Bridging Computer Vision & LLMs in Production Systems
I've trained CNNs to see and transformers to reason. Now I build systems where both work together - from diffusion pipelines shipping photorealistic product imagery at Avataar AI, to agentic AI pipelines at Armada AI. IISc Bangalore alumnus, GATE AIR 221.
From Signals to Neural Networks
My path to AI started in electrical engineering - clearing GATE (AIR 221) and BARC, then choosing research over a government job. That decision led me to IISc, where I published on continual learning (WACV 2025) and discovered my calling: building systems where vision and language work together.
Today, I ship AI that matters - diffusion pipelines at Avataar AI, agentic systems at Armada AI. The boundary between what machines see and what they understand is blurring. I build at that edge.
AI Engineer
- Architecting end-to-end agentic systems using LangGraph for multi-step reasoning
- Building RAG pipelines with Qdrant vector database for semantic retrieval
- Developing production APIs with FastAPI and Chainlit interfaces
- Containerizing ML workflows with Docker and PostgreSQL backends
Research Engineer
- Built end-to-end lifestyle image generation pipeline using Flux Model and ControlNets
- Modified diffusion sampling for improved object reconstruction with intrinsic decomposition
- Developed classification systems using CLIP, BLIP2, and Qwen2.5 for low-data scenarios
- Enhanced segmentation accuracy with BiRefNet and SAM + YOLO-world integration
Teaching Assistant
- Integrated continual learning frameworks (L2P, DualPrompt) to mitigate catastrophic forgetting
- Built self-supervised models using MoCo and SimCLR for visual representation learning
- Developed adaptive prompt-based learning with dynamic token expansion
Teaching Assistant
- Developed DFT-based frequency domain filtering for image denoising and enhancement
- Implemented SIFT and Normalized Cut for feature detection and segmentation
- Optimized deep learning models using EfficientNet-B0 with custom classifiers
M.Tech in Artificial Intelligence
Indian Institute of Science (IISc), Bangalore
2022 - 2024 · CGPA: 8.0/10.0
B.Tech in Electrical Engineering
Bhagalpur College of Engineering, Bhagalpur
2018 - 2021 · CGPA: 8.75/10.0
Diploma in Electrical Engineering
Government Polytechnic Muzzafarpur, Muzaffarpur
2015 - 2018 · 77.73%
Secondary School (10th)
Bihar School Examination Board · Utkramit M S Parmanandpur
2015 · 60%
ML Foundations
- Linear Algebra
- Stochastic Models and Applications
- Pattern Recognition and Neural Networks
- Computational Methods of Optimization
- Game Theory
Computer Vision
- Digital Image Processing
- Advanced Image Processing
- Computer Vision
- Digital Video Perception and Algorithms
Language & LLMs
- Introduction to NLP
- Deep Learning for NLP
- LLMs for Practical NLP
AI/ML
Frameworks
Infrastructure
Languages
Let's Build Something Together
Looking for collaboration on AI/ML projects, research opportunities, or just want to chat about generative models and agentic systems.
sahil15rohit88@gmail.com