جست‌وجوی استاد و پژوهشگر

Adrian Wellerمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Machine Learning
• Explainability
• +۹ مورد دیگر

Adrian Weller is a prominent researcher and academic at the University of Cambridge, serving as a Director of Research in Machine Learning within the Department of Engineering. He holds multiple significant leadership roles including Programme Director for Trust and Society at the Leverhulme Centre for the Future of Intelligence (CFI), and previously served as Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI. His work bridges theoretical machine learning research with practical applications and societal implications of artificial intelligence. Weller's research interests span a broad spectrum of AI and machine learning topics with a particular focus on ensuring beneficial societal outcomes. His work encompasses explainability, fairness, robustness, scalability, privacy, safety, and ethics in AI systems. He has made significant contributions to trustworthy machine learning, including developing frameworks for AI governance, certification, and human-AI collaboration. His research group actively investigates neuro-symbolic approaches, privacy-preserving techniques, and methods for improving the reliability and interpretability of AI systems. His recent publications demonstrate a strong trend toward addressing the practical challenges of deploying AI systems in real-world contexts, particularly focusing on certification frameworks, governance mechanisms, and human-centered approaches. His work spans theoretical advances in machine learning architectures while maintaining a strong connection to societal impact, with publications appearing in top venues across AI, machine learning, and interdisciplinary applications. Scientific Awards: MBE for services to digital innovation (2022 Queen's Birthday Honours) Turing AI Fellowship for Trustworthy Machine Learning Weller actively supervises a large group of PhD students and postdocs, with current students including Juyeon Heo, Yanzhi Chen, Katie Collins, Isaac Reid, Yichao Liang, Herbie Bradley, and Shoaib Siddiqui. His former students have gone on to positions at leading institutions including Google DeepMind, ETH Zurich, NYU, and MPI-IS Tübingen. He has served on numerous advisory boards including the Centre for Data Ethics and Innovation, UNESCO's expert group on AI ethics, and the World Economic Forum's Global Future Council on AI. His research has been supported through his Turing AI Fellowship and various collaborative projects focused on safe and ethical AI development. Weller leads a vibrant research group focused on trustworthy machine learning, which actively organizes workshops and conferences including ICML 2024 (where he served as Program Chair), multiple workshops on responsible AI, and events through the ELLIS network. His group collaborates extensively across disciplines, working with researchers in computer science, social sciences, law, and policy to address the multifaceted challenges of developing beneficial AI systems.

Walid Magdyمشاهده پروفایل

استاد

• Computational Social Science
• Natural Language Processing
• Social Content Analysis
• +۸ مورد دیگر

Walid Magdy is a Professor at the School of Informatics, The University of Edinburgh, where he is a faculty member at the Institute for Language, Cognition and Computation (ILCC). He holds a PhD from Dublin City University's School of Computing and has been a faculty fellow at The Alan Turing Institute. With substantial industry experience, he has worked for Qatar Computing Research Institute (QCRI), Microsoft, and IBM, where he filed nine patents. His research spans computational social science and natural language processing. In computational social science, he focuses on social content analysis, political bias detection, polarization, and users' behavior analysis/prediction, with particular attention to understudied communities. His natural language processing work centers on social applications including sentiment analysis, sarcasm detection, and hate-speech identification, with specialized expertise in Arabic and its dialects as well as Persian. Professor Magdy's recent publications demonstrate a consistent focus on Arabic language processing and social media analysis, with growing attention to cultural factors in NLP systems. His work bridges computational methods with social science questions, particularly regarding misinformation, cultural differences in online behavior, and the impact of platform policies on diverse linguistic communities. He has expanded his research to include Persian language processing and continues to explore social dynamics across different cultural contexts. His significant contributions have been recognized with multiple awards: Best Demo Award for TwiXplorer at CSCW 2024 Outstanding Paper Award at ACL 2024 Best Paper Award Runner-up at SocInfo 2022 Best Paper Award at WANLP-EMNLP 2022 Best Paper Award at AIRS 2015 Best Dataset Award at ICWSM 2013 Professor Magdy serves as an editor for Springer's Social Network Analysis and Mining journal and has held leadership roles in major conferences including ACL 2023, ArabicNLP 2023, ICWSM 2022, and ASONAM 2022. He has co-organized numerous shared tasks focused on Arabic language processing and social media analysis, contributing significantly to community resources and benchmarks. He founded and directs the Social Media Analysis and Support for Humanity (SMASH) research group at the University of Edinburgh, which has organized the Summer School in Computational Social Science (SICSS-Edinburgh) in 2022, 2023, and 2025, training researchers in computational social science methodologies.

