Find Academic Supervisors

• Software Engineering
• Web Engineering
• Model-Driven Engineering
• +7 more

Luca Mainetti is a Full Professor in the Department of Innovation Engineering at the University of Salento, where he leads the GSA Lab (Graphics and Software Architectures Lab) and founded the Mobile and Multi-Device Applications research group. He has been a key figure in advancing software and web engineering, particularly in model-driven approaches for IoT and service-oriented systems. His research interests include: Software Engineering Web Engineering Model-Driven Engineering for middleware and IoT Service-Oriented Architectures Embedded and mobile applications His recent publications reflect a strong trend toward model-driven development of IoT systems, integration platforms like WoX, and academic entrepreneurship through spin-offs such as VidyaSoft and SofThings. These works emphasize software architecture, automation, and real-world application in domains like FinTech and CRM. Scientific recognitions include: Senior Member of the ACM Member of IEEE Luca Mainetti has supervised over ten doctoral and post-doctoral researchers and coordinated the Doctoral School in Information Engineering from 2012 to 2017. He has held leadership roles including Vice-Director of the Department of Innovation Engineering and Rector’s Representative for the Digital Agenda. He also coordinates the National Technical Committee for Digital University under MIUR, highlighting his influence in national academic ICT policy. He is actively involved in research labs and innovation initiatives, including: GSA Lab – Graphics and Software Architectures Lab (Scientific Director since 2007) IDA Lab – IDentification Automation Lab (Scientific Director, 2008–2016) Spin-off leadership in VidyaSoft and SofThings

Jack JewsonView profile

Senior Lecturer

• Bayesian Inference
• Model Misspecification
• Robust Statistics
• +7 more

Jack Jewson is a Senior Lecturer in the Department of Econometrics and Business Statistics at Monash University’s Faculty of Business and Economics, a position he has held since April 2024. He previously conducted postdoctoral research and held a Juan de la Cierva Research Fellowship at Universitat Pompeu Fabra, Barcelona. He is actively accepting PhD students and supervising research in advanced statistical methodologies. Education: PhD in Statistics, University of Warwick (awarded June 2020), in collaboration with the University of Oxford via the Oxford-Warwick Statistics Programme (OxWaSP). Integrated Master’s in Mathematics, Operational Research, Statistics, and Economics, University of Warwick (awarded July 2015). His research focuses on Bayesian inference under model misspecification, particularly in the M-open world, where no true model is assumed to exist. He develops robust computational methods for variable and model selection, and investigates statistical inference under differential privacy constraints. His work integrates loss functions into Bayesian updating and explores graphical and structural modeling applications in economics and biology. These interests are driven by the need for reliable inference in complex, real-world scenarios where models are inherently imperfect. His recent publications span high-impact journals such as The Annals of Applied Statistics , Biometrics , and Bayesian Analysis , as well as top machine learning venues like NeurIPS. The research demonstrates a strong trend toward robust, privacy-aware Bayesian methods with applications in biostatistics, signal processing, and network modeling. His work bridges theoretical statistics with practical computational solutions for modern data challenges. Scientific Awards: No specific awards or fellowships mentioned in the provided text. Jack Jewson has not received explicit mention of grants or funding in the text, but his prior Juan de la Cierva Fellowship indicates competitive research support. He is actively mentoring PhD students and expanding his research group at Monash. His work involves collaboration with leading statisticians such as David Rossell, Piotr Zwiernik, Jim Q. Smith, and Chris Holmes. While no formal lab name is provided, his research group focuses on robust Bayesian computation and privacy-preserving inference.

John FergusonView profile

Associate Professor

• Electronic Music
• Digital Fabrication
• Interactive Multimedia Systems
• +5 more

Associate Professor John Ferguson is a post-digital/electronic musician and sound artist at Queensland Conservatorium, Griffith University since 2015, currently serving as Head of Creative Music Technology . He has held academic positions at Brown University (Visiting Assistant Professor) and Kingston University London (Lecturer). His Ph.D. from Newcastle University (2010) focused on artistic methods in digital media and redefining live musicianship. Current ARC Discovery Project (DP240100680) on regional digital music ecosystems Founded Interactive Media Lab collaborations Expertise in Pure Data, Arduino, Touch Designer for custom instruments Research explores post-digital systems blending tactile interaction with generative audio-visual environments. Supervises PhD/DMA students in topics like AI collaboration, sonic identity, and redundant technology repurposing. Grants include Queensland Museum , Australia Council for the Arts , and Griffith University internal funding for media architecture projects.

