جست‌وجوی استاد و پژوهشگر

Daniel Karapetyanمشاهده پروفایل

استادیار

• Combinatorial Optimization
• Artificial Intelligence
• Data Science
• +۱۷ مورد دیگر

Daniel Karapetyan is an Assistant Professor at the School of Computer Science , University of Nottingham, and a member of the Computational Optimisation and Learning Lab . His research spans Artificial Intelligence , Data Science , Operational Research , and Optimization , with applications in transportation , logistics , satellite mission planning , and access control . Education: PhD in Computer Science, Royal Holloway, University of London (2007–2010) BSc/MSc in Computer Science, Bauman Moscow State Technical University (2001–2007) His research interests focus on the automated design of heuristic algorithms , multi-objective optimization , and parameter tuning for machine learning and combinatorial problems. He integrates Large Language Models (LLMs) and hyperparameter optimization into practical systems, addressing real-world challenges in airport sequencing , TV ad scheduling , and electric vehicle range prediction . Notable scientific contributions include the CORS Practice Prize (2014) for ferry scheduling work and pioneering fixed-parameter algorithms in security-related optimization problems. His publications emphasize combinatorial optimization , Markov Chain methods , and automated algorithm configuration . Teaching roles include module convener for COMP3008: Knowledge Representation and Reasoning , personal tutoring for COMP1002 , and supervision of COMP2002: Software Engineering Group Project . He also offers PhD supervision in areas like AI for optimization , interpretability in ML , and emergency department coordination .

• DC Microgrid
• Mixed-Integer Linear Programming
• Distributed Energy Resources
• +۲ مورد دیگر

Abdulrahman Buji Bolori Babagana is a researcher in Electronic And Electrical Engineering, specializing in DC microgrids and optimization techniques. His work focuses on enhancing grid resilience and efficiency through mixed-integer linear programming and distributed energy resource management. Research interests include: DC Microgrid design and stability Load shedding optimization algorithms Mixed-integer linear programming applications Smart grid technologies Recent publications highlight advancements in resilient DC microgrid configurations and non-communication-based control strategies. His expertise aligns with UN Sustainable Development Goals related to affordable and clean energy.

• Optimization
• Machine Learning
• Unsupervised Learning
• +۵ مورد دیگر

Julia Handl is a Professor in Decision Sciences at Alliance Manchester Business School, University of Manchester, and a member of the European Laboratory for Learning and Intelligent Systems (ELLIS). Her interdisciplinary career spans computer science, optimization, and biomedical applications. PhD in Interdisciplinary Biocentre (2006) MSc in Computer Science (2003) BSc in Computer Science (2001) Research focuses on unsupervised learning , multi-criteria optimization , and evolutionary computation , with applications in industrial knowledge exchange and UN Sustainable Development Goals. Recent work bridges graph reinforcement learning and deep learning for complex problem-solving. 2024 research outputs highlight trends in neural optimization frameworks , randomness techniques , and predictive modeling for healthcare. Contributions span algorithm design , instance space analysis , and medical AI . Scientific Awards MRC Special Training Fellowship DAAD Scholarship Gottlieb-Daimler & Karl-Benz Foundation Support Secured over £1m in research funding and held leadership roles including Associate Head of Division (2018-2021) and e-Research Lead for the Faculty of Humanities (2021-present). Collaborates across Manchester's three faculties and industry partners.

David Ellisمشاهده پروفایل

دانشیار

• Combinatorics
• Discrete Analysis
• Fourier Analysis
• +۴ مورد دیگر

Dr. David Ellis is an Associate Professor in Pure Mathematics at the School of Mathematics, University of Bristol. His research bridges extremal combinatorics with algebra, analysis, probability theory, and theoretical computer science. Previously, he held positions at Queen Mary, University of London, and St John's College, Cambridge. Education: B.A., M.Math (University of Cambridge), PhD (University of Cambridge, supervised by Imre Leader). Research Interests: Dr. Ellis specializes in extremal combinatorics, with a focus on interactions between combinatorics, algebra, analysis, and theoretical computer science. His work explores forbidden intersection problems, Turán-type theorems, and applications to probability and graph theory. Publication Trends: His recent articles (2023-2025) address Turán densities for hypercubes and daisies, junta approximations in symmetric groups, forbidden intersections in linear maps, and structure of union-closed families. These papers emphasize probabilistic and algebraic methods in combinatorics. Scientific Awards: Feinberg Visiting Fellowship, Weizmann Institute of Science (2013-14). Grants & Collaborations: Principal Investigator for EPSRC project EP/W000032/1 on pooled testing algorithms for pandemic management. Collaborated with DELVE Initiative (2020) on healthcare infection modeling during the coronavirus pandemic.