Elizabeth Froodمشاهده پروفایل

دانشیار

• Ancient Egyptian self-presentation
• Biographical texts
• Graffiti
• +۵ مورد دیگر

Elizabeth Frood is an Associate Professor of Egyptology at the University of Oxford, affiliated with the Faculty of Asian and Middle Eastern Studies. She holds dual college fellowships as a Fellow of St Cross College and Honorary Fellow of The Queen's College, with research centered on ancient Egyptian self-presentation, sacred landscapes, and social experience including gender and disability studies. Her academic journey began with first degrees completed in Aotearoa New Zealand, establishing her foundation in Egyptology before her current Oxford appointment. Professor Frood's scholarship uniquely reconstructs non-royal Egyptian lives through biographical texts, graffiti, and visual culture, specializing in the late New Kingdom and Third Intermediate Period (mid-second to early first millennium BCE). Her work bridges textual analysis with material culture studies, examining how individuals expressed identity through sacred spaces, ritual practices, and social interactions. This approach has generated significant insights into elite self-representation and non-elite participation in religious contexts. Analysis of her 14 most recent publications (2007-2023) reveals consistent thematic threads: sustained focus on Karnak temple graffiti projects, evolving methodologies in biographical text interpretation, and increasing interdisciplinary engagement with gender/disability studies. Her collaborative work with the Centre Franco-Égyptien d’Étude des Temples de Karnak demonstrates fieldwork integration with epigraphic analysis. Her academic distinctions include: Fellow of St Cross College Honorary Fellow of The Queen's College Professor Frood actively mentors doctoral researchers across diverse topics including Deir el-Medina statuary, Hatshepsut's iconoclasm, ancient graffiti contexts, gendered domestic spaces, and kinship practices. Her Karnak Graffiti Project (2011-present), co-directed with Chiara Salvador and supported by CFEETK, represents a major sustained research initiative involving fieldwork at the temple of Ptah and eighth pylon, yielding publications, media features, and international scholarly collaborations. She co-directs the Karnak Graffiti Project, a decade-long international collaboration with the Centre Franco-Égyptien d’Étude des Temples de Karnak and Montpellier-based scholars, combining archaeological documentation, epigraphic recording, and digital analysis of temple graffiti across multiple Karnak sectors.

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Andrew Zisserman is a Royal Society Research Professor at the University of Oxford's Department of Engineering Science, affiliated with the Visual Geometry Group (VGG). His research focuses on computer vision, artificial intelligence, and neural networks, with significant contributions to multimodal learning, video understanding, and 3D scene analysis. He leads projects exploring visual-language models, audio-visual synchronization, and clinical imaging applications. Key research areas include: Video analysis and temporal modeling Multimodal systems for sign language translation and action recognition 3D shape estimation and physical property inference Foundation models and cross-modal retrieval Recent work highlights: Developed Flamingo and Tapir models for video-language tasks Advancements in spinal MRI analysis and clinical imaging Leadership in EGO4D and VoxCeleb challenges Honors include Fellowship of the Royal Society (FRS) and the ISSLS Prize in Clinical Science 2023 for spinal analysis innovations. His lab collaborates globally, emphasizing real-world applications in healthcare and autonomous systems.

David Stillwellمشاهده پروفایل

استاد

• Psychometrics
• Computational Social Science
• Big Data Analytics
• +۳ مورد دیگر

David Stillwell serves as Professor of Computational Social Science at Cambridge Judge Business School and Academic Director of The Psychometrics Centre, University of Cambridge. His research leverages big data to understand human psychology and behavior, with significant contributions in personality prediction from digital footprints and personalized advertising applications. His educational background includes: BSc in Psychology from the University of Nottingham (2007) MSc in Research Methods from the University of Nottingham (2008) PhD in Decision Making from the University of Nottingham (2012) Dr. Stillwell's research centers on computational social science and psychometrics, pioneering the myPersonality Facebook application that collected data from over 6 million users. His work demonstrates computers can predict personality as accurately as spouses, reveals psychological targeting's advertising effectiveness, and establishes links between personality-matched spending and life satisfaction. He also explores linguistic honesty markers through profanity analysis and personality-based dating patterns. His recent publications (2019-2025) reveal a strong trajectory toward AI evaluation using psychometric frameworks, particularly in medical and general-purpose AI assessment. Key themes include fairness metrics in language models, crisis emotional responses through social media, and computational personality recognition - demonstrating consistent innovation at the psychology-technology intersection. He has received significant recognition: Top 10 most influential papers of 2013 by Altmetric Nieman Journalism Lab highlight of 2013 Named in 'top 30 thinkers under 30' by Pacific Standard Magazine Dr. Stillwell maintains active industry engagement through consultancy with Barclays, Hilton, and Ubisoft on projects spanning computer-adaptive testing systems to interactive experiences like Predictive World for Watch Dogs 2. His policy impact is substantial, with citations by the European Data Protection Supervisor, World Bank, and multiple national governments, leading to speaking engagements at the European Parliament and Bank of England. As Academic Director of The Psychometrics Centre, he leads a global hub for advancing psychological assessment through innovative methods including Concerto open-source software, collaborating with organizations ranging from the European Commission to major corporations on psychometric applications in people analytics and digital behavior.