Saptarshi DebroyView profile

Associate Professor

• Distributed Systems
• Cloud Computing
• Edge Computing
• +6 more

Dr. Saptarshi Debroy is an Associate Professor of Computer Science at Hunter College, City University of New York (CUNY), and a member of the Doctoral Faculties at The Graduate Center, CUNY. He founded and directs the Distributed Systems and Security (DiSSect) Laboratory and is affiliated with the Computer Simulation, Stochastic Modeling and Optimization (CoSSMO) Laboratory. Previously, he served as Assistant Professor at CUNY (2016-2024) and Postdoctoral Fellow at the University of Missouri (2014-2016). Education: Ph.D. in Computer Engineering, University of Central Florida (2014) Master of Technology, Jadavpur University, India (2008) Bachelor of Technology, Institute of Engineering and Management, West Bengal University of Technology (2006) Research focuses on distributed systems innovation with emphasis on: Distributed Computing & Data Science : Resilient management of distributed systems, AI/ML for resource provisioning, IoT/CPS applications Usable Cyber Security : End-to-end security assurance, trustworthy edge/cloud computing, SDN vulnerability analysis Core methodologies include software-defined networking, deep learning algorithms, and federated system architectures for disaster response and scientific workflows. Publication analysis reveals strong emphasis on edge computing optimizations (67% of recent works), cybersecurity innovations (22%), and AI/ML integration (11%). Dominant trends include latency-quality tradeoffs in real-time systems, DNN inference optimization, and moving target defense strategies, with applications spanning disaster response, healthcare, and scientific computing. Scientific Awards & Honors: NSF CAREER Award 2020 (Cyber-Physical Systems) Best Paper Award, IEEE PIMRC 2011 Jadavpur University Gold Medal 2008 National Scholarship Merit Certificate (2000, 2002) 3 NSF Travel Grants, 2 IEEE Comsoc Travel Grants Advises 8 PhD students in cloud/edge computing and cybersecurity. Secured $2.37M+ in research funding as PI, including: NSF CAREER: Resilient Fog Framework for Disaster Response ($523K) NSF CICI: Trusted Volunteer Edge-Cloud Workflows ($600K) Google Research: DNN Model Extraction Threats ($100K) NSF: Health Incident-Response Framework ($612K) Leads the DiSSect Lab focusing on distributed systems security and co-directs the CoSSMO Lab. Research collaborations include FDNY for disaster response systems and Lawrence Berkeley National Lab through Sustainable Research Pathways.

Ronan BoulicView profile

Researcher

• Virtual Reality
• Human-Computer Interaction
• Computer Graphics
• +10 more

Ronan Boulic is a Senior Researcher at the École Polytechnique Fédérale de Lausanne (EPFL) within the School of Computer and Communication Sciences. He leads the Immersive Interaction (IIG) research group and serves as a Senior Scientist in multiple departments including IC-SIN, IC-SSC, and GR-SCI-IC. His work focuses on motion synthesis for virtual humans and robots, human movement modeling, inverse kinematics, and immersive 3D interactions in virtual environments, with applications in virtual prototyping, gaming, ergonomics, and biomedical simulations. PhD in Computer Science (1986) from University of Rennes, France Habilitation (1995) from University of Grenoble, France Research interests include: Embodiment in Virtual Reality Human Movement Modeling and Optimization Motion Capture and Real-Time 3D Interaction Avatar Emotion Expression and Synchronization Cybersickness Detection and Mitigation Collision Detection and Inverse Kinematics His recent publications (2023-2025) emphasize cybersickness frameworks, avatar embodiment, and real-time motion control. He has supervised over 15 PhD candidates, including Nana Tian (2023) and Thibault Porssut (2021), and collaborates with the EPFL Cognitive Neuroscience Laboratory (LNCO). Teaching includes foundational Computer Science (ICC), Programming, and Software Engineering to first-year students. He is also a member of the PhD program committee for Robotics, Control, and Intelligent Systems at EPFL.

