🎓 Graduate Student at Texas A&M University (Master's in Computer Science, CGPA: 4.0)
👨💻 Software Engineer | Open Source Contributor | Machine Learning Enthusiast
🐛 Debugging Life, One Byte at a Time
I'm a tech enthusiast with expertise in software engineering, machine learning, and distributed systems. I enjoy taking on challenging projects, contributing to open-source communities, and creating scalable solutions. My journey has been a blend of research, innovation, and practical implementation.
🔹 Current Focus:
- Contributing to PyDough, an open-source DSL for analytical problem-solving.
- Building scalable MLOps pipelines for IoT time series data.
🔹 Experience Highlights:
- Reduced deployment time by 90% for ML pipelines using FastAPI, Celery, and Redis.
- Saved $55K annually by migrating ML inference platforms to in-house infrastructure.
- Built an LLM-powered Chrome extension for intelligent form filling.
- ⚙️ PyDough: An open-source DSL streamlining SQL generation for complex analytical tasks.
Languages: Python, Java, C/C++, SQL, JavaScript, Ruby, Bash
Frameworks & Libraries: Spring Boot, ReactJS, Flask, FastAPI, TensorFlow, PyTorch
Tools: Docker, Kubernetes, Redis, Kafka, Spark, GCP
Specialties: Distributed Systems, Machine Learning, MLOps, Cloud Infrastructure
- 4.0/4.0 CGPA in Master’s at Texas A&M University.
- Led a team to migrate legacy systems (Ruby on Rails → Spring Boot) with Kubernetes deployment.
- Contributed to scalable open-source projects and published research-backed tools.
- Built a mini OS Kernel from scratch, mastering low-level thread, memory, and file management.
- Aplora: A Chrome extension using LLMs for intelligent form filling.
- Tiny Social Networking Service: Distributed system with leader-election and fault tolerance.
- x86 Mini-Kernel: Built a kernel with memory/thread management and hard disk drivers.
📫 You can reach out to me at [email protected].
