جستجوی استاد راهنمای دانشگاهی

• Digital Strategy
• Innovation Management
• Open Innovation
• +۷ مورد دیگر

Christopher L. Tucci is a Professor of Digital Strategy & Innovation at Imperial College London's Business School and currently serves as Interim Vice Dean of Education. He is also the Founding Dean of NEOM's College of Business & Innovation in Saudi Arabia. Previously, he held the Chair in Corporate Strategy & Innovation at École Polytechnique Fédérale de Lausanne (EPFL), where he served as Dean of the College of Management from 2013 to 2018. His academic qualifications include a PhD in Management from MIT and multiple degrees from Stanford University: an AB in Music, BS in Mathematical Sciences, and MS in Computer Science and Computer Science. His research focuses on digital strategy, innovation management, open innovation, and business model innovation, with particular emphasis on how firms transition to new technologies and organizational forms. He has pioneered work on crowdsourcing, inter-networking, and AI-driven innovation. His award-winning article 'Crowdsourcing as a Solution to Distant Search' (co-authored with Allan Afuah) has received multiple accolades, including the AMR Decade Award in 2022. Professor Tucci teaches courses such as AI Ventures, Co-Creation in AI & Robotics, and Design Thinking. He actively contributes to academic leadership roles, including serving on the Academy of Management's Board of Governors and leading initiatives like Imperial's I-X (Artificial Intelligence and Digital Innovation hub). His work integrates technology, strategy, and organizational dynamics to address modern business challenges. Educations: PhD in Management, MIT (1992–1997) SM in Technology & Policy/EECS, MIT (1989–1991) BS in Mathematical Sciences, Stanford (1978–1982) AB in Music, Stanford (1979–1983) MS in Computer Science, Stanford (1982–1984) Labs/Teams: Co-Director of Imperial's I-X initiative, focusing on AI, data science, and digital innovation.

Yvonne Rogersمشاهده پروفایل

استاد

• Ubiquitous Computing
• Interaction Design
• Human-Computer Interaction
• +۱ مورد دیگر

Yvonne Rogers is a Professor of Interaction Design and Director of the UCL Interaction Centre (UCLIC), with a joint appointment as Deputy Head of the Department of Computer Science at University College London. She joined UCL in 2011 after holding professorships at the Open University (2006-2011) and Indiana University (2003-2006). Her pioneering work spans ubiquitous computing, interaction design, and human-computer interaction, with a current focus on human-centered AI. She co-authored the definitive 'Interaction Design' textbook (6 editions, 300,000+ copies) and serves as CTO of LetThink.com. Research interests center on designing technologies that enhance human cognition and daily activities: Ubiquitous Computing: Augmenting learning/work activities through pervasive technologies Human-AI Interaction: Developing AI systems that enhance human decision-making Health Technologies: Creating VR therapies and ADHD support systems Community Resilience: Designing tools for environmental monitoring and sustainable practices Publication analysis reveals three dominant trends: (1) VR applications for mental health (emotion regulation, ADHD support), (2) AI systems for cognitive augmentation, and (3) community-centered tools for healthcare/environmental challenges. Recent work demonstrates strong emphasis on vulnerable populations including children with ADHD, older adults, and postoperative patients. Major scientific recognition includes: International Member, National Academy of Engineering (2024) ACM SIGCHI Lifetime Research Award (2022) Royal Society Robin Milner Medal (2022) Royal Society Fellowship (2022) Microsoft Outstanding Collaborator Award MRC Suffrage and Science Award (2020) Triple Fellow status (ACM, BCS, CHI Academy) Advises PhD students including Leon Reicherts, Sheena Visram, and Tu Duong. Secured major grants including EPSRC Dream Fellowship on ageing/computing and led the Intel Collaborative Research Institute on Sustainable Connected Cities (2012-2018). Directs UCLIC research center and previously established the Pervasive Interaction Lab at Open University.

