Candidate Profile

Continuously Learning, Continuously Improving.

Mechanical Engineer

Strategic profile summary: cross-disciplinary candidate blending engineering, analytics, research, and business training with evidence-driven project work.

Education

• 2025 – 2027: M.Tech, Mechanical Engineering at Indian Institute of Technology Gandhinagar
• 2025 – 2027: Master of Business Administration (MBA) at Indian Institute of Management Visakhapatnam
• 2021 – 2025: B.Tech, Production Engineering at National Institute of Technology Agartala

Experience

• May 2024 - July 2024: Summer Intern at Tata Steel. o Investigated AM repair strategies for steel components to reduce replacement cost and downtime o Learned WAAM processes and microstructural analysis through 250+ literature sources o Developed and tested MS-SS316L graded structures using WAAM. o Authored a comprehensive first-of-its-kind review paper on metal additive manufacturing. Achieved 40% hardness increase and 10% projected lifecycle cost reduction
• May 2026 - Present: Research Intern at SWA Consultancy. Just started
• Jan 2025 - Feb 2025: GET at Kiswok. o Identified bottlenecks in NPD workflows, causing delays across product development stages o Learned project planning and dependency tracking using MS Project in a manufacturing setup o Structured process plans and tracked milestones across teams to improve coordination o Reduced cycle time by 15% and improved throughput planning

Core Skills

• Business: Data-Driven Decision
• Business: Problem Solving
• Business: Cost Optimization
• Business: Market Analysis
• Business: Competitive Strategy
• Business: Supply Chain Management
• Engineering: Computational Fluid Dynamics (CFD)
• Engineering: Finite Element Analysis (FEA)
• Engineering: Manufactuing Processes
• Engineering: Quality Management
• Engineering: Project Management
• Engineering: Additive Manufacturing
• Softwares: COMSOL
• Softwares: Abaqus CAE
• Softwares: ANSYS
• Softwares: Origin Pro
• Softwares: SolidWorks
• Softwares: Fusion360
• Softwares: CREO
• Softwares: JIRA
• Softwares: MS Projects
• Softwares: Office365
• Softwares: MATLAB
• Softwares: Mathematica
• Softwares: Gen AI
• Softwares: Python

