Find Academic Supervisors

• Fuzzy Logic Systems
• Artificial Intelligence
• Model-Based Predictive Control
• +6 more

Professor Mahdi Mahfouf holds the Chair in Intelligent Systems at the University of Sheffield's School of Electrical and Electronic Engineering . He obtained his MPhil (1988) and PhD (1991) in Control Systems from the same institution. After postdoctoral research (1992-1996) on Leverhulme-funded projects in Model-Predictive Control and Fuzzy Logic, he progressed through academic ranks at Sheffield to Full Professor (2005). Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award (for ICU Decision Support Systems) Over 370 publications, including 130+ journal papers Head of the Intelligent Systems Research Laboratory Research Themes His work spans fundamental research in Fuzzy Logic (modelling, control), Neural-Fuzzy Systems, Self-Organising Control, and Evolutionary Optimization, alongside applied domains in pharmaceutical manufacturing, aerospace systems, biomedical engineering (ICU monitoring), and intelligent transportation. Recent publications focus on hybrid AI for pharmaceutical processes , type-2 fuzzy control systems , and machine learning in manufacturing metrology . Lab initiatives include multistage process monitoring and human-machine interaction systems for stress management.

Robin PurshouseView profile

Professor

• Computational Modelling of Complex Social Systems
• Agent-Based Modelling
• Machine Learning
• +6 more

Professor Robin Purshouse is a leading academic at the University of Sheffield , currently serving as Professor of Decision Sciences in the Department of Automatic Control and Systems Engineering within the School of Electrical and Electronic Engineering . With a career spanning academia and industry, his work bridges computational modelling , optimization , and systems science to address complex challenges in public health and engineering. His research has been pivotal in developing mechanisms for agent-based modelling and evolutionary multi-objective optimization . Education: PhD in Control Systems (2004), MEng in Control Systems Engineering (1999) from the University of Sheffield Professor Purshouse's research focuses on computational modelling of complex social systems , decision analytics for population health policy , and Bayesian optimization . He has pioneered the integration of machine learning and uncertainty quantification in social science simulations, with notable projects like the Sheffield Alcohol Policy Model and CASCADE initiative. His work spans interdisciplinary domains, including health economics , policy evaluation , and engineering design . Recent publications highlight his expertise in agent-based modelling for smoking/vaping dynamics , intersectional disparities in alcohol consumption , and inclusive economy frameworks . He has secured substantial funding (exceeding £16 million) through grants from NIH , CRUK , UKPRP , and MRC , including his role as co-PI in the HealthMod cluster. His contributions to multi-objective optimization and evolutionary algorithms have advanced methodologies in both engineering and public health domains. Scientific Awards: ESRC Future Research Leaders Award (2012-2015) As a co-developer of the Liger optimization environment , Purshouse has fostered open-source tools for complex decision-making. He leads the SIPHER consortium for systems science in public health and serves on editorial boards for journals like Environmental Modelling & Software . His teaching includes Agent-Based Modelling (ACS6132), and he maintains professional memberships in the Association for Computing Machinery and Research Society on Alcohol .

Richard CollinsView profile

Senior Lecturer

• Water Distribution Systems
• Hydraulic Transients
• Pipe Fatigue Analysis
• +5 more

Dr Richard Collins is a Senior Lecturer in Water Engineering at the University of Sheffield , affiliated with the School of Mechanical, Aerospace and Civil Engineering. His research focuses on hydraulic transients , pipeline integrity , and smart water infrastructure . Graduated with an Aerospace Engineering degree (2005) and PhD in Materials and Mechanical Engineering (2009) Current research explores pressure transients , leak detection , and autonomous robotic systems for pipeline inspection Projects include fatigue analysis , biofilm mobilisation , and ultrasound-based pipe assessment His publications emphasize cast iron pipe fatigue , acoustic leak detection , and transient-induced contamination . Funded by RCUK and Datatecnics , his work bridges mechanical engineering and civil infrastructure challenges.