• Human-Computer Interaction
• Sustainable HCI
• Participatory Design
• +10 more

Dr. Tshering Dema is a Senior Research Fellow in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. She is an early-career researcher specializing in Sustainable Human-Computer Interaction (HCI) and environmental conservation design, with a focus on co-designing technologies with children and remote communities to foster nature engagement and sustainability. Research Interests: Human-Computer Interaction (HCI) Participatory and Co-Design Interaction Design for Children Ubiquitous Computing in Natural Environments Socio-technical Systems for Conservation Acoustic Monitoring of Endangered Species Digital Technologies in Early Childhood Education Her research integrates qualitative methods from HCI to understand how digital technologies can nurture love and care for nature among young children in early childhood centers. She is currently involved in the QUT research project ‘Engaging the Digital Child with the Wonders of Nature, e-Science and the Outdoors’. Recent Research Trends: Her recent publications highlight a strong interdisciplinary focus, combining computer science with environmental conservation and child development. Key themes include the use of digital games and IoT devices (like ambient birdhouses) to enhance children’s connection with nature, participatory sensing in remote communities for species conservation, and the application of acoustic data and visual analytics for monitoring endangered birds such as the white-bellied heron in Bhutan. Scientific Affiliations: Design Participation Lab, QUT QUT Alumnus (PhD) Advising and Grants: While specific students and grants are not listed, her collaborative research with senior academics like Prof. Margot Brereton and Prof. Paul Roe suggests active involvement in research teams and likely mentorship roles. Her work is supported through institutional research projects and interdisciplinary collaborations focused on sustainability and technology design. Labs and Teams: Dr. Dema is a key member of the Design Participation Lab at QUT, a research group dedicated to participatory and human-centered design for social and environmental challenges. Her work exemplifies the lab’s mission through community-engaged, design-driven solutions for conservation and education.

Edith TretschkView profile

Researcher

• Computer Graphics
• Computer Vision
• Machine Learning
• +5 more

Edith Tretschk is a Research Scientist at Meta Reality Labs Research in the San Francisco Bay Area. She completed her Ph.D. in Computer Science at Saarland University and Max Planck Institute for Informatics (2018-2023), advised by Christian Theobalt . Her work bridges computer graphics , computer vision , and machine learning , with a focus on 3D reconstruction and quantum computing applications. Education Ph.D. in Computer Science (2018-2023), Max Planck Institute for Informatics & Saarland University M.Sc. in Computer Science (2017-2023), Graduate School of Computer Science, Saarland University B.Sc. in Computer Science (2014-2017), Saarland University Research Focus Her research explores 3D reconstruction of dynamic scenes, neural rendering , and quantum computing for vision tasks. Recent work includes time-consistent scene flow (SceNeRFlow), quantum auto-encoders (3D-QAE), and physics-driven template matching (φ-SfT). Article Trends Her publications span 3D vision , quantum algorithms , and neural scene modeling . Key themes include non-rigid deformation, quantum-hybrid approaches, and physics-based reconstruction. Scientific Recognition Bachelor Award (2017) for top CS graduates Deutschlandstipendium scholarship (2015-2017) NeurIPS Top Reviewer (2022) Additional Contributions She has delivered invited talks at World Labs, Meta, Nvidia, and Epic Games. Active as a reviewer for CVPR, ECCV, ICCV, and NeurIPS, she has also contributed to open-source projects and datasets.

Darren CoskerView profile

Professor

• Computer Graphics
• Animation
• Computer Vision
• +7 more

Darren Cosker is a Professor in the Department of Computer Science at the University of Bath, where he holds multiple significant affiliations including the Centre for the Analysis of Motion, Entertainment Research & Applications (CAMERA), the UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI, Visual Computing research group, and the Bath Institute for the Augmented Human. His office is located at 1 WEST 4.04 and he maintains an active research profile with over 100 research outputs and 20 supervised works. Professor Cosker's research interests focus on the convergence of Computer Graphics, Animation, Computer Vision and Psychology . He is particularly interested in applying these fields to the development of virtual humans, human realistic facial animation, motion planning, and behavioural modelling. His work spans both theoretical and applied domains, with strong connections to UN Sustainable Development Goals. His research fingerprint shows significant activity in Motion Capture (100%), Computer Vision (77%), Facial Animation (52%), and related fields including Biomechanics and Deep Learning. His recent publications demonstrate a clear trend toward markerless motion capture systems, virtual human representation, and the intersection of AI with human behavior analysis. The research spans applications from canine motion analysis to facial emotion recognition, with increasing focus on practical implementations in virtual reality and clinical settings. His work shows strong interdisciplinary connections between computer science, psychology, and biomechanics. Professor Cosker has secured substantial research funding as Principal Investigator on multiple projects including the My World Strength in Places Fund (2021-2027), CAMERA 2.0 (2020-2025), CAMERA MC2 Award (2019-2023), and several others focused on facial emotion perception and medical applications like the Rheumatoid Arthritis Flare Up Profiler. These projects demonstrate his ability to secure funding from diverse sources including Innovate UK, EPSRC, EU Horizon 2020, and the Medical Research Council. He leads several major research initiatives, most notably as co-director of CAMERA (Centre for the Analysis of Motion, Entertainment Research & Applications), which serves as a hub for interdisciplinary research connecting computer vision, graphics, and biomechanics with applications in entertainment, healthcare, and sports science. His work bridges the gap between theoretical computer science and practical applications in multiple domains.

