Hi There,
I'm Rokesh Prakash
i am into
About MeI’m a passionate software engineer with expertise in full-stack development, cloud computing, and AI-driven solutions. I specialize in building scalable systems using C#, Python, React.js, and cloud platforms like Azure, AWS, and GCP. My recent work includes fine-tuning LLAMA 7B for a multilingual medical chatbot and leveraging Generative AI for smarter automation.
Currently, I’m pursuing my Master’s in Computer Engineering at Stony Brook University, where I also work as a Graduate Teaching Assistant, mentoring students in programming and data structures.
email : rokesh2897@gmail.com
place : New York, USA - 11790
Aug 2024 – Present
• Enhanced students’ understanding of C and Git by conducting interactive tutorials and simplifying complex concepts through structured presentations for the ESE 124 Programming Fundamentals course under Prof. Alex Doboli (Spring 2025).
• Created lab materials, conducted lab sessions, and graded homework for ESE 224 - Advanced Programming & Data Structures at Stony Brook University (Fall 2024).
• Provided additional student support during office hours under the guidance of Prof. Xin Wang.
Jun 2021 – Dec 2022
• Contributed to the development of a U.S. retirement product, serving over 5M users with C#, Entity Framework, REST API, and SQL for backend and React.js, ELK for frontend integration and logging.
• Redesigned legacy customer notification system into a scalable, event-driven architecture using serverless architecture, message queue, and mail service, reducing delivery latency by 80% and enabling dynamic template-driven emails across 5M+ users.
• Revamped backend data flow across distributed services to improve page response times by 300% through performance profiling with ANTS and optimization of SQL queries, Redis caching, and indexing strategies.
• Architected a serverless pipeline that reduced manual Excel column-to-object mapping effort by 60%, leveraging ASP.NET Core Web API.
• Reduced debugging time by 40% by integrating Serilog with ELK stack (Elasticsearch, Logstash, Kibana) for real-time log monitoring and enhanced system observability.
• Created an intuitive dashboard for DigiMon, consolidating 10+ data streams; improved data retrieval speed by 40% for quicker decision-making.
• Received "Star of the Sprint Award" for Sprint 35, recognized for developing LTPT classification that led to a 20% increase in user engagement.
• Earned the "TEDC Kudos Award" for exceptional skills in ASP.NET, C#, MYSQL, and REST API during the TEDC training program.
Jun 2020 – Jun 2021
• Developed a Windows-based Embedded Machine Control Platform for multi-axis machines using C#, .NET Framework, WPF, and Entity Framework, enhancing automation and precision in advanced manufacturing.
• Improved system accuracy by 40% by leading the development of a low-latency, real-time video processing module using C#, EmguCV, and WPF, dynamically adjusting machine parameters to enhance reliability in performance-critical environments.
• Eliminated 30% of recurring defects and improved release speed by implementing test-driven development and clean code practices using MVVM architecture and unit testing across modules.
• Engineered a containerized software suite, achieving 60% faster setup times and eliminating configuration errors by delivering Docker images for seamless deployment across client environments.
• Increased production by 250% by developing an automated tool path generation system in C#, integrating algorithmic optimization for efficient machining.
• Spearheaded projects with Dr. Sathyan Subbiah from IIT Madras, integrating AI and IoT technologies into advanced manufacturing, leading to a 40% reduction in production time and a 25% increase in quality.
May 2019 – May 2020
• Achieved 96% accuracy in textile fiber identification using a CNN model built with Python, TensorFlow, and Keras.
• Simplified fabrication for prosthetic legs using a C++ OpenCV-based measurement system with 0.05 precision.