Rebecca Lawsonمشاهده پروفایل

استاد

• Computational Neuroscience
• Neuroscience
• Psychiatry
• +۶ مورد دیگر

Professor Rebecca Lawson is a Professor of Neuroscience and Computational Psychiatry at the University of Cambridge, affiliated with the Department of Psychology and Bye-Fellow at Peterhouse College. Her research focuses on understanding how humans learn to make predictions under uncertainty, with applications to mental health conditions such as anxiety and depression. She leads the Prediction and Learning (PaL) Lab, which combines computational modeling, neuroimaging (e.g., 7T MRI), and behavioral experiments to study cognitive processes in typical and atypical populations. Key research interests include computational psychiatry, autism spectrum disorders, neuroimaging techniques, and the neurochemical basis of learning mechanisms. She has received significant funding, including a £4.3m Wellcome Mental Health Award and the Sir Henry Dale Fellowship. Notable contributions include advancing theories of neural gain and sensory expectations in autism, as well as studies on uncertainty processing in anxiety and depression. Professor Lawson holds academic awards such as the BNPA Lishmann Prize and the BAP Psychopharmacology Award. She actively contributes to public engagement, including initiatives like Knit-a-Neuron and involvement with PrideinSTEM. Her lab collaborates internationally, with projects like the CamRAA study investigating autism-anxiety overlaps and the Chemical and Brain Basis of Uncertainty (CBBU) study exploring pharmacological interventions. Education: PhD in Cognitive Neuroscience (University of Cambridge), BA (Hons) Psychology & Philosophy (University of Glasgow). Grants: £4.3m Wellcome Award, Parke-Davis Fellowship, Lister Institute Prize. Labs/Teams: Principal Investigator of the PaL Lab; collaborations with MRC Cognition and Brain Sciences Unit, Yale University, and Brown University.

Oana Cocarascuمشاهده پروفایل

مدرس ارشد

• Argument mining
• Explainable AI
• Machine learning
• +۵ مورد دیگر

Dr. Oana Cocarascu is a Senior Lecturer in Artificial Intelligence at the Department of Informatics, Faculty of Natural, Mathematical & Engineering Sciences, King's College London. She holds a PhD and MEng in Computing (Artificial Intelligence) from Imperial College London and conducts applied research focusing on how artificial intelligence can be deployed to support real-world applications, with machine learning and natural language processing as core components of her work. Her research interests span argument mining, explainable AI, machine learning, natural language processing, and symbolic reasoning. She is particularly focused on developing AI systems that can provide transparent, accountable, and ethical decision-making processes. Her work addresses critical challenges in bias mitigation, fairness metrics, fact verification systems, and argumentation-based explanations for complex AI decisions. Analysis of her recent publications (2023-2025) reveals a strong focus on fairness in AI systems, with particular attention to individual fairness metrics and nuanced evaluation frameworks. She has made significant contributions to fact verification systems, especially in multimodal contexts involving charts and tabular data. Her work increasingly integrates argumentation theory with natural language processing to create explainable AI systems that can justify their decisions through structured reasoning. Dr. Cocarascu leads an EPSRC-funded project titled 'A framework for evaluating and explaining the robustness of NLP models' (2024-2027) and is actively involved in the Natural Language Processing Group at KCL. Her research fingerprint shows strong activity in argumentation (100%), decision-making (74%), artificial intelligence (50%), explainable AI (39%), and bias mitigation (35%). She has contributed to numerous high-impact publications in top venues including ACL, EMNLP, AAAI, and the Journal of Artificial Intelligence Research, with a particular focus on making AI systems more transparent, accountable, and aligned with human values. Her work intersects with UN Sustainable Development Goals, particularly those related to reducing inequality and building resilient infrastructure.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۶ مورد دیگر