Marya Besharovمشاهده پروفایل

استاد

• Leadership
• Social Impact
• Hybrid Organizations
• +۷ مورد دیگر

Marya Besharov is a Professor of Organisations and Impact at Saïd Business School, University of Oxford, and Academic Director of the Skoll Centre for Social Entrepreneurship. She holds a BA, MA, and PhD from Harvard University, alongside an MBA from Stanford University. Her work focuses on leadership, social impact, and hybrid organizations, advising global entities on balancing social and financial priorities. Education: PhD in Organizational Behavior, Harvard University MA in Sociology, Harvard University BA in Social Studies, Harvard University MBA, Stanford University Research Interests: Dr. Besharov’s research explores how organizations navigate competing goals, particularly in hybrid models like social enterprises. She investigates organizational identity, institutional logics, and leadership frameworks for systemic change. Her findings appear in Administrative Science Quarterly , Harvard Business Review , and Stanford Social Innovation Review . Engagement & Teaching: She leads executive education programs and workshops on leadership and systems change through the Skoll Centre. Her teaching emphasizes contingency-based frameworks for managing organizational complexity. Labs & Initiatives: Academic Director of the Skoll Centre for Social Entrepreneurship, a global hub for social impact education and research.

Leslie Ann Goldbergمشاهده پروفایل

استاد

• Algorithms
• Complexity Theory
• Randomised Algorithms
• +۵ مورد دیگر

Leslie Ann Goldberg is a Senior Research Fellow at St Edmund Hall and Professor of Computer Science at the University of Oxford. She currently serves as Head of the Department of Computer Science (on sabbatical 2025-26) and focuses on foundational problems in Algorithms and Complexity Theory , particularly randomised algorithms for network communication, machine learning, and statistical physics models. Her research includes solving Aldous' 1987 conjecture on backoff protocol instability (with John Lapinskas), developing rigorous mathematical analysis frameworks for algorithmic efficiency, and advancing approximate counting techniques via Markov Chain Monte Carlo methods (with Andreas Galanis and collaborators). Key projects involve graph homomorphisms , Moran process dynamics , and #BIS complexity class analysis. Recent publications (2023-2024) span topics like Sybil defense mechanisms, low-temperature sampling on random graphs, and parameterised subgraph counting modulo 2. Her work demonstrates cross-disciplinary impact in computational biology, statistical physics, and database theory. Scientific Awards include Best Paper Prizes at ICALP 2016, ICALP 2010, and IPEC 2017. She supervises PhD student Paulina Smolarova and collaborates extensively with researchers in Oxford and beyond.

• Algebraic Geometry
• Moduli Spaces
• Stability Conditions
• +۴ مورد دیگر

Arend Bayer is a Professor of Algebraic Geometry at the University of Edinburgh's School of Mathematics, where he has been a faculty member since 2012. He specializes in areas such as stability conditions, moduli spaces, and derived categories, contributing to the understanding of Fano varieties, K3 surfaces, and wall-crossing phenomena. His research emphasizes collaboration, reflecting his belief in mathematics as a social endeavor. Education: Arend holds degrees from prestigious institutions, including a PhD from the University of Bonn, with earlier studies at Heidelberg University and a year at the University of Cambridge. His academic journey reflects a deep commitment to advancing algebraic geometry through rigorous research and interdisciplinary collaboration. Research Interests: Arend’s work focuses on algebraic geometry, particularly in stability conditions, Fano varieties, and moduli spaces. He explores the interplay between algebraic structures and geometric objects, often employing derived categories and wall-crossing techniques. His contributions include foundational insights into Kuznetsov components and the geometry of cubic threefolds. Collaborations are central to his approach, emphasizing problem-solving through shared ideas and sustained intellectual exchange. Scientific Awards: No specific scientific awards were mentioned in the provided text. Advising and Grants: While specific advising records or grant details are not detailed in the text, Arend’s collaborative approach suggests active involvement in mentoring and securing research funding. Labs and Teams: Arend contributes to a thriving research group within the School of Mathematics at Edinburgh, focusing on structural and symmetrical aspects of algebraic geometry. His work aligns with broader initiatives in the department, fostering a collaborative environment for advanced mathematical inquiry.