James ShucksmithView profile

Senior Lecturer

• Urban Flooding Hydrodynamics
• Water Quality Modeling
• Sustainable Drainage Systems (SuDS)
• +3 more

Dr James Shucksmith is a Senior Lecturer in Water Engineering at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. After completing his undergraduate degree and PhD at the same department, he joined the academic staff in 2010 following a KTP associate role with Yorkshire Water. His research focuses on urban flooding hydrodynamics, water quality modeling, and sustainable drainage systems. Co-director of EPSRC Centre for Doctoral Training in Water Infrastructure and Resilience Current projects: Real Time Abstraction Management (with Severn Trent Water), Centaur FloodInteract Research interests include: Urban flood hydrodynamics and drainage-surface flow interactions Water quality forecasting tools for surface water abstraction Development of local real-time control systems for urban drainage Experimental validation of flood models using PIV measurements His publications (2010-2025) cover topics like contaminant transport in flooded sewer systems, longitudinal dispersion modeling, and real-time control optimization. Recent work focuses on data-driven approaches for Cryptosporidium prediction and E. coli forecasting.

Paola FalugiView profile

Senior Lecturer

• Predictive Control Systems
• Data-Driven Modelling
• System Modelling and Optimization
• +4 more

Dr. Paola Falugi is a Senior Lecturer in Electro-Mechanical Engineering at the University of East London and holds an honorary visiting researcher position at Imperial College London. Her expertise spans predictive control systems, data-driven modeling, and energy network optimization under uncertainty. Senior Lecturer, Department of Engineering & Construction, School of Architecture, Computing and Engineering, University of East London Honorary Visiting Researcher, Imperial College London Research focuses on: Predictive control strategies for uncertain systems Data-driven modeling for control applications Optimization methods in energy network expansion Energy management under stochastic conditions Control systems for robotics and mechatronics Recent publications highlight her contributions to: Robust co-design frameworks for building energy systems Machine learning integration in transmission expansion planning Automated scenario generation for optimal control Control strategies for residential buildings with energy storage Her work bridges theoretical advancements in control theory with practical applications in energy systems and building automation.

Oleg PikhurkoView profile

Professor

• Extremal combinatorics
• Graph theory
• Descriptive combinatorics
• +6 more

Oleg Pikhurko is a Professor of Mathematics at the University of Warwick, affiliated with both the Mathematics Institute and DIMAP (the Centre for Discrete Mathematics and its Applications). His office is located in room B2.12 at the University of Warwick in Coventry, UK. Pikhurko has established himself as a prominent researcher in combinatorics with significant contributions to extremal combinatorics, graph theory, and related fields. His research interests span a wide range of topics in discrete mathematics including extremal combinatorics and graph theory, descriptive combinatorics, graph limits, random structures, and algebraic, analytic and probabilistic methods in discrete mathematics. Pikhurko's work bridges theoretical foundations with practical applications, often employing sophisticated mathematical techniques to solve challenging problems in combinatorial structures. The analysis of Pikhurko's recent publications reveals a consistent focus on extremal combinatorics, particularly Turan-type problems, hypergraph theory, and graph limits. His work demonstrates increasing sophistication in handling complex combinatorial structures, with recent papers exploring connections to measure theory, geometry, and coding theory. Notably, his research shows a progression from classical combinatorial problems toward more abstract and interdisciplinary approaches, including measurable versions of combinatorial theorems and applications to high-dimensional spaces. ERC Advanced Grant 'Finite and Descriptive Combinatorics' (2022-2026) Pikhurko has successfully supervised numerous PhD students including Teresa Sousa (2006), David Offner (2009), Zelealem Yilma (2011), Matthew Fitch (2019), and Matteo Mazzamurro (2023). He currently co-advises Irene Gil Fernández and Zhuo Wu, both expected to complete their PhDs in 2025. His research group focuses on 'Finite and Descriptive Combinatorics,' reflecting his dual interest in finite combinatorial structures and their descriptive (measurable) counterparts. The ERC Advanced Grant awarded in 2022 has provided significant funding to support this research program through 2026. Beyond traditional research, Pikhurko founded the Hedgehog Fund, which encourages innovative proofs of mathematical results presented in his lectures. He also maintains an Erdos Lap Number of 2, having sat on the lap of Barbie Freidin (Erdos Lap Number 1) who herself sat on Paul Erdos's lap.