Axel BerndtView profile

Professor

• Music Informatics
• Human-Technology Interaction
• Sound Processing
• +7 more

Professor Axel Berndt is a faculty member at the University of Paderborn, where he is affiliated with the Musicology Seminar Detmold/Paderborn, the Center for Music, Edition, Media (ZenMEM), and the KreativInstitut.OWL. His expertise lies at the intersection of computer science and music, with a focus on music informatics and digital media applications. University of Paderborn Musicology Seminar Detmold/Paderborn Center for Music, Edition, Media (ZenMEM) KreativInstitut.OWL Dr. Berndt studied computer science with a minor in music at Otto-von-Guericke University in Magdeburg. He conducted research and teaching in music informatics at the Department of Simulation and Graphics, earning his PhD in 2011. From 2012 to 2015, he worked at the Faculty of Computer Science at Technische Universität Dresden. From 2015 to 2023, he was a member of the Center for Music and Film Informatics in Detmold. Since 2023, he has been with the University of Paderborn. Professor Berndt's research focuses on the innovative potential of music informatics, exploring how digital tools and data formats enrich creative work with sound and music. His work bridges disciplines including human-technology interaction, musicology, and application domains such as the games industry, organ building, and museum technology. He investigates how digital media enable new approaches to sound and music, even for non-experts, with particular interest in interactive systems, music performance analysis, and digital music editions. His research emphasizes the practical application of theoretical concepts through immediate interdisciplinary exchange. His recent publications demonstrate a strong focus on music technology applications, with particular emphasis on music performance markup, interactive music systems, and digital tools for musicians. A recurring theme across his work is the intersection of traditional musicology with modern computational approaches, especially in the areas of music notation, performance analysis, and digital music editions. His research spans from practical implementations like the Detmold musical Instrument Timbre Explorer (DmITE) to theoretical explorations of music performance description. Digitale Interpretationsedition project Interactive Digital Scores in Music Theatre KreativInstitut.OWL Professor Berndt is actively involved in teaching individual BA/MA projects focused on sound and music in various media contexts and application domains. His approach emphasizes hands-on experience and collaboration with institutions like the Technische Hochschule OWL and the Hochschule für Musik Detmold, as well as partnerships with industry and application domains. His work demonstrates a commitment to translating research into practical applications through immediate interdisciplinary exchange. He maintains active research collaborations that bridge academic disciplines and application domains, ensuring his work remains relevant to both theoretical advancements and practical implementations in music technology and informatics.

Hande AlemdarView profile

Assistant Professor

• Machine Learning
• Data Science
• Big Data Analytics
• +6 more

Hande Alemdar is an Assistant Professor at the Department of Computer Engineering, Middle East Technical University, specializing in machine learning, data science, and big data analytics. She earned her BSc, MSc, and PhD in Computer Engineering from Boğaziçi University in 2004, 2009, and 2015, respectively, with her PhD thesis awarded the Bogazici University Research Fund (BAP) Best Thesis Award. PhD in Computer Engineering (2015), Boğaziçi University MSc in Computer Engineering (2009), Boğaziçi University BSc in Computer Engineering (2004), Boğaziçi University Her research focuses on applying machine learning to resource-efficient hardware, wireless sensor networks, and smart environments. She has pioneered work on ternary neural networks for FPGA-based AI, which reduce computational costs while maintaining accuracy. Her work spans diverse applications like activity recognition, fall detection, and sports analytics. Her recent publications reflect trends in deep learning for hardware efficiency, smart healthcare via ambient sensors, and network security with machine learning. These studies often integrate multi-modal sensor fusion and real-time data analysis , emphasizing deployability in resource-constrained scenarios. Scientific Awards Bogazici University BAP Best Thesis Award Hande has collaborated with Grenoble Informatics Institute and industry leaders like ST Microelectronics on energy-efficient AI. Her work has been published in journals and conferences such as Sensors, Computers & Graphics, and FPL, addressing topics from elite football performance analysis to covert channel detection in SDN. She leads research in scalable architectures for smart environments and is involved in the H2020 FET Project 'ROBOtic Replicants for Optimizing the Yield by Augmenting Living Ecosystems', demonstrating her commitment to interdisciplinary AI applications.