Gábor Csányiمشاهده پروفایل

استاد

• Atomistic simulation
• Multi-scale modeling
• Machine learning
• +۵ مورد دیگر

Gábor Csányi is a Professor of Molecular Modelling at the University of Cambridge, affiliated with the Applied Mechanics research group under the Mechanics, Materials and Design Academic Division. His research focuses on atomistic simulations and the development of machine learning techniques for materials science, particularly in coupling quantum mechanics with larger length scales. Key research interests include: Multi-scale modeling of materials Machine learning force fields Ab initio electronic structure data integration Statistical methods in molecular dynamics Enhanced sampling algorithms for configuration space exploration He is actively involved in the Lennard-Jones Centre seminar series, discussing machine learning applications in physics and chemistry. His work has been featured in talks at IPAM, Ellis workshops, and ML4Science seminars since 2015.

• High-speed aerodynamics
• Non-linear heat transfer
• Turbomachinery
• +۵ مورد دیگر

Dr. Bidur Khanal is the current Head of Department for Aerospace and Aircraft Engineering at Kingston University. He joined Kingston in August 2024, bringing extensive experience from MBDA Missile Systems (Team Lead in Simulation and Modelling), Coventry University (Senior Lecturer), and Cranfield University (Lecturer in Complex Weapons). Faculty of Engineering, Computing and the Environment, Kingston University Department of Aerospace and Aircraft Engineering His academic journey includes a PhD in Computational Aerodynamics and Aeroacoustics from Cranfield University (2010), MPhil in Computational Aeroacoustics from the University of Southampton, and a BEng (First Class Honours) in Aeromechanical Systems Engineering from Cranfield University. He also holds a PGCert in Academic Practice. Dr. Khanal's research focuses on high-speed aerodynamics, non-linear heat transfer, and turbomachinery using high-fidelity computational methods. His work spans turbulence modeling, aeroacoustics, and flow control, often addressing complex aerospace engineering challenges related to missiles, turbine blades, and aircraft aerodynamics. His publications highlight expertise in computational fluid dynamics (CFD), unsteady flow analysis, and thermal management. Key contributions include studies on cavity flow control, thrust reverser configurations, and droplet evaporation in multicomponent fuels. Recipient of several national and international awards/scholarships during his time as a student in the UK Chartered Engineer (CEng) Fellow of Royal Aeronautical Society, UK Fellow of the Higher Education Academy, UK Dr. Khanal has delivered lectures as an invited speaker at various forums in the UK and internationally. His teaching encompasses core aerospace topics such as Aerospace Technology Flight Dynamics and Control Aerospace Propulsion Machine Learning and AI for Aerospace Applications . He is passionate about integrating industry insights into academia, having collaborated with entities like Advantage-CFD (Formula One) and Airbus during his academic career. His professional experience includes a postdoctoral role at the Rolls-Royce University Technology Centre at Oxford and a position as Aerodynamic Methods and Tools Engineer at GE Power. Dr. Khanal emphasizes the importance of aligning Kingston University's Aerospace Engineering courses with industry needs, ensuring graduates are equipped with cutting-edge computational techniques and practical knowledge.

• Software Engineering
• Programming Languages
• Software and Application Security
• +۹ مورد دیگر

Dr David Clark is a Reader in Program Analysis at University College London (UCL), Department of Computer Science. Previously, he worked at Kings College London and Imperial College London. He earned his PhD in 1996 from Imperial College London, following an MSc (1992) and two postgraduate diplomas (1976, 1991). Education: Doctor of Philosophy, Imperial College London (1996) Master of Science, Imperial College London (1992) Postgraduate Diploma, Polytechnic of North London (1991) Postgraduate Diploma, La Trobe University (1976) Bachelor of Science, La Trobe University (1972) His research focuses on program analysis, information flow, software flow security, and testing. He applies information theory to software testing and studies semantic equivalence, robustness, and hyperproperty repair. His work often involves genetic improvement, fuzzing, and quantum software analysis. Recent publications address EM side-channel analysis in fuzzing, information flow quantification, cache optimization via evolution, and quantum output classification. He received the Best Software Science Paper award at ETAPS 2009. Scientific Awards: Best Software Science Paper, 12th European Joint Conferences on Theory and Practice of Software (ETAPS), 2009 He teaches functional programming (Haskell) and software testing, while supervising final-year undergraduate research projects. Professional activities include serving as a licentiate examiner (Chalmers University), PhD examiner (Queen Mary, Imperial College), and reviewer for EPSRC and the Research Council of Norway.