• Sustainable Aerospace Engineering
• Conceptual Aircraft Design
• Propulsion Systems
• +3 more

Dr Albert Stevan van Heerden is a Lecturer in Aerospace Engineering at the James Watt School of Engineering, University of Glasgow. Previously, he was a Research Fellow at Cranfield University's Rolls-Royce University Technology Centre and Centres for Aeronautics and Propulsion and Thermal Power Engineering. He holds a PhD in Aerospace Engineering from Cranfield University, an MS in Aeronautics from California Institute of Technology (Fulbright scholar), and a BEng in Mechanical Engineering from the University of Pretoria. His research focuses on conceptual aircraft design , airframe and propulsion systems development , and technical/economic assessment of sustainable aerospace technologies . He employs deterministic and non-deterministic design methods, with a unique emphasis on evolvable aircraft family design for long-term relevance. His work spans traditional civil transport aircraft, electric aircraft , and hydrogen-powered aircraft systems. Key publications include advancements in set-based design techniques margin allocation strategies hydrogen propulsion systems thermal management frameworks uncertainty allocation methods . Scientific recognition includes Fellow of the Higher Education Academy (FHEA) Member of the Royal Aeronautical Society (MRAeS) . He also serves as Academic Adviser for the Commonwealth Scholarship Commission and Academic Ambassador for the James Watt School of Engineering. His teaching portfolio includes Thermodynamics 2, Aircraft Design 3, and Fluid Mechanics (University of Glasgow Singapore), reflecting his expertise in core aerospace disciplines.

Zixu LiuView profile

Lecturer

• Machine Learning
• Information System
• Decision Making
• +3 more

Dr. Zixu Liu is a Lecturer in Decision Analytics and Risk at Southampton Business School, University of Southampton. He focuses on applying machine learning and optimization techniques to business analytics problems, particularly in decision-making, smart grids, and industrial systems. PhD in Computer Science, University of Manchester (2013-2017) MSc in Computation and Game Theory, University of Liverpool (2012-2013) BSc in Computer Science and Technology, Jilin University (2007-2011) His research integrates advanced algorithms with cloud/web-based information systems to solve real-world challenges in multicriteria decision-making, electricity market pricing, and computer vision applications. Current projects emphasize industry transferability through API-driven solutions. Recent publications highlight diverse applications including: Smart grid optimization and demand response Hesitant fuzzy linguistic decision models Industry 4.0 collaboration platforms Deep learning benchmarks for object counting Wireless mesh network architecture He actively supervises PhD students and teaches undergraduate courses on spreadsheets, databases, algorithmic thinking, and data visualization.

Tossapon BoongoenView profile

Professor

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +6 more

Tossapon Boongoen is a Professor in the Department of Computer Science at Aberystwyth University, with over a decade of experience in artificial intelligence and machine learning. Previously, he served as Associate Professor at Mae Fah Luang University (2017-2022) and Royal Thai Air Force Academy (2011-2017), where he also directed the MFU Research and Innovation Institute. His research spans ensemble clustering for privacy-preserving data fusion deep learning in remote sensing and sky survey data network security applications for ransomware and intrusion detection forest fire risk modeling using spatial-temporal data Recent publications focus on convolutional neural networks, adversarial attack classification, and collaborative filtering algorithms. He leads international projects funded by the British Council, FCDO, and Academy of Medical Sciences, including collaborations with institutions in Thailand, Korea, Vietnam, France, and Czech Republic. Professional engagements include editorial roles in journals like Knowledge-Based Systems Frontiers in Neurorobotics PeerJ Computer Science ICT Express and partnerships with GISTDA, GOTO Observatory, and Imperial College London.

Ali KhurramView profile

Professor

• Artificial Intelligence in Pathology
• Head and Neck Cancer
• Tumour Microenvironment
• +3 more

