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Schedule Interview NowMy name is Mahendra G. and I have over 8 years of experience in the tech industry. I specialize in the following technologies: Microservice, ASP.NET, C#, Windows Presentation Foundation, Windows App Development, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I’ve worked on include: CUDA Electric Field Line Simulation, Molecular Structure Recognition, OCR Model Trainer with Custom Feature Engineering, Force Field Vector Evaluator & Visualizer. I am based in Noida, India. I've successfully completed 4 projects while developing at Softaims.
I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.
Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.
I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.
Main technologies
8 years
1 Year
4 Years
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Potentially possible
Microsoft India
High-performance physics simulation built in C++ with CUDA, OpenGL, and OpenAL, modeling charged particle interactions in real time. Implements Coulomb’s law and Newtonian motion with randomized charges, dipoles, and adaptive updates for stability. CUDA accelerates electric-field computation across thousands of vectors per frame. OpenGL renders dynamic 3D field lines with camera controls and alpha blending. OpenAL adds spatialized Doppler-shifted audio, showcasing GPU computing, computational physics, and real-time graphics.
A specialized desktop tool that accurately interprets chemical structure diagrams—including branched dendritic molecules like PG5 dendrimers—from images. Using advanced contour detection, optical character recognition, and vector-based parsing, the system reconstructs molecular skeletons, bonds, and labels. Demonstrated capability to process intricate molecular images, significantly enhancing research and educational workflows in organic chemistry.
Built a desktop tool that converts diverse fonts into 21×21 grayscale images, extracts 64‑dimensional feature vectors through custom pixel-region analysis, and trains OCR models using ML.NET with LightGBM, SDCA, Naive Bayes, and TensorFlow. Delivered high-accuracy glyph recognition via a clean UI with augmentation sliders and engine selection—ideal for specialized OCR needs. (Screenshot shows selectable fonts, feature settings, and data loading progress.)
Developed a versatile desktop tool for defining and visualizing symbolic vector fields—covering poles, dipoles, and arbitrary mathematical expressions. The app renders precise vector plots and equipotential overlays to analyze classical field interactions, zones, and behaviors. Designed for STEM applications, this tool provides developers and researchers with visual validation of field logic before full-scale simulation.
Bachelor of Engineering (BEng) in Electronics & Computer Science
2003-01-01-2007-01-01