• Quantum Computation
• Quantum Algorithms
• Computational Complexity
• +۳ مورد دیگر

Ashley M R Montanaro is a Professor of Quantum Computation at the School of Mathematics, University of Bristol . Active in quantum computing research since at least 2014, they lead projects at the intersection of quantum algorithms , computational complexity , and quantum information theory , affiliated with the Bristol Quantum Information Institute. Research interests focus on quantum algorithm design , computational complexity analysis , and quantum simulation . Key work includes developing variational quantum algorithms for phase transition detection, Hamiltonian simulation techniques, and quantum-classical hybrid methods for solving complex problems in physics and optimization. Recent publications demonstrate expertise in: Quantum phase diagram simulation with low-depth circuits Quantum speedups for constraint satisfaction problems Quantum communication complexity of machine learning tasks Quantum-enhanced optimization heuristics Hamiltonian simulation with time-dependent product formulas Quantum algorithm complexity analysis Scientific awards include: EPSRC Fellowship (2014-2019) - "New insights in quantum algorithms and complexity" Active in quantum software development through projects like: "Quantum Algorithms from Foundations to Applications" (ERC-2018-COG) "Quantum Computing and Simulation Hub" (2019-2024) "Prosperity Partnership in Quantum Software" (2019-2023)

Dylan Jonesمشاهده پروفایل

استاد

• Operational Research
• Logistics
• Healthcare
• +۳ مورد دیگر

Professor Dylan Jones is a Professor of Operational Research at the University of Portsmouth within the School of Mathematics and Physics. He holds dual affiliations with the Centre for Operational Research and Logistics and the Centre of Excellence in Defence, Risk & Resilience. His academic journey includes a BSc (Hons) in Mathematics with Operational Research from the University of Southampton and a PhD in Operational Research from the University of Portsmouth. Specializing in Multi-Criteria Decision Making (MCDM), his research spans logistics, healthcare, renewable energy, and defense applications. He has led over 18 PhD theses and secured EU funding for projects focused on offshore wind energy and sustainable logistics. Professor Jones is also the Director of the Centre for Operational Research and Logistics, emphasizing strategic port development and disaster risk reduction. His work integrates advanced methodologies like goal programming and mixed modeling to address complex real-world challenges. Recent contributions include frameworks for offshore wind farm logistics, sustainable port selection, and resilience-based maintenance strategies. Education: BSc (Hons) in Mathematics with Operational Research, University of Southampton PhD in Operational Research, University of Portsmouth Research interests revolve around applying operational research principles to solve multi-objective problems in logistics, healthcare systems, and renewable energy sectors. His work emphasizes sustainability, decision-making under uncertainty, and optimizing resource allocation. Key projects include developing methodologies for offshore wind energy infrastructure and analyzing risk in maritime logistics. His research outputs (109+ publications) focus on advancing operational research techniques, with notable contributions to goal programming, logistics optimization, and multi-criteria decision analysis. He collaborates internationally, particularly in Brazil, France, Spain, and Portugal, to address global challenges in sustainable energy and infrastructure. Labs/Teams: Centre for Operational Research and Logistics Centre of Excellence in Defence, Risk & Resilience

Tan Viet Tuyen Nguyenمشاهده پروفایل

مدرس

• Human-centered Artificial Intelligence
• Social Human-Robot Interaction
• Multimodal Perception and Interaction
• +۵ مورد دیگر

Dr. Tan Viet Tuyen Nguyen is a New Frontiers Fellow (Lecturer) in AI at the University of Southampton, specializing in Human-Centered Artificial Intelligence and Social Human-Robot Interaction. His research focuses on multimodal learning for robots to adapt their behavior to human social needs, with applications in healthcare, education, and service environments. Prior to this role, he was a Research Associate at King’s College London and a Research Assistant on the EU-funded CARESSES project, developing culturally-aware assistive robots for elderly support. Education: PhD in Information Science (Robotics) from Japan Advanced Institute of Science and Technology. He has organized conferences such as the IEEE RO-MAN 2022 special session on nonverbal communication and served as a reviewer for top-tier robotics and AI conferences. Research Interests include: Human-Robot Collaboration, Multimodal Perception, Generative AI for Social Interaction, and Context-Aware Robot Behavior Generation. His work has been recognized with awards including the Best Paper Award at ROMAN 2022 and the Prospective Research Award at ICServ 2023. Teaching Responsibilities include courses on Biologically Inspired Robotics, High-Level Programming, and MSc/Undergraduate project supervision. He currently oversees two PhD students and collaborates on projects like 'Exploring the impact of AI-driven writing of engagement in climate change' and 'Bridging Generations and Cultures through Generative AI.' Labs/Teams: Member of the Agents, Interaction and Complexity Centre and the Centre for Robotics Research at Southampton.