Professor Ali Khurram serves as the Dean of the School of Clinical Dentistry and Professor of Pathology at the University of Sheffield, with a concurrent role as Honorary Consultant Pathologist. He holds a BDS, MSc, PhD, and fellowships from the Royal College of Pathologists (FRC Path) and Higher Education Academy (FHEA). Previously, he was Senior Clinical Lecturer (2016–2022) and NIHR Academic Clinical Lecturer (2011–2016) at the same institution. His research focuses on: AI-driven pathology diagnostics for head and neck cancers Tumour microenvironment dynamics in cancer metastasis Salivary gland tumor pathobiology Digital biomarker discovery for prognosis prediction Supported by Cancer Research UK, NIHR, and international collaborators, his NEOPATH Research Group pioneers translational oncology solutions. Recent publications demonstrate concentrated work in AI-based classification systems for oral lesions and validation of digital pathology tools. His scholarly output emphasizes clinical applicability in early cancer detection and personalized treatment planning. Awards/Honors: PathSoc Golden Microscope Award (2022) Fellowship of the Royal College of Pathologists Fellowship of the Higher Education Academy Academic Leadership: Trains 9 PhD students, serves as Training Programme Director for Oral Pathology (Yorkshire region), and leads Module ORP611 (Advanced Oral Histopathology). Clinically, he oversees diagnostic services for head and neck cancers and chairs regional multidisciplinary tumor boards. Affiliations: Trustee for The Swallows Head and Neck Cancer Charity, Deputy Chair of NCRI Salivary Gland Cancer Working Group, and member of Head and Neck Cancer International Group.

Cameron BrownView profile

Associate Professor

• Pharmaceutical Manufacturing
• Crystallization Processes
• Digital Design Tools
• +4 more

Dr. Cameron Brown is a Reader (equivalent to Associate Professor) at the Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow. He specializes in developing digital design tools and strategies for pharmaceutical manufacturing. Brown joined Strathclyde in 2014 and has progressed through research associate, research fellow, and Chancellor's fellow positions. He currently coordinates the Drug Substance Manufacturing module for the Advanced Pharmaceuticals Manufacturing MSc program. Education: Brown holds a PhD in crystallization process characterization and a Chemical Engineering degree, both from Heriot-Watt University. Research Focus: His work centers on three primary areas: Hybrid modeling approaches : Integrating physics-based and data-driven models to enhance drug substance manufacturing efficiency Self-driving labs : Developing automated systems for drug substance process development with model-based experimental design Digital decision-making : Implementing coupled models through GenAI and LLMs for rapid pharmaceutical process development His research contributes to UN Sustainable Development Goals through improved medicine manufacturing sustainability. Publication Trends: Brown's recent articles focus on pharmaceutical crystallization, digital design methodologies, AI applications in manufacturing, and process optimization. His work demonstrates strong emphasis on translating computational models into industrial practice, particularly in continuous manufacturing and quality-by-design frameworks. Honors: Elected staff officer of British Association of Crystal Growth (2024) Research Leadership: Brown serves as Principal Investigator for PharmaCrystNet and co-investigator on multiple major initiatives including Digital Design and Manufacturing of Amorphous Pharmaceuticals, Future CMAC Manufacturing Hub, Accelerated Discovery and Development of New Medicines Prosperity Partnership, and ARTICULAR. He leads knowledge exchange projects with pharmaceutical companies and manages knowledge transfer partnerships. Professional Engagement: Brown is active in the Acceleration Consortium and serves on the committee of the British Association of Crystal Growth.

• Nuclear Physics
• Radiation Detection
• Gamma-ray Spectrometry
• +2 more

Dr Ellis Rintoul is an active academic researcher and educator specializing in nuclear physics and radiation detection technologies. Affiliated with a UK-based university (likely through the Science and Technology Facilities Council grant), he contributes to both research and teaching in advanced detector systems and nuclear science. Research Focus: Nuclear instrumentation, gamma-ray tracking, and medical imaging applications Teaching Roles: Coordinates and teaches modules in nuclear science (PHYS135), gamma spectrometry (PHYS804), and practical physics (PHYS106) Research Outputs: Published extensively on HPGe detectors, CZT detectors, and Compton imaging systems since 2020 His work centers on optimizing radiation detection systems for nuclear physics experiments and medical applications, particularly through signal analysis and detector design innovations. Recent publications (2021-2023) demonstrate expertise in gamma-ray tracking algorithms, Compton camera performance validation, and charge collection characterization in segmented detectors. Current research projects include the ENVISAGE grant (2023-2026) for evaluating the SIGMA gamma-ray tracking detector in operational environments, indicating sustained leadership in detector technology development.

• Accelerator Physics
• Particle Physics
• Beam Dynamics
• +3 more

Dr Maxim Korostelev is a Research Fellow at the University of Liverpool , affiliated with the Department of Physics under the School of Physical Sciences . His work focuses on Accelerator Physics and Particle Physics , with expertise in beam dynamics, lattice design, and instability modeling. Key research contributions include studies on microwave instability in ILC damping rings, impedance analysis, tomographic beam diagnostics, and optics optimization for the LHC upgrade. His publications highlight collaborations with international projects like ALICE and ILC. 2012: LHC upgrade optics and lattice 2011: ILC damping ring wake fields 2010: Coupled lattice function calculations No scientific awards or student advisement details were explicitly mentioned in the provided texts.

