Hi, I'mRakesh Bodapatla
I craft exceptional digital experiences with code, creativity, and a passion for innovation.
About Me
I'm a passionate software engineer driven by curiosity and the thrill of building things that work beautifully. I specialize in backend development with Node.js and Redis, and I’ve been exploring the world of machine learning to bring smarter, more adaptive systems to life. While I love optimizing what’s under the hood, I’m equally comfortable collaborating across the stack. Give me a problem, and I’ll probably obsess over it until it’s solved or until it starts solving itself.
When I'm not coding, you can find me exploring new technologies, playing cricket, or catching up with friends and family.
My Skills
Featured Projects
MeetSync (In Progress)
Bringing friends together in the city by smartly matching their vibes, budget, distance, and all, so every meetup feels just right
TinyGuard
An ultra-lightweight model distilled from a larger CNN, optimized to just 0.05KB using Knowledge Distillation for detecting compromised IoT devices in resource-constrained environments
Epileptic Seizure Detection
Hybrid CNN-TCN Model for Epileptic Seizure Detection from EEG Signals
Receipt Rocket
An end-to-end image processing pipeline that segments, corrects, and extracts receipt data, clean results without the overhead of machine learning.
Pneumonia Detection + XAI
An intelligent Pneumonia detector that aids medical professionals by identifying and highlighting the most likely affected regions enhancing diagnosis speed and confidence.
Work Experience
Data Scientist Intern
Research and development on state-of-the-art DeepFake image generation using Generative Adversarial Networks(GANs) and Stable Diffusion models, alongside simulating attacks to evaluate system robustness. Engineered advanced detection frameworks to safeguard Fibe’s VKYC (Video KYC) pipeline against synthetic identity threats, leveraging Vision Transformers and Swin Transformers for high-accuracy deepfake detection
Backend Developer
Built and optimized a real-time gaming platform supporting 10,000+ concurrent users on a t3.micro instance using Node.js, Redis, and Socket.IO. Conducted extensive load testing with Artillery to validate performance under high concurrency. Achieved 6x faster response times using BullMQ queues and reduced database load by 40% through Redis caching. Implemented WebSocket namespaces for efficient real-time updates across user groups. Deployed on AWS EC2 with S3 integration for scalable and reliable infrastructure