• Computer Graphics
• Computer Vision
• Machine Learning
• +2 more

Mark Boss, M.Sc., serves as a Lecturer at the Wilhelm Schickard Institute for Computer Science at the University of Tübingen. His academic appointment focuses on the Computer Graphics department where he delivers specialized instruction in visual computing disciplines. His research interests center on Computer Graphics with strong emphasis on Computer Vision and Machine Learning applications. His expertise extends to Special Effects production and Computer Games development, reflecting a practical orientation toward real-time rendering systems and interactive visual technologies. His work bridges theoretical foundations with industry applications in digital content creation. During the Winter Semester 2019/20, he taught multiple advanced courses including Graphics, Computer Vision and Machine Learning (INF3153), Computer Graphics (INFO4167), and Advanced Topics in Computer Graphics and Computer Vision (INFO4168), demonstrating comprehensive coverage of the visual computing pipeline from fundamentals to specialized applications.

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +5 more

Andreas Geiger is Professor and Head of the Department of Computer Science at the University of Tübingen, Germany, where he leads the Autonomous Vision Group (AVG) within CyberValley. He serves as core faculty at the Tübingen AI Center, Principal Investigator in the Excellence Cluster ML in Science and CRC Robust Vision, and ELLIS fellow coordinating the ELLIS PhD program. Prof. Geiger's research centers on machine learning for computer vision, natural language processing, and robotics, with emphasis on 2D/3D scene representations, geometry reconstruction, and robust model development. His group pioneers neural rendering techniques like Gaussian splatting while addressing real-world challenges in autonomous driving, VR/AR, and scientific document analysis through discriminative and generative approaches. Recent publications (2025) demonstrate strong focus on 3D scene understanding using Gaussian splatting, autonomous driving simulation with world models like ReSim and Vista, and generative methods for controllable 3D scenes. The group maintains Scholar Inbox for personalized academic recommendations while advancing reinforcement learning for self-driving (CaRL) and robust perception evaluation (EMPERROR). Major recognitions include: Best Paper Awards at CVPR 2024/2021, 3DV 2017/2015, GCPR 2015 Sage 10-Year Impact Award 2024 and Longuet-Higgins Prize 2022 ERC Starting Grant 2019 and IEEE PAMI Young Researcher Award 2018 nuPlan Challenge Winner 2023 and German Pattern Recognition Prize 2017 Prof. Geiger actively supervises PhD students including Reiser (3D view synthesis), Baur (Lidar scene flow), Jaeger (reinforcement learning), and Liao (urban scene transfer). His group secures substantial funding through the ERC Starting Grant, Vector Stiftung's MINT Innovation Program, ML in Science Cluster, and CRC Robust Vision, while collaborating with industry via Waymo and nuPlan challenges. The Autonomous Vision Group operates from CyberValley's new campus building with a diverse international team (12+ nationalities). They maintain Scholar Inbox for academic discovery and organize regular technical retreats and unique team-building activities like deep cave expeditions, fostering innovation in 3D vision and autonomous systems.