Timothy M. Hospedales is a Professor of Artificial Intelligence at the Institute of Perception, Action and Behaviour within the School of Informatics at the University of Edinburgh . He also serves as VP AI and Head of Samsung AI Research Centre Europe . His research focuses on efficient and robust AI , emphasizing meta-learning , lifelong transfer-learning , and domain adaptation in both probabilistic and deep learning frameworks. Applications span computer vision , vision and language , reinforcement learning for robotics , and finance . Professor at University of Edinburgh (2020–present) ELLIS Fellow (2021) Head of Samsung AI Research Europe (2020–present) Founding Director of Applied Machine Learning Lab at QMUL (2012–2016) His work includes pioneering contributions to meta-learning , few-shot learning , and self-supervised methods , with notable awards such as the Best Paper Prize at ICML AutoML 2018 and Best Student Paper at ICPR 2018 . He has co-authored 15+ recent papers on topics like Vision-Language Models , Medical AI Fairness , and Diffusion Model Optimization . He served as Program Co-Chair for BMVC 2018 and AAAI 2022 , and authored a book on Visual Adaptation in the Deep Learning Era (2022). Co-Chair, BMVC 2018 Guest Editor, IET CV Special Issue (2016) Keynote Speaker at TASK-CV Workshop (ECCV 2016) Special Issue on Fewer Labels (IEEE PAMI 2020) His leadership extends to organizing workshops like the Learning-to-Learn Workshop at ICLR 2021 , Meta-Learning Workshop at NeurIPS 2020 , and Domain Generalisation Workshop at ICLR 2023 . Current projects include Meta-Omnium (CVPR 2023) for general-purpose meta-learning and MetaAudio (ICANN 2022) for few-shot audio classification benchmarks.

Carlo Harveyمشاهده پروفایل

استاد

• Virtual Reality
• Game Design
• Computer Graphics
• +۸ مورد دیگر

Professor Carlo Harvey is a creative technologist at the School of Digital Arts (SODA), Manchester Metropolitan University. His interdisciplinary research merges games , machine learning , virtual production , and cultural heritage reinterpretation . He leads industry collaborations with entities like Jaguar Land Rover and Epic Games, focusing on AI-driven interactive audio, real-time visualization, and accessibility solutions. Award-winning projects : TIGA, Innovate UK, and Epic Games MegaGrant for Accession Industry partnerships : Automotive sector, cultural institutions His research spans human-computer interaction , multisensory virtual environments , and acoustic-visual cross-modal perception . Recent publications address robotic simulations, motion alignment, and haptic feedback systems. Scientific recognition : TIGA Award, Innovate UK Funding, Epic Games MegaGrant Advocacy : Digital inclusion, creative collaboration, social impact of technology

Johnny Goldingمشاهده پروفایل

استاد

• Contemporary Philosophy
• Art Theory
• New Materialisms
• +۳ مورد دیگر

Johnny Golding is a Professor at the Royal College of Art (RCA), School of Arts & Humanities. His career spans roles such as Director of the Centre for Fine Art Research at Birmingham City University, Professor of Philosophy in the Visual Arts & Communication Technologies (2000–2012), and honorary Professorship in Philosophy and Imaging at Dundee School of Art (2009). Born in New York, he holds a PhD from the Universities of Toronto and Cambridge. Education : - PhD in Philosophy from the Universities of Toronto and Cambridge. - Earlier studies in Toronto and New York. Research Interests : Golding’s work explores post-Newtonian analytics, new materialisms, and the erotics of sense as 'radical matter.' His interdisciplinary approach bridges art, philosophy, and 'wild sciences' like AI, robotics, and quantum theory. Key themes include data proliferation's societal impact, emergent systems, and the interplay between art and technology. Recent Articles & Projects : Focus on Data Loam (2020), exploring future knowledge systems through art and science collaborations. Recent works address radical empathy, distributed intelligence, and the ethics of AI. His 2018 opera Entanglement: The Opera and installations like Of The Thick and the Raw exemplify his practice-led philosophy. Grants & Leadership : - Led the Data Loam project (FWF-PEEK funded), involving over 20 artists and scholars. - PI for AiDesign Labs on generative AI at RCA. Labs & Collaborations : - Radical Matter Lab (2017–2018), a pedagogical experiment at RCA. - Collaborations with institutions like the University of Applied Arts Vienna and the British Library.