Selected Projects

• Why Do Malls Die? A Survival, Density, and Spatial Competition Framework for Urban Retail Ecosystems: I come from the northeast (Silchar and Agartala), and we were introduced to the concept of malls rather recently. It was only in 2012 that the Goldighi Mall opened its doors in Silchar after a long construction time, followed by the ML Plaza in Agartala in 2013. Interestingly, both had BigBazar as their opening partners and for a long time, the mall was colloquially known as BigBazar. These malls instantly became the heart of their respective towns, attracting massive footfall in the initial days and, to some extent, becoming the envy of local store owners. It is worth noting that these were malls in the true sense, built over a large area, hosting multiple brand outlets (albeit not so high-end), a gaming plaza, a food court, and a cinema complex. The sunshine days for these establishments started to wane about half a decade into their operations. Things were already slowing down, and then the pandemic became the last nail in the coffin. Although neither of them has stopped operations today, their footfall is a shadow of what it was. What were once bustling centres of commerce have almost been abandoned. I observed a similar cycle in Bengaluru and Ahmedabad, and they were much more pronounced. Unlike towns in the northeast, Bengaluru and Ahmedabad are metropolises with malls sprouting on every other corner and every other day. But these new malls stand in contrast to older malls that have shut their doors. Seeing this, a question came to my mind: Why do malls die? What are the most important factors? What is the optimal density of malls for a given population? Establishing and running a mall requires significant investment, and many families' livelihoods depend on it. Hence, this question becomes significant. I have started my investigation, and I hope to have an answer soon. If anyone is interested in contributing to this work, you're welcome to reach out to me. Challenge: Action: Result:
• IITGN Academic Planner: Grad school is tough. New environment, harder classes, freedom to choose from hundreds of courses. Naturally, it was kind of confusing for me at first. So, as the first semester ended, I tried to go onto my institute's ERP system to plan my next semester, and to my utter dismay, there were no such tools to do that. So how do students navigate this? As primitive as it may sound, they use pen and paper, or none at all (some do use Excel). So, seeing this vacuum, I decided that if there is no such platform, then I will make one. One whole night, a few cups of coffee, and I finally made the platform. Challenge: Lack of tools to plan courses in the institute's ERP system, leading to confusion and primitive methods like pen and paper or Excel being used by students. Action: Created a platform, https://www.academic-planner-iitgn.vercel.app, using AI-assisted development. Result: A platform was made to fill the vacuum of course planning tools.
• Strategic Data Warehousing for Retail Profitability: The DMart Case Study: How do retailers, especially in high-volume, low-margin markets, turn operational control into sustainable profit without complex, bleeding-edge tech? This project analyzed DMart's unique strategic use of a data warehousing-enabled Management Information System (MIS) to drive precise inventory, lean supply chain, and rigorous SKU rationalization decisions. The study revealed how disciplined data management, focused on operational control over sophisticated prediction, generates a profound competitive advantage and robust margin protection. Challenge: Indian retail firms faced intense pressure from low margins and high volume, significant inventory risk, supply chain inefficiencies, and fragmented decision-making, making sustainable profitability a complex challenge. The core problem was understanding how a data warehousing-enabled Management Information System (MIS) could transform operational control into consistent, sustainable profit. Action: Analyzed DMart's business model and MIS strategy, examining its data warehousing approach, inventory and supply chain decisions, and SKU rationalization process through a strategic management information system lens. Developed key learnings about the critical role of data discipline and operational control in retail profitability. Result: The analysis identified that DMart achieved a 15% Return on Capital Employed (ROCE) advantage over traditional retailers, maintained over 60 days sales before vendor payments, and operated with 30-40% fewer products than competitors. Strategic MIS proved to be a profit governance tool, not merely a reporting system, driving sustainable margins and cost leadership.
• AI-Powered Portfolio Website: As is the case for every engineering and MBA grad, LinkedIn is a major part of personal branding, and everyone does their best to make that profile as perfect as possible. Now, for those of us old folks who lived before ChatGPT, we know that LinkedIn didn't offer many AI services, which is not at all the case today. Every LinkedIn element comes with an AI offering bundled into the Premium plan, which is fairly priced for an executive but certainly not for a fresher. Which is ironic, as freshers need the platform the most. Now, I was in the same boat, and I thought, there's no way I am paying for premium, so what do I do? I decided I will make my own LinkedIn Premium. I, assisted by AI, built the entire portfolio website, integrated AI across most aspects of the site, and added a careers section that includes AI-driven ATS screening, resume building, and job search. Challenge: Limited access to AI services on LinkedIn for those who need it most, such as freshers, due to the cost of the Premium plan Action: Built a personal portfolio website with AI integration across most aspects of the site, including a careers section with AI-driven ATS screening, resume building, and job search Result: Created a personalized alternative to LinkedIn Premium with AI-powered features
• Computational Fluid Dynamics of Converging-Diverging Rocket Nozzles: This project was done as part of Prof. Dilip Sundaram's CFD course at IITGn. The problem statement involved predicting the fluid flow through a converging-diverging nozzle. A program was developed to solve unsteady, inviscid, compressible fluid flow through a C-D nozzle using an explicit, time-marching MacCormack scheme, and the results were validated against analytical and NASA experimental data. Challenge: The primary challenge involved developing a program to accurately simulate unsteady, inviscid, compressible fluid flow through a converging-diverging rocket nozzle, and then computing steady-state flow properties across both isentropic subsonic and subsonic-supersonic flow regimes. This required correctly capturing potential discontinuities and conserving mass, momentum, and energy across the domain, all while maintaining numerical stability and accuracy. Action: Engineered a program in MATLAB to simulate quasi-one-dimensional, unsteady, compressible fluid flow through a converging-diverging rocket nozzle by implementing the MacCormack scheme to solve Euler equations. Designed and applied appropriate boundary conditions and a time-marching loop for convergence across two distinct isentropic flow regimes. Result: The numerical results for pressure, density, temperature, and Mach number profiles demonstrated strong agreement with analytical solutions and a very close tie to NASA experimental data, validating the model's ability to accurately capture real-world fluid behavior across both isentropic subsonic and subsonic-supersonic flows.