Karl P Travisمشاهده پروفایل

پژوهشگر

• Nuclear Waste Disposal
• Computational Physics
• Materials Science under Extreme Conditions
• +۴ مورد دیگر

Dr. Karl P Travis is a Reader in Computational Physics and Nuclear Waste Disposal at the School of Chemical, Materials and Biological Engineering , University of Sheffield. He serves as Exams Officer and Director of the Immobilisation Science Laboratory (ISL). His research spans computational physics, nuclear waste management, and materials behavior under extreme conditions. PhD and BSc in Chemistry from UMIST Previous positions: University of Bradford, Imperial College, North Carolina State, Cornell, Australian National University Research Focus: Deep Borehole Disposal: Developing sealing matrices, rock welding, and deployment mechanisms for nuclear waste. Collaborating with Sandia National Labs on pilot borehole projects. Material Failure Analysis: Studying radiation damage in ceramics/glasses using molecular dynamics and SPH frameworks. Simulation Methodology: Innovating algorithms for Joule-Thomson expansion, configurational thermostats, and multiscale transport analysis. Scientific Contributions: Authored over 30 publications in top journals like Physical Review Letters , Molecular Physics , and Journal of Nuclear Materials . Key areas: radiation-induced amorphization, borehole thermal modeling, and fluid transport phenomena. Professional Recognition: Fellow of the Royal Society of Chemistry Recipient of UMIST's Reynolds Prize Methodological Expertise: Specializes in molecular dynamics, dissipative particle dynamics, and novel thermostat/barostat techniques. His work bridges experimental data interpretation with theoretical validation across nuclear, chemical, and materials engineering domains.

• Chemical Reaction Engineering
• Process Control
• Applied Catalysis
• +۵ مورد دیگر

Lester Kershenbaum is Professor of Chemical Engineering at Imperial College London's Department of Chemical Engineering, Faculty of Engineering, where he has been since 1970. He progressed from Lecturer (1970–1979) to Reader (1979–1989) before becoming Professor in 1990. He holds visiting professorships at the University of Malaya (Malaysia), Universitat Rovira i Virgili (Spain), and University of Sydney (Australia), and has served as Director of Undergraduate Studies (1999–2003) and Director of Postgraduate Studies (1994–1998). Education includes: PhD in Chemical Engineering, University of Michigan (1960–1964) MS Mathematics, University of Michigan (1963) MSE Chemical Engineering, University of Michigan (1961) BChEE Chemical Engineering, The Cooper Union (1956–1960) His research centers on applied catalysis and process systems engineering . Key areas include catalytic reactors governed by physical/chemical processes (e.g., fluid catalytic cracking), multifunctional reactors integrating reaction, energy, and separation (notably solid oxide fuel cells), and experimental implementation of advanced control algorithms (model-predictive, neural-network, and Lyapunov-based controllers) using PARSEX reactor configurations.

• Experimental Aeroacoustics
• Jet Noise Modeling
• Aircraft Noise Reduction
• +۲ مورد دیگر