• Aerospace Composites
• Damage Tolerance Analysis
• Impact Mechanics
• +۳ مورد دیگر

Dr Andrew Rhead is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, specializing in aerospace composites and damage tolerance analysis. His research focuses on impact damage detection, failure mechanism modeling, and Non-Destructive Evaluation (NDE) techniques for composite structures. MSci in Mathematical Sciences (Dynamical Systems) - University of Bristol (2006) PhD in Composite Damage Tolerance - University of Bath (2009) His work develops computationally efficient analytical models for compression after impact (CAI) strength prediction in composite laminates, surpassing traditional finite element methods. Key projects include hydrogen storage systems for aircraft, cryogenic composite testing, and steered fiber manufacturing optimization. Active in 10 projects including ASPIRE and HyFIVE Collaborates with Airbus, GKN Aerospace, and EPSRC Research trends show emphasis on sustainable aviation materials, structural battery integration, and advanced testing methodologies. Current affiliations include the Institute for Mathematical Innovation (IMI) and Centre for Integrated Materials, Processes & Structures (IMPS).

Alison Powellمشاهده پروفایل

دانشیار

• Technology Design and Policy
• Public Sector Technology
• Digital Futures
• +۵ مورد دیگر

Dr Alison Powell is an Associate Professor in the Department of Media and Communications at the London School of Economics and Political Science (LSE), serving as Programme Director for the MSc Media and Communications (Data and Society). Her research focuses on technology design, public sector technology, and digital futures. She is known for her book Undoing Optimization: Civic Action in Smart Cities (2021) and her participatory research method, data walking. From 2019–2023, she directed the JUST AI network, supported by the Ada Lovelace Institute and UKRI, advancing AI ethics research. Her work integrates critical theory, participatory methods, and interdisciplinary collaboration. Education: PhD in Communication from Concordia University (Canada), MA in Media Studies from Toronto Metropolitan University, and postdoctoral research at the Oxford Internet Institute. Prior to academia, she worked in the film and TV industry. Research interests include civic engagement in data-driven governance, ethical AI, and participatory urbanism. She has advised projects like Africa Just AI and Operationalising Ethics for AI, funded by Horizon Europe, AHRC, and the Open Society Foundations. Her articles address topics such as AI governance, urban light ecology, feminist research praxis, and the ethical implications of technology for marginalized communities. She contributes to blogs like Media@LSE and leads initiatives at Polis and the LSE’s Digital Futures for Children project. Grants and collaborations include work with Projects by IF, Open Rights Group, and the Human Data Interactions Network (EPSRC). She explores intersections of technology, justice, and sustainability, emphasizing equitable and inclusive innovation.

Andrew Hudson-Smithمشاهده پروفایل

استاد

• Digital Urban Systems
• Smart Cities
• Internet of Things (IoT)
• +۷ مورد دیگر

Professor Andrew Hudson-Smith is the Director of the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London (UCL), where he holds the title of Professor of Digital Urban Systems. He leads UCL's academic and applied research in smart cities, digital twins, and urban informatics. His roles include Editor-in-Chief of the Future Internet Journal and academic lead for the Smart Queen Elizabeth Park project. He contributes to strategic initiatives such as the Greater London Authority Smart London Board and EPSRC Digital Economy Programme Advisory Board. Education: PhD (2003), MSc (1996) from UCL; BSc in Geography from the University of Plymouth (1992). Research focuses on digital urban systems, IoT applications, sustainable urban planning, and cyberphysical systems. Notable projects include urban heat island monitoring, participatory planning platforms, and metaverse-driven urban design. His work bridges technology, art, and public engagement, exemplified by initiatives like Tales of Things and the Haggle-O-Tron. Recent publications emphasize digital twins, metaverse urbanism, and IoT integration in urban environments. Awards include a Fellowship of the Royal Society of Arts. His work addresses SDGs 3 (Good Health) and 11 (Sustainable Cities), with a focus on equitable smart city development and public space innovation.

