Dr Srijoni Majumdar

Profile

My research focuses broadly on automated decision‑assistance and recommendation. I have developed niche assistance software for maintenance decisions for legacy
code modernisation.
My current research is centred on privacy-aware and sustainable decision-making for shared resources, which are critical in the evolving landscape of the Internet of Things and Artificial Intelligence. In my current postdoctoral position on a UKRI Future-Leader- Fellowship project, I have developed decision support tools for managing urban commons and have made key contributions to award-winning decentralised optimisation systems and received fellowships to prototype Artificial Intelligence solutions for supply chains in the United Kingdom.

My PhD focused on building tools to boost programmer efficiency with C, in complex legacy code. I developed an automated assistance system that reduced code comprehension time by 18.2% in industrial codebases from Interra Systems and Mentor Graphics. Additionally, I worked part-time with a team of three researchers to build a sensor-based image navigator for ISRO’s Mars Mission, improving crater region analysis in high-resolution geo-tagged images.

RESEARCH FUNDING

My independent research journey began through receiving an individual grant [Oct 2024-March 2025, £12,816] from Research England Northern Triangle Talent – Northern Gritstone to support “Redefining Load Balancing of Common Urbans. It piloted novel AI-based recommendation systems to enhance efficiency in the distribution of urban resources. Building on this momentum, the project was selected for a further award under the Google-powered AI Super Connector Cohort II, receiving an additional £20,000 individual funding for the period from November 2024 to June 2025. Currently, I also serve as a Co-Investigator on the EPSRC Impact Acceleration Account project “Collective Learning Optimisation Algorithm” (February 2025 to January 2026, £118,730.83), focusing on advanced combinatorial optimisation models. I am also part of core team to acquire a UKRI-supported grant - Rapid Response Fund project titled “Embedding EDI in the Distribution of Research Funding” (£67,926.39, July 2025 to December 2026) as part of the UK AI for Collective Intelligence National Hub.

Qualifications

• Btech in Computer Science and Engineering
• Mtech in Information and Communication Engineering
• PhD in Machine Leanring for Decision Support Systems