CircuitLab AI is a research initiative supported by the Department of Computer Science and Engineering at the National Institute of Technology Meghalaya, with institutional support from the Centre for Innovation, Incubation and Entrepreneurship (CIIE) and the Office of the Director.
About CircuitLab AI
A research initiative at NIT Meghalaya focused on practical, efficient, and scalable artificial intelligence systems.
We develop AI technologies that are robust in real-world settings and deployable across cloud, edge, and embedded environments. Our work combines fundamental research with practical systems engineering to move ideas from experimentation to usable tools.
People Behind CircuitLab AI
Pushpak Das
Founder, CircuitLab AI
Pushpak Das grew up in a rural region along the Indo-Nepal border in the Indo-Gangetic Plain, where limited access to advanced technological infrastructure shaped his early curiosity about computing systems. This curiosity gradually developed into an interest in how intelligent and energy-efficient computing technologies can address real-world challenges. His academic interests include communication networks, distributed systems, and efficient computing architectures. At CircuitLab AI, he works on developing scalable and sustainable computing systems and contributes to the research direction of intelligent computing technologies.
Md Rasel Mandol
Founder, CircuitLab AI
Md Rasel Mandol was born and grew up in Jolilpur, a small village near the West Bengal border, where access to computers, technology, and the internet was almost nonexistent during his early years. He completed his primary education up to class five in a local village school. His curiosity about technology began when he first used a computer at a friend's home, the first time he ever touched a mouse and explored the internet, which made him deeply curious about how technology works and shapes the modern world.
He completed his secondary education in 2019 and his higher secondary education in 2021-22. Later, he received the Study in India (SII) Scholarship from the Government of India, which gave him the opportunity to pursue a B.Tech in Computer Science and Engineering at the National Institute of Technology Meghalaya.
He mainly finds machine learning and data very interesting and tries to find meaningful outputs from data using machine learning and deep learning.
Dr. Diptendu Sinha Roy
Dean - Research & Consultancy, NIT Meghalaya
Supports the broader research ecosystem at NIT Meghalaya and encourages student-driven research initiatives such as CircuitLab AI.
Prof. Deepak Kumar
Head of Department, Computer Science & Engineering, NIT Meghalaya
Provides academic guidance and departmental support for research initiatives and student-led technological projects.
Dr. Bibhas Manna
Assistant Professor, Department of ECE, CIIE In-Charge, NIT Meghalaya
Supports innovation and student research initiatives through the Centre for Innovation, Incubation and Entrepreneurship (CIIE) at NIT Meghalaya.
Director, NIT Meghalaya
Director, National Institute of Technology Meghalaya
Provided institutional and financial support for the development of CircuitLab AI and encouraged student-driven research and innovation initiatives within the institute.
Core Research Focus
Computer Vision and Segmentation
Designing reliable vision models for segmentation, detection, and scene understanding across diverse domains.
Medical Imaging AI
Building clinically relevant pipelines for MRI analysis, anatomical segmentation, and decision support research.
Energy-Efficient AI Systems
Optimizing models and inference pipelines to reduce computational overhead while maintaining strong performance.
Applied Intelligent Infrastructure
Developing AI-enabled monitoring and analytics systems for infrastructure, urban intelligence, and adaptive services.
How We Work
Research to Deployment
We follow a full-cycle workflow: problem definition, dataset curation, model development, evaluation, and deployment-ready system design.
Collaboration and Open Research
We encourage collaboration with students, researchers, and institutions through shared tools, reproducible methods, and applied research projects.
Long-Term Direction
Our long-term direction aligns with Cognitive City: A Vision of Ubiquitous Connectivity, where AI systems, sensors, and connected infrastructure work together to create adaptive and responsive environments.