Hello, I'm Mukesh Gautam
.NET Full Stack Developer specializing in building scalable enterprise applications with modern technologies and cloud solutions
About Me
Get to know more about my journey and passion
Mukesh Gautam
Project Engineer - .NET Full Stack DeveloperI'm a Project Engineer (.NET Full Stack Developer) at Wipro Limited, specializing in enterprise-level applications with ASP.NET Core, React, and Azure. I graduated from Sikkim Manipal Institute of Technology (July 2024) with a B.Tech in Computer Science.
My research experience at IIT BHU focused on machine learning applications in materials science, where I developed deep generative models for discovering novel 2D materials, demonstrating my ability to apply cutting-edge technology to solve complex challenges.
Education
B.Tech CSE - SMIT
Current Role
.NET Developer - Wipro
Research
ML Intern - IIT BHU
Experience & Internships
My professional journey and work experience
Project Engineer
Wipro Limited
March 2025 - Present | Hyderabad, India- Underwent rigorous technical training in C#, .NET Core, SQL Server, React, and Azure fundamentals
- Built multiple POCs (proof-of-concept) and internal mini-projects using ASP.NET Core and React to strengthen full-stack development skills
- Practiced unit testing, clean architecture principles, and followed agile methodologies in mock project environments
- Developing expertise in modern web technologies and enterprise application development
- Gaining hands-on experience with cloud solutions and Microsoft Azure platform services
- Following industry best practices for code quality, testing, and software development lifecycle
Research Intern
IIT BHU (Banaras Hindu University)
January 2024 - July 2024 | Varanasi, India- Developed a deep generative model to identify novel 2D materials using advanced machine learning techniques
- Conducted comprehensive data preparation including extraction, preprocessing, and featurization from multiple databases (Materials Project, C2DB, 2DMatpedia, C1DB, MC3D)
- Generated 100,000 new material formulas using a GAN model, with 17,949 valid and unique formulas after applying rigorous validity checks
- Screened potential 2D materials using a Random Forest classifier, resulting in 1,492 promising screened 2D formulas
- Predicted properties of the valid 2D formulas utilizing Pymatgen library for computational materials science
- Applied cutting-edge machine learning techniques for materials discovery and computational chemistry research
Technical Skills
Technologies and tools I work with to build innovative solutions
Frontend
Backend
Cloud & DevOps
AI & ML
Core Competencies
Tools & Platforms
Featured Projects
Showcasing my work in AI, full-stack development, and cloud deployment
Contact Me
Let's connect and discuss how we can work together
Get in Touch
Feel free to reach out for collaborations, opportunities, or just a friendly chat.