I'm Asaad Cheema, Applied AI Engineer at Mowi, embedded with the Sales and Marketing (S&M) Digital Solutions team. AWS-certified Data Engineer and Solutions Architect, with PhD-level depth in federated learning, computer vision, and LLM-driven workflows. I don't just design solutions; I deliver them, from research notebooks to production in the cloud.
AC
Currently at Mowi · S&M Digital Solutions
Working with the Mowi team to design a secure internal GPT with task-specific agents for retrieval, forecasting, customer context, and decision support to improve sales productivity.
Building autonomous agents that read, classify, and reason over complex commercial contracts. They surface risk, obligations, and renewal triggers so legal and commercial teams act on insight, not paperwork.
Modernizing data flows across production and commercial operations, bringing relevant signals together so domain experts can make informed decisions more efficiently.
Embedding ML and LLM-driven copilots into existing operational workflows to deliver relevant information within the tools teams already use.
A running log of milestones — new roles, talks, papers, and things I'm learning along the way.
Explored how strong product organizations connect strategy informed by customer insights, rapid product discovery, and empowered teams that work across functions. My biggest takeaway was to give teams meaningful customer problems to solve, test ideas early, and measure success through customer and business outcomes rather than feature output.
Embedded with the S&M Digital Solutions team, building agentic AI for contracts, sales, and operations. Leading the Blue Revolution.
Defended my thesis, Topology-Aware Machine Learning in IoT Systems, after four years in Trondheim and a research stay at Imperial College London.
Clustered federated learning work in the IEEE Internet of Things Journal, Physical Communication, and IEEE Communications Letters. Full list on Google Scholar.
I spent four years at NTNU earning a PhD in Topology-Aware Machine Learning for IoT, with a research stint at Imperial College London. I shipped production ML at Wrist-Shot (luxury-product authentication at 90%+ accuracy on AWS), then worked as a consultant at Lighthouse.no, delivering data-driven solutions for asset health and resource optimization. Today I'm an ML Engineer at Mowi, operationalizing AI across the value chain.
I care about systems that are private by design, computationally efficient, and actually deployable. Federated learning, LoRA / PEFT, agentic LLMs, real-time vision. The unifying thread is making intelligent systems work at the edge of constraints.
Completed a PhD at NTNU and a visiting research placement at Imperial College London. Built production ML at Wrist-Shot, completed post-PhD consulting at Lighthouse.no, and now ML engineering at Mowi.
I value the collaborative environment and people at Mowi. Leading the Blue Revolution.
Grateful for a collaborative team that made difficult problems feel manageable.
A rewarding chapter shaped by close collaboration with the team.
I am grateful to mentors whose knowledge, support, and friendship helped me grow as a researcher and as a person.
Imperial's open research culture sharpened how I think about efficient, adaptive machine learning systems.
A selection of research projects and production systems, each shaped by deliberate choices around models, licensing, deployment, and data flow.
End-to-end computer-vision system enforcing PPE compliance (safety vests, hard hats, harnesses) across industrial environments. Built on YOLO-NAS, chosen deliberately for its permissive license (commercially deployable, unlike YOLOv8/v5 GPL variants), combined with Apple's Depth Pro for monocular depth estimation, so the system reasons about proximity to hazard zones in addition to detecting PPE on bodies. Real-time inference with user-adaptive alerting, deployed end-to-end on AWS EC2. Measurably reduced onsite violations.
Multi-agent system that interprets natural-language requests and resolves them across heterogeneous sources: PDF catalogs, multiple internal databases, and product imagery. A router agent decides on the right retrieval strategy per query (structured SQL, semantic PDF search, or visual lookup), then a synthesis agent fuses the evidence into a grounded answer. Built with LangChain for intent & entity extraction, with conversation memory for multi-turn refinement. Replaces manual lookup across systems with one natural interface.
Novel framework for population-based SHM across bridges. Clustered Federated Learning trains without sharing raw data. The framework clusters bridges by principal-angle similarity without requiring domain knowledge and uses adaptive parameter transfer to adapt to new structures efficiently.
Integrated drones with a blockchain safety protocol to enhance vehicular security, deployment efficiency, and communication reliability. Optimized for spectral efficiency in dense urban scenarios. Published in IEEE Trans. Intelligent Transportation Systems.
Work shaped by partnerships across academic and industrial research labs.
NBL
TUW
NUST
NTNU
ICL
Eleven peer-reviewed papers across federated learning, structural health monitoring, vehicular networks, and wireless communications. Full list on Google Scholar.
From IEEE conference presentations to mentorship sessions for engineering students. I enjoy translating dense research into clear, useful ideas.
A career and technology outlook session for engineering students navigating the rapidly evolving AI landscape.
On topology-aware learning, federated meta-learning, and how intelligence can self-organize at the network edge.
With Salman Ijaz Siddiqui & Pierluigi Salvo Rossi
Hands-on across the modern ML stack, from raw research code to AWS-deployed systems.
Doctoral training across Norway and the UK, master's in Pakistan, plus AWS certifications.
Topology-Aware Machine Learning in IoT Systems
PhD research exchange in collaboration with NTNU
Machine Learning–Based Blockchain Networks for Combating Security Threats in IoTs
Low Power Dynamic Random Access Memory (DRAM)
"Not the best photographer, but I love capturing the world around me."
Mountains, fjords, slow mornings with chai, and traveling whenever the calendar allows. A collection of moments from a phone camera and a curious eye.
Open to collaborations and research conversations. The fastest way to reach me is by email.