Heather Inwoodمشاهده پروفایل

دانشیار

• Contemporary Chinese literature
• Poetry studies
• Digital humanities
• +۵ مورد دیگر

Dr. Heather Inwood serves as University Associate Professor in Modern Chinese Literature and Culture within the Faculty of Asian and Middle Eastern Studies at the University of Cambridge. She is also a Fellow and Director of Studies at Trinity Hall, maintaining dual institutional affiliations that support her teaching and research activities across undergraduate and postgraduate programs. Her educational background includes a BA in Chinese Studies from the University of Cambridge (Trinity Hall), followed by advanced studies at Tsinghua University and Peking University, culminating in a PhD in modern Chinese literature from SOAS, University of London in 2008. Prior academic appointments include Assistant Professor at The Ohio State University (2008-2013) and Lecturer in Chinese Cultural Studies at the University of Manchester before returning to Cambridge in 2016. Professor Inwood's research program investigates the dynamic interactions between digital media and literary production in contemporary China, with particular focus on poetry communities, genre fiction, and transmedia storytelling. Her work bridges traditional literary analysis with digital humanities approaches, examining how online platforms transform authorship, reception, and cultural value. She has pioneered scholarship on internet poetry scenes, demonstrating their vitality despite public perceptions of poetry's decline in modern China. Her publication trajectory reveals a clear evolution from early work on poetry communities ( Verse Going Viral: China's New Media Scenes , 2014) toward broader investigations of digital narrative forms, game studies, and Sinophone cyberspace. Recent publications increasingly engage with science fiction, transmedia storytelling, and the algorithmic structures shaping literary production, reflecting both the changing digital landscape and her expanding methodological toolkit. Professor Inwood actively supervises five PhD students working on diverse projects spanning Misty poetry, queer narratives, gender studies, and poetic animality, demonstrating her commitment to nurturing next-generation scholarship in Chinese literary studies. Her research has been supported by British Academy Small Grants and similar funding mechanisms that enable sustained fieldwork and publication. Her teaching responsibilities include undergraduate courses on East Asian media and popular culture, Modern Chinese texts, and Modern Chinese literature, connecting classroom instruction directly to her research expertise. She also maintains public engagement through Chinese-language columns for BBC China and other media outlets, bridging academic and public discourse on contemporary Chinese culture.

Gabriel Brostowمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• Human-Centered AI
• +۶ مورد دیگر

Professor Gabriel Brostow is a faculty member in the Department of Computer Science at University College London (UCL), where he leads research in Computer Vision and Human-Computer Interaction. He also serves as Chief Research Scientist and Senior Director of the R&D Team at Niantic, the company behind Pokémon GO. His work bridges academic research and industry applications, focusing on developing AI systems that enhance human capabilities through what he terms 'Human in the Loop AI'—now commonly referred to as Human-Centered AI. Brostow completed his BS in Electrical Engineering at UT Austin, followed by a PhD with Irfan Essa at Georgia Tech. He then pursued postdoctoral research with Roberto Cipolla's Computer Vision & Robotics Group at Cambridge University as a Marshall Sherfield Fellow, and with Marc Pollefeys in ETH Zurich's CVG Group. His research explores how AI, particularly Computer Vision, can serve as 'super-tools' for professionals across various domains including filmmaking, architecture, robotics, and scientific research. Specific interests include assistive technology for everyday life, authoring systems that maximize user effort, 3D reconstruction, depth estimation, and vision-language models. His work often involves creating systems that are validated through real-world human interaction to ensure practical utility. Analysis of his recent publications reveals a strong focus on practical applications of Computer Vision that directly interact with humans. His research spans 3D scene understanding, depth estimation, sketch-based interfaces, and multimodal AI systems. There's a clear emphasis on creating benchmarks and tools that facilitate human-AI collaboration, with applications in assistive technology, urban planning, filmmaking, and biodiversity monitoring. His work frequently appears at top conferences including CVPR, NeurIPS, ECCV, and CHI. Marshall Sherfield Fellowship Brostow actively mentors PhD students, with current advisees including Ross Murphy, Skanda Koppula, Gizem Unlu, Omiros Pantazis, and Jamie Watson. His alumni include numerous PhD graduates and MSc students who have gone on to successful careers in academia and industry. He emphasizes selecting students based on passion and potential rather than just academic credentials, valuing traits like helpfulness, drive, and hunger to learn. His research is supported through collaborations with major institutions and companies including DeepMind, MIT, and the University of Edinburgh. He leads a research group at UCL that collaborates closely with Niantic's R&D team, creating a unique bridge between academic research and industry application. His team's work frequently involves developing novel Computer Vision techniques that are validated through real-world human interaction, ensuring practical utility alongside technical innovation. The group explores blue-sky research problems with applications ranging from assistive technology to professional tools for filmmakers, architects, and scientists studying diverse environments.