participants to leverage the virtual visit of the ATLAS experiment at CERN Laboratory by Dr. Steven Goldfarb and Dr. Clara Nellist.

• Implemented smart parking system by utilizing MATLAB, Arduino Uno, and neural network to automate license plate recognition and achieved 90% accuracy. • Engineered predictive maintenance system with 87% accuracy using MATLAB to detect motor faults by analyzing vibration, temperature and current data. • Trained the model with 85% precision using deep learning toolbox of MATLAB to enhance classification of ripeness in fruit images.

● Developed and executed student engagement strategies for IIM Ahmedabad’s annual cultural fest, CHAOS’21, featuring 150+ business events, leadership talks, and entrepreneurial competitions. ● Planned targeted outreach campaigns that successfully drove 110 student registrations from my institute, maximizing participation and networking engagement opportunities.

Coursework :- Fall 2025 Optimization Models and Methods. Probability and Statistics. Industry Project in Operations Research and Analytics.

Coursework Service Operations Management

CGPA: 8.75/10, Department Rank:3rd (Secretary at IEEE BVM SB, Tech Lead of Annual Cultural Fest – UDAAN’22, General Event Manager at BVM Student Council)