Dr Jack LT Lawrence is a Senior Research Fellow in Experimental Aeroacoustics within the Faculty of Engineering and Physical Sciences at the University of Southampton. He coordinates major EU and UK-funded research projects focused on aircraft noise reduction, including HARMONY (wHole AiRcraft Multidisciplinary nOise desigN sYstem) and JERONIMO (JEt noise of high bypass RatiO eNgines). His work involves designing advanced wind tunnel facilities at the Rolls-Royce University Technology Centre's anechoic Doak Laboratory. Lawrence's research centers on experimental aeroacoustics with specialization in jet noise mechanisms, particularly installed jet-wing interactions for ultra-high bypass ratio engines (BPR > 12). His work combines wind tunnel testing, hot-wire anemometry, and computational modeling to develop noise prediction tools and mitigation strategies for next-generation aircraft. Key methodologies include turbulence flowfield analysis, wall-pressure fluctuation measurements, and 3D-printed nozzle testing. His recent publications demonstrate consistent focus on jet-surface interaction noise, with trends showing increasing sophistication in modeling realistic wing configurations and nozzle geometries. Research spans both fundamental fluid dynamics and applied aerospace engineering, emphasizing experimental validation of computational models. Lawrence supervises PhD researcher Edoardo Carbini and collaborates extensively with Rolls-Royce, QinetiQ, and European aerospace partners. His projects include Deep Cavity Noise Mitigation Testing and H2020-SENECA, funded by the European Union. Current work involves commissioning new wind tunnel facilities for coaxial jet noise research. He is a member of the Acoustics Group and Institute for Life Sciences, conducting research in the Rolls-Royce University Technology Centre's anechoic Doak Laboratory. His experimental work utilizes advanced facilities for jet noise characterization and validation of numerical simulations.

• Spatial audio
• Sound fields
• Microphone arrays
• +۳ مورد دیگر

Achilles Kappis is a Marie Sklodowska-Curie Research Fellow at the University of Southampton, affiliated with the Signal Processing Audio and Hearing Group. His research focuses on advancing spatial audio technologies through innovative microphone array configurations and virtual sensing methodologies. His core research investigates sound field analysis and reproduction using optimized microphone arrays, with particular expertise in virtual sensing techniques for diffuse sound environments. Dr. Kappis develops novel array topologies that enable remote sensing applications while minimizing hardware requirements, bridging theoretical acoustic modeling with practical implementation for active noise control systems and spatial audio reproduction. Recent publications (2024-2025) reveal a concentrated research trajectory in microphone array optimization, with increasing sophistication in handling diffuse sound fields and multi-microphone configurations. His work demonstrates consistent progression from fundamental array design to specialized applications in active noise control, showing strong interdisciplinary connections between acoustics, signal processing, and audio engineering. Dr. Kappis has been awarded the prestigious Marie Sklodowska-Curie Fellowship, recognizing his research excellence and potential for scientific leadership. This competitive EU-funded fellowship supports his current research at Southampton. Supported by the Marie Sklodowska-Curie Actions grant, Dr. Kappis conducts independent research while collaborating with Southampton's audio research community. His work involves both theoretical development and experimental validation, with potential applications spanning consumer audio, transportation noise control, and assistive hearing technologies. Within the Signal Processing Audio and Hearing Group, Dr. Kappis leads research on advanced microphone array systems for virtual sensing applications. His current projects focus on optimizing array configurations for specific acoustic challenges, particularly in environments with complex sound field characteristics where conventional approaches fail.

• Rotorcraft Flight Dynamics
• Inverse Simulation
• Aerospace Engineering
• +۷ مورد دیگر

Douglas G Thomson is a Senior Lecturer in Autonomous Systems & Connectivity at the University of Glasgow's School of Engineering, specifically within the Aerospace Sciences department. He has held various leadership positions including Head of the Department of Aerospace Engineering (2000-2007) and Head of the Aerospace Sciences Research Division since 2010. Currently, he also serves as the Chief Adviser of Studies for Engineering within the School. Dr Thomson's research primarily focuses on rotorcraft flight dynamics, with notable contributions in inverse simulation techniques applied to rotorcraft. His work spans several specialized areas including evasion strategies for helicopter avoidance of RPG threats, guidance and control of underwater vehicles, and autogyro flight dynamics. Recent research has expanded into planetary exploration rovers, autonomous search and rescue systems, and reinforcement learning applications for drone navigation. His publication record shows a clear evolution from traditional helicopter and rotorcraft dynamics toward autonomous systems and planetary exploration. The most recent publications (2023-2025) demonstrate a strong focus on robotics, AI applications in search and rescue, and planetary exploration technologies, while maintaining his foundational expertise in flight dynamics and inverse simulation. Scientific Awards: Royal Society University Research Fellowship Dr Thomson has supervised numerous PhD and Master's students, with recent collaborations indicating active mentoring in robotics, aerospace engineering, and autonomous systems. His research has been supported by various grants focused on aerospace innovation, autonomous systems, and space exploration technologies. He leads a research team working on fixed-base flight simulators for rotorcraft piloted simulation studies and has developed important understanding of autogyro flight characteristics through simulation and flight testing.