• Algorithms
• Game Theory
• Automata Theory
• +۷ مورد دیگر

Marcin Jurdzinski is an Associate Professor (Reader) in the Department of Computer Science at the University of Warwick , UK. He has been a faculty member since 2004 and is a core member of the Foundations of Computer Science and Discrete Mathematics and its Applications research groups. University: University of Warwick School: Faculty of Science Department: Department of Computer Science Position: Associate Professor (Reader) Email: Marcin.Jurdzinski@warwick.ac.uk Office: CS2.19 His research lies at the intersection of algorithms, game theory, automata, and logic , with a strong emphasis on formal verification , model checking , and theoretical computer science . He is best known for his foundational work on parity games , including the development of small progress measures and discrete strategy improvement algorithms. The recent publications reveal a consistent focus on computational complexity in games and verification. Key themes include stochastic games, timed automata, bisimilarity, and quantitative analysis . His work often bridges theoretical insights with practical verification challenges, especially in real-time and probabilistic systems. He has supervised several PhD students and hosted postdoctoral researchers such as Laure Daviaud and Alexander Kozachinskiy. He has led EPSRC-funded projects including Solving Parity Games in Theory and Practice and Counter Automata: Verification and Synthesis . PhD Students: Aditya Prakash, Thejaswini K. S., Michail Fasoulakis, John Fearnley, Michal Rutkowski, Ashutosh Trivedi Postdocs: Laure Daviaud, Alexander Kozachinskiy He is actively involved in the academic community, serving on the steering committee of the Highlights of Logic, Games and Automata conference and on program committees for major venues such as CONCUR, ICALP, and LICS. He has also organized workshops including FORMATS and ICALP co-located events.

Justin Sirignanoمشاهده پروفایل

استاد

• Applied Mathematics
• Machine Learning
• Financial Mathematics
• +۷ مورد دیگر

Justin Sirignano is a Professor of Mathematics at the University of Oxford, affiliated with the Mathematical Institute. His research bridges Applied Mathematics, Machine Learning, and Financial Mathematics, developing novel mathematical frameworks and computational methods. Education: B.A. in Mathematics, Princeton University PhD in Mathematics, Stanford University Chapman Fellow, Imperial College London His research focuses on theoretical and applied aspects of machine learning, particularly in mean-field analysis of neural networks , deep learning for PDEs/SDEs , and scientific machine learning . He has pioneered methods for solving complex financial and scientific problems using data-driven approaches. His recent publications emphasize recurrent neural networks, reinforcement learning, and PDE closure models with applications in turbulence simulation and hypersonic flows. These works span numerical methods, optimization, and stochastic processes. Scientific Awards: 2014 SIAM Financial Mathematics and Engineering Conference Paper Prize Grants & Collaborations: He has secured over $16.5 million in funding from agencies like ONR, NSF-EPSRC, and DoE. His PhD students hold positions at J.P. Morgan, Bank of America, and other institutions. Labs & Teams: He leads research groups in Machine Learning and Mathematical Finance at Oxford, collaborating with institutions like Notre Dame, Boston University, and UIUC.

Salome Voegelinمشاهده پروفایل

استاد

• Sound Studies
• Sound Practice
• Politics
• +۷ مورد دیگر

Salome Voegelin is a Professor of Sound Art at the London College of Communication, University of the Arts London. She is a leading figure in sound studies, focusing on listening as a socio-political practice and the transversal potential of sound across disciplines. Her research explores the intersections of sound with politics, feminism, and pedagogy, and she leads projects like Listening across Disciplines II (LxDII), funded by the AHRC, which investigates listening as a research methodology. Education: PhD in Sound Art, Goldsmiths, University of London (2000–2004) BA (Hons) Fine Art Film and Video, Central Saint Martins (1994–1997) PGCertHE, Middlesex University Research Interests: Sound Studies, Sonic Pedagogy, Feminism, Interdisciplinary Knowledge Production, Sonic Methodologies Her work bridges artistic practice and theory, including collaborations with David Mollin and co-convening Points of Listening . Key books include Listening to Noise and Silence (2010), The Political Possibility of Sound (2018), and Sonic Possible Worlds (2021). She is a member of the Creative Research into Sound Arts Practice (CRiSAP) and leads the Sounding Knowledge Network. Recent articles and presentations highlight themes like transversal sound studies, the ethics of listening, and curatorial practices. Her projects emphasize participatory engagement and the socio-political dimensions of sound.

