I am a B.Sc in CSE student and a Backend Engineer driven by architectural elegance. My current focus is bridging the gap between robust backend systems and Machine Learning. Having completed Stanford & DeepLearning.AI's ML Specialization, I'm now building the deep learning half of that bridge.
Working through MIT 6.S191, implementing CNNs, RNNs and attention from scratch, and folding trained models into private microservice ecosystems.
Developing secure, high-concurrency backend services. My role involves architecting internal system models and ensuring high-performance data delivery across distributed nodes.
Focusing on service orchestration and low-latency internal communication using modern protocols.
Maintaining system integrity through standard identity protocols and secure model design.
Massachusetts Institute of Technology · 2026
MIT's official introductory deep learning course, covering convolutional networks for vision, sequence models and attention, generative modeling, and the practical limits of deep learning.
DeepLearning.AI & Stanford Online, Andrew Ng · 2026
Three-course specialization covering supervised learning (regression and classification), advanced learning algorithms (neural networks, decision trees), and unsupervised learning, recommenders and reinforcement learning.
Sonargaon University · 2024 - 2028
Undergraduate degree in Computer Science & Engineering, currently in the third year. Coursework spans data structures, algorithms, operating systems, database systems and software engineering.
Full-stack web development program covering the MongoDB, Express, React and Node.js stack, from REST API design and authentication through to deploying complete production applications.
Supervised & Unsupervised
CNNs, RNNs, Attention
gRPC Architectures
FastAPI / Node.js
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