Petar Kormushev is a Senior Lecturer (Associate Professor) in Robotics at the Dyson School of Design Engineering, Imperial College London, and the founder/director of the Robot Intelligence Lab. He holds a PhD in Computational Intelligence from Tokyo Institute of Technology. His research focuses on robotics and machine learning, particularly reinforcement learning for autonomous robots. Key projects include the WALK-MAN humanoid robot for disaster response and contributions to the PANDORA and STIFF-FLOP EU projects. He has received the 2013 John Atanasoff Award for scientific excellence in ICT. His lab develops machine learning algorithms applied to humanoid robots like COMAN and iCub, with interests in robot learning, compliant control, and autonomous systems. He has supervised numerous PhD students and led research teams at IIT and Imperial College.
Felipe Meneguzzi is a Professor of Computing Science at the University of Aberdeen, where he leads research in automated planning, goal and plan recognition, multiagent systems, BDI agents, and machine learning. He also holds a Bridges Professorship at the Pontifical Catholic University of Rio Grande do Sul (PUCRS) in Brazil and leads the Group on Artificial Intelligence at PUCRS. He is a Senior Member of the ACM and AAAI. PhD in Artificial Intelligence (2009) from King's College London Postdoctoral Fellowship at Carnegie Mellon University His research spans theoretical and applied artificial intelligence, with a focus on automated planning, decision-making in autonomous agents, and AI applications in neuroscience. He has contributed to landmark-based methods in plan recognition, generalized decision-making in BDI agents, and clinical AI for autism spectrum disorder detection. Key publications include: Landmark-based approaches for goal recognition as planning (IJCAI 2024) Empowering BDI Agents with Generalised Decision-Making (AAMAS 2024) Identification of autism spectrum disorder using deep learning (Neuroimage: Clinical, 2017) Visually-impaired accessibility application via CNNs (IJCNN 2017) Norm conflict identification with deep learning (AAMAS 2017 workshop) Scientific honors include: Best SPC member at AAMAS 2021 Blue-Sky Paper award at AAMAS 2024 Google Research Awards for Latin America (2016, 2019) Runner-up for Microsoft Research Faculty Fellowship (2013) CNPq Highly Productive Researcher Fellowship (Brazil) As an advisor, he supervised Ramon Pereira's MSc dissertation and PhD thesis, both recognized as top works in Brazilian AI. He actively mentors students in automated planning, machine learning, and multiagent systems through projects like the final year project repository and the graduate student repository .
Brad Campbell is an Associate Professor in the Department of Computer Science and Electrical and Computer Engineering at the University of Virginia, where he is a member of the Link Lab, a cross-disciplinary research group focused on cyber-physical systems. His research centers on designing and building scalable, effective, and unobtrusive embedded systems for the Internet of Things, with applications in smart buildings, smart cities, and personal health. His work spans hardware design, networking, and cloud infrastructure, with a strong emphasis on energy-harvesting systems, low-power wireless communication, and resilient embedded operating systