Rate My Professor Nelly Bencomo

Dr. Nelly Bencomo is an Associate Professor in the Department of Computer Science at Durham University. She obtained her PhD from Lancaster University in the UK. Her career includes previous roles as Senior Lecturer (equivalent to Associate Professor) in the Computer Science Department at Aston University, Marie Curie Fellow at INRIA Paris-Roquencourt on the Requirements-aware Systems project from 2011 to 2013, and Senior Research Associate at Lancaster University. Bencomo leads the Software Engineering research team SE@Durham within the Artificial Intelligence and Human Society research cluster and serves as Principal Investigator on EPSRC-funded projects such as Twenty20Insight, weDecide for shared decision-making in menopause treatment, and JusTN0W on just transitions to net zero.

Her research specializations encompass AI and machine learning, decision-making under uncertainty, just transitions, software engineering for autonomous and self-adaptive systems, software engineering for AI/ML systems, autonomous systems, and runtime models. Bencomo has earned significant recognition, including Best Paper Awards at the International Conference on Engineering Digital Twins 2024, SEAMS 2024, and REFSQ 2013; two 10-year Most Influential Paper Awards in 2019 for 'RELAX: Incorporating Uncertainty into the Specification of Self-Adaptive Systems' and 'A Goal-Based Modeling Approach to Develop Requirements of an Adaptive System with Environmental Uncertainty'; a Leverhulme Fellowship for 'QuantUn: quantification of uncertainty using Bayesian surprises' in 2019-2020; and a Marie Curie Intra-European Fellowship. She was listed among Women for Innovation in Health Science in the North of England in 2024. Key publications include the edited volume 'Models@run.time: Foundations, Applications, and Roadmaps' (2014); 'Declarative Lifecycle Management in Digital Twins' (EDTconf 2024); 'Code Gradients: Towards Automated Traceability of LLM-Generated Code' (RE 2024); 'Uncertainty Flow Diagrams: Towards a Systematic Representation of Uncertainty Propagation' (SEAMS 2024); and 'Latency-aware RDMSim' (SEAMS 2024). Her contributions have advanced uncertainty handling and self-adaptation in software engineering.