James TaylorView profile

Professor

• Control Engineering
• Data-Driven Modelling
• Automatic Control
• +3 more

Professor James Taylor is a distinguished academic at Lancaster University where he holds a Personal Chair in Control Engineering within the School of Engineering . As Impact Champion for the School of Engineering and lead for Robotics & Control, he has been instrumental in advancing control engineering research. Previously, he served as group lead for Nuclear Science & Engineering (2019-24) and held senior administrative roles including Director of Teaching and Deputy Head of Engineering (2005-2018). Professor Taylor's research spans data-driven modelling and automatic control for challenging, uncertain systems with applications in Energy systems Healthcare Robotics Environmental monitoring His work has attracted over £10m in UK research council funding as co-investigator across 10+ projects. He has made significant contributions through his research on topics such as Electricity theft detection using machine learning Nuclear fuel analysis with hyperspectral imaging Digital twins for nuclear manufacturing Adaptive medical treatment systems Robotic plant phenotyping platforms Scientific recognition includes: Fellow of the Institution of Engineering & Technology (FIET) Member of IET Academic Accreditation Committee Editorial board member for three Elsevier journals Active participation in UK Automatic Control Council Professor Taylor has supervised numerous PhD students to successful completion and co-develops the internationally used CAPTAIN Toolbox (MATLAB) for system identification and control. He has been involved in developing control systems for Hydraulically actuated dual-arm robots Wave energy converters Assisted tele-operation systems Grow-cell agricultural facilities Motion planning algorithms

Safia BarikzaiView profile

Associate Professor

• Educational Technology
• Courseware Engineering
• Technology Startups
• +4 more

Dr. Safia Barikzai serves as an Associate Professor in the School of Computer Science and Digital Technologies at London South Bank University (LSBU), holding responsibilities for employability, student experience, and academic enrichment across South Bank Academies. She previously contributed as the Equality, Diversity, and Inclusion (EDI) Lead for the School of Engineering, collaborating with external organizations to foster inclusive tech environments. Her educational background includes a PhD in Courseware Engineering completed at LSBU in November 2006, with a thesis titled 'Integrating Courseware into Collaborative Learning Environments'. Her academic journey began in 1996 through a Teaching and Learning Technology Programme (TLTP) funded project involving seven UK institutions. PhD in Courseware Engineering, London South Bank University (2006) Undergraduate degree completed prior to 1996 Dr. Barikzai's research spans educational technology foundations in courseware engineering to contemporary investigations of technology entrepreneurship. Her current work employs qualitative methodologies to analyze entrepreneurial pivoting in tech startups, examining triggers, adaptation strategies, and survival mechanisms within the UK high-tech ecosystem. This evolution reflects a strategic shift from learning environment design to venture development dynamics while maintaining a focus on collaborative systems. Analysis of her 2019-2024 publications reveals a dominant focus on technology entrepreneurship (80% of outputs), particularly through qualitative studies of startup pivoting. Her 2024 decolonization panel work extends this critical perspective to institutional history, while her sole 2019 publication demonstrates interdisciplinary application of machine learning in medical diagnostics for cancer and diabetes. Scientific awards: None documented in provided materials. Dr. Barikzai has supervised two postgraduate students and served as Course Director for a Masters programme at the University of Wollongong (2002-2005), managing offshore dissertations in Hong Kong. Her grant involvement includes the Teaching and Learning Technology Programme (TLTP) project and subsequent funding for collaborative learning tools. She maintains active roles in curriculum development, serving on education committees and teaching Analysis and Design alongside Innovation and Enterprise courses. Supervision: 2 postgraduate students Past Leadership: Masters Programme Course Director (University of Wollongong, 2002-2005) Committee Service: School Education Committee member As part of LSBU's Digital x Data Research Centre, Dr. Barikzai contributes to academic enrichment initiatives for South Bank Academies while advancing UN Sustainable Development Goals through educational innovation. Her collaborative networks include external diversity-focused organizations working to transform engineering and technology sectors.