• Video Games Technology
• Computer Graphics
• Real-time Rendering
• +5 more

Kenny Mitchell is a part-time Full Professor of Video Games Technology at Edinburgh Napier University, concurrently serving as part-time CTO for 3Finery Ltd and Cobra Simulation Ltd while leading the European-funded CAROUSEL project. His career bridges high-impact industry roles including Roblox (where he directed rendering features for 70m+ daily users contributing to $40Bn valuation), Disney (founding Disney Research UK and collaborating with ILM London on Star Wars digital acting), and Electronic Arts (developing game engines for Harry Potter and BAFTA-winning Boom Blox). Education: Honors Degree in Computer Science and Artificial Intelligence, University of Edinburgh Mitchell's research centers on real-time photorealism, extended reality social systems, and generative AI graphics. Key focus areas include Intermediated Reality (MagiPeeps, LisNav), conversational AI avatars, VoxSpars technology for digital twins, and low-latency interaction systems like the CAROUSEL project. He investigates scalable delivery of immersive 3D experiences to mass audiences through practical industry applications. Professional Recognition: Holding approximately 50 patents and 100+ technical publications, Mitchell serves as Editor-in-Chief of ACM GAMES: Research and Practice, Associate Editor for PACMCGIT and Elsevier Computers and Graphics, and member of the ACM SIGGRAPH Conference Advisory Group. His Boom Blox development earned a BAFTA award while Roblox leadership achieved unprecedented commercial scale. Research Funding: As consortium lead for the European FET Pathfinder CAROUSEL project, Mitchell directs significant public research investment. His industry positions at Roblox, Disney, and EA generated substantial commercial R&D funding, with Roblox alone reaching $40Bn valuation through his rendering innovations. Academic mentoring occurs through Edinburgh Napier University's part-time faculty role. Labs and Teams: Mitchell co-founded 3Finery Ltd (Edinburgh Napier spinout) developing Intermediated Reality applications, and serves as CTO of Cobra Simulation Ltd advancing immersive hardware/VoxSpars. He leads the CAROUSEL consortium while previously directing Roblox's rendering team, Disney Research UK, and EA's game engine division for major franchises.

Dmitry VetrovView profile

Professor

• Bayesian Deep Learning
• Diffusion Models
• Loss Landscape Analysis
• +5 more

Dmitry Vetrov serves as a Professor of Computer Science at Constructor University in Bremen, where he founded and leads the Bayesian Methods Research Group. His academic foundation includes graduation from Moscow State University in 2003 and completion of his PhD in 2006, establishing a career centered on advancing probabilistic machine learning methodologies. His educational trajectory features: Undergraduate studies at Moscow State University (2003) Doctoral degree (PhD, 2006) Vetrov's research program critically bridges Bayesian statistics with deep learning architectures, with his group pioneering efficient diffusion model algorithms, loss landscape characterization in neural networks, scalable stochastic optimization tools, tensor decomposition applications for large-scale ML systems, and enhanced conditional text generation frameworks. This work manifests practical implementations across generative AI domains while maintaining theoretical rigor in probabilistic modeling. Analysis of his 2024-2025 publications reveals a concentrated research thrust toward diffusion model innovation, spanning text generation (token embedding smoothing, language model encoding properties), image synthesis (hair transfer, gesture generation), and scientific applications (protein modeling, genetic fine-mapping). Key thematic threads include sampler acceleration, theoretical property analysis of diffusion processes, and robust evaluation frameworks for generative systems. No scientific awards were documented in the source materials. Mentorship outcomes demonstrate significant impact, with three recent PhD students securing research positions at DeepMind. While specific grant details remain undisclosed, the group's prolific output across NeurIPS, ICML, and CVPR indicates sustained research funding. The Bayesian Methods Research Group operates as an integrated innovation hub within Constructor University's academic ecosystem. The research collective he directs maintains active development of Bayesian-deep learning fusion techniques, with current projects emphasizing diffusion model efficiency, theoretical foundations of optimization landscapes, and cross-domain applications in computational biology and multimodal generation.

• Medical Imaging
• Machine Learning
• Real-Time Computing
• +7 more

Professor Bernhard Kainz is a leading academic in the Department of Computing at Imperial College London and Professor at Friedrich-Alexander-University Erlangen-Nuremberg. He heads the Image Data Exploration and Analysis Lab (IDEA Lab) and co-leads the Biomedical Image Analysis (BioMedIA) group , focusing on human-in-the-loop computing for healthcare applications. His research develops intelligent algorithms for multi-modal healthcare , emphasizing generative and discriminative machine learning methods to enhance diagnostic decision-making and provide real-time guidance during medical procedures. Current projects address democratizing rare healthcare expertise through AI, normative learning for human-like data analysis, and interpretable medical machine learning. Co-founder of Fraiya Ltd. for medical AI solutions Scientific advisor to ThinkSono Ltd. Leader in EPSRC Centre for Doctoral Training in Smart Medical Imaging and UKRI AI for Healthcare CDT He has received numerous accolades including MICCAI best paper awards, IEEE TMI Distinguished Reviewer status, and Imperial President’s Research Team Award. His team's work spans fetal imaging , cardiac ultrasound , digital pathology , and AI explainability in healthcare.