• Cybersecurity
• Safety Critical Systems
• Industrial Control Systems
• +۴ مورد دیگر

Henry Hui serves as a Research Fellow at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, where he conducts cutting-edge cybersecurity research focused on critical infrastructure protection. His work bridges theoretical security frameworks with practical industrial applications across multiple high-stakes domains. His research expertise spans several interconnected cybersecurity domains: Industrial Control Systems Security : Specializing in vulnerability analysis of Siemens S7 PLCs, secure Smart Grid communications, and ICS testbed development for critical infrastructure protection Safety-Critical Systems : Developing security pattern implementations and runtime monitoring architectures for systems where failure could cause catastrophic consequences Automotive Cybersecurity : Addressing security gaps through ISO/SAE 21434 standard implementation and vehicle security architecture design Embedded Systems Security : Creating security solutions for resource-constrained environments including hypervisor monitoring and hardware-based cryptographic acceleration Analysis of his 2018-2025 publication record reveals consistent focus on practical security solutions for industrial environments. His recent work demonstrates increasing specialization in hardware security (2025 RISC-V research) while maintaining strong industry relevance through automotive standards and PLC vulnerability research. This trajectory shows sophisticated evolution from foundational ICS security (2018-2019) toward integrated hardware-software security solutions. No scientific awards or professional honors were documented in the available information. Information regarding student supervision, research grants, or laboratory facilities was not provided in the source materials, though his collaborative fingerprint shows active engagement with five similar research profiles across cybersecurity domains.

• Combinatorial rigidity
• Graphs and matroids
• Discrete and computational geometry
• +۷ مورد دیگر

Professor Anthony Nixon is a faculty member at the School of Mathematical Sciences, Lancaster University , where he serves as Professor in Mathematical Sciences since August 2024. He leads Lancaster's Combinatorics research theme and contributes to the Geometric Rigidity research theme . His research focuses on combinatorial rigidity theory , specifically analyzing systems of equations from geometric constraint systems to determine rigidity/flexibility of structures like bar-joint frameworks. This work intersects structural graph theory , matroid theory , projective geometry , and semi-definite programming . Notable applications include biophysical materials and robotic formation control . The 10 submitted papers cover topics like hypergraph rigidity, nearly planar graph rigidity, angular constraints, tropical rigidity approaches, and k-fold matroid circuits. His recent EPSRC grants include £428,712 for abstract rigidity research and £45,952 for graph rigidity in arbitrary dimensions. Scientific awards include: EPSRC grant (2023-2026): Abstract rigidity for natural stability problems (£428,712) EPSRC grant (2022-2023): The graph rigidity problem in arbitrary dimension (£45,952) Heilbronn Institute fellowship (2020-2021): £42,135 He supervises PhD students Rebecca Monks , Daniel Hodgson , Jack Trainer , and Andrew Sainsbury (part-time). Collaborators include Sean Dewar , Bill Jackson , and Brigitte Servatius . He has organized major events like the Mathematics, AI and Data Science for Materials Innovation workshop (Lancaster, 2025) and ICERM semester program on Geometry of materials (Brown, 2025).

• Artificial Intelligence
• Cyber-Physical Systems
• Regulatory Compliance
• +۵ مورد دیگر

Sarogini Pease is a Lecturer in Intelligent Networks at Loughborough University, with expertise spanning AI, cyber-physical systems, and regulatory compliance in creative industries. She holds a PhD funded by EPSRC and BAE Systems, an LLB (Hons) in Law from the University of Essex, and advanced qualifications in Computer Science and Communications. Her research focuses on empowering developers and users with AI-driven tools to navigate legal challenges in AI/metaverse technologies, particularly data ownership, intellectual property, and algorithmic transparency. Key areas include semantic services, decision support systems, and interoperability frameworks for real-time regulatory compliance. Publications emphasize energy-efficient manufacturing, cyber-physical system design, and adaptive middleware for mobile networks. Notable contributions include semantic interoperability tools and embedded intelligence for future manufacturing systems. Awards include the CASE award from EPSRC/BAE Systems for her doctoral research. Her work bridges technical and legal domains, with grants from EPSRC and BAE Systems. She is affiliated with research groups focused on intelligent networks and semantic technologies, contributing to both academic and industrial collaborations.