• Online Algorithms
• Learning-Augmented Algorithms
• Theoretical Analysis of Algorithms
• +۷ مورد دیگر

Christian Coester is an Associate Professor of Computer Science at the University of Oxford and a Tutorial Fellow at St Anne's College. His research focuses on theoretical computer science, particularly in the design and analysis of algorithms for problems involving uncertainty and incomplete information. His primary research areas include: Online algorithms, with groundbreaking work on the k-server problem (including refuting the randomized k-server conjecture, which earned the STOC 2023 Best Paper Award) Learning-augmented algorithms (algorithms with predictions) that leverage machine learning predictions while maintaining robustness guarantees Fundamental problems such as the k-taxi problem, metrical task systems, and online shortest paths Coester's theoretical work aims to develop algorithms with provable performance guarantees, particularly focusing on competitive ratios that measure worst-case performance against optimal offline solutions. His research often addresses problems that are 'simple to state and hard to solve,' leading to techniques with broad applicability across theoretical computer science. His publications span top venues including STOC, FOCS, SODA, and ICML, showing consistent contributions to both classical online algorithms and the emerging field of learning-augmented algorithms. The publications reveal a strong focus on metric spaces, competitive analysis, and the integration of prediction models into traditional algorithmic frameworks. Coester has received significant recognition including the STOC 2023 Best Paper Award and a substantial ERC Starting Grant (EUR 1.5M) for 'Challenges in Competitive Online Optimisation' (2025-2029). He actively supervises PhD students and welcomes inquiries from mathematically skilled candidates interested in theoretical computer science.

• AI in Healthcare
• Electronic Health Records Analysis
• Biomedical Time Series Analysis
• +۶ مورد دیگر

Dr. Kezhi (Ken) Li is an Associate Professor of AI in Healthcare at the Institute of Health Informatics, University College London (UCL). He leads the AI for Health research group and has established himself as a leading expert in applying artificial intelligence to solve complex problems in healthcare, with over 130 publications in leading journals (total impact factor greater than 400). Dr. Li earned his Doctor of Philosophy from Imperial College of Science, Technology and Medicine in 2013, followed by research positions at the Medical Research Council (2015-2017), University of Cambridge (2014-2015), and Royal Institute of Technology (KTH) (2013-2014). His academic journey reflects a consistent trajectory from technical AI research toward increasingly healthcare-focused applications. Dr. Li's research focuses on solving physiological, medical, clinical, and operational problems in healthcare using AI techniques. His specific expertise includes AI in healthcare using electronic health records (EHR), biomedical time series analysis using monitors/wearables, diabetes management, large language models (LLM) in healthcare (especially mental health), patient flow optimization, and digital health with federated learning. His work bridges the gap between cutting-edge AI methodologies and practical healthcare applications, with a strong focus on improving patient outcomes and healthcare system efficiency. Analysis of Dr. Li's publication history reveals a strong emphasis on diabetes management technologies, particularly blood glucose prediction systems using advanced neural network architectures. More recently, his work has expanded into mental health applications of large language models, blockchain-based federated learning for healthcare data, and mortality prediction in critical care settings. His research demonstrates a clear evolution from purely technical AI development toward increasingly clinically impactful applications, with growing emphasis on explainability, privacy preservation, and real-world implementation challenges. Dr. Li has received numerous prestigious awards recognizing his contributions to healthcare AI: Best Application Award of IEEE Global Blockchain Conference (2025) Fellow of British Computer Society (2025) Fellow of the Royal Society for Public Health (2024) Healthcare Partnership of the Year category at the London Higher Awards (2024) ECR Promising Project Award (2023) Gallivan Award finalists (2022) Stylianos Kalaitzis PhD Award Winner (2022) HDR UK Team of the Year (COVID-19) Award (2021) As an educator, Dr. Li serves as the Director of MRes study (AI-enabled Healthcare Systems) at UCL. He leads multiple key modules including Healthcare Artificial Intelligence Journal Club, Dissertation in Artificial Intelligence Enabled Healthcare, and Advanced Machine Learning for Healthcare. His supervision extends across dissertation projects and junior researchers in his AI for Health group. His research has been supported by various grants, including those from HDR UK, focusing on translating AI innovations into practical healthcare solutions. Dr. Li leads the AI for Health research group (https://ai4hucl.github.io/ai4h_webs/), which comprises researchers with diverse expertise in machine learning, healthcare systems, and clinical domains. The group maintains strong collaborations with healthcare providers and industry partners to ensure their research addresses real-world healthcare challenges and can be effectively translated into clinical practice.

• Geospatial Engineering
• Positioning, Navigation, and Timing (PNT)
• Global Navigation Satellite Systems (GNSS)
• +۳ مورد دیگر

Dr. Ma'Mon Saeed Alghananim is an Honorary Research Fellow at the Department of Civil and Environmental Engineering , Faculty of Engineering , Imperial College London. His work focuses on geospatial engineering and Positioning, Navigation, and Timing (PNT) for mission-critical systems. PhD in Civil and Environmental Engineering, Imperial College London (2022) MSc in Geospatial Engineering, University of New South Wales (UNSW) BSc in Surveying and Geomatics Engineering, Al-Balqa Applied University, Jordan Dr. Alghananim pioneered the Maximum non-Bounded Difference (MnBD) method to solve a 20-year-old GNSS overbounding error problem, enhancing safety in critical applications. He also developed the GEV-based Gaussian distribution for extreme event modeling in complex datasets. His research spans GNSS error analysis , extreme value statistics , and safety-critical systems , contributing to high-profile projects like the European Space Agency's INSPIRe and UKRI's WeWalk . No scientific awards are explicitly mentioned.

Sina Sarehمشاهده پروفایل

استاد

• Soft robotics
• Multi-modal mobility
• Manipulation and attachment
• +۱ مورد دیگر

Sina Sareh is a robotics researcher at the Royal College of Art (RCA), where he leads the RCA Robotics Laboratory within the School of Design. He has established himself as an expert in soft robotics and multimodal sensing, developing innovative solutions for human safety and access problems in industrial operations. Dr. Sareh's educational background includes: PhD in Robotics from the University of Bristol, where he worked on monolithic design of flexible actuators for operation in confined liquid environments MSc in Control Systems from the University of Sheffield BSc in Electrical Engineering from Amirkabir University of Technology, Tehran Dr. Sareh's research focuses on soft robotics, multi-modal mobility, manipulation and attachment, and multimodal sensing. His work bridges the gap between robotics engineering and practical applications, particularly in medical and industrial settings. He has developed novel approaches to robotic attachment inspired by octopus biology, created haptic interfaces that mimic the feeling of touching human internal organs, and designed soft robotic technologies to help articulate pain symptoms. His research consistently demonstrates innovation in creating adaptable robotic systems that can operate effectively in complex, unstructured environments where traditional rigid robots face limitations. His publication record demonstrates a strong trajectory in robotics research, with emphasis on soft robotics, medical applications, and novel sensing techniques. The research shows progression from fundamental soft actuator design to practical applications in surgery, industrial operations, and human-robot interaction, with a consistent focus on solving real-world problems through biologically inspired approaches. Dr. Sareh has successfully secured multiple research grants, including EPSRC funding for 'Getting a Grip' and 'Multi-vendor Interoperability in Robotics,' as well as InnoHK funding for 'Intelligent Medicine Warehousing.' He has also served as an impact assessor for the Research Excellence Framework (REF) 2021 in Engineering and is a member of the editorial board at IET Cyber-physical Systems and Robotics Journal. Currently, Dr. Sareh advises research students including Filippo Sanzeni, and maintains active collaborations with industry and academic partners through the RCA Robotics Laboratory, which serves as a hub for interdisciplinary robotics research at the intersection of design, engineering, and human-centered applications. His work on projects like 'Topographies of Pain' and 'Reminisys' demonstrates a commitment to applying robotics technology to improve healthcare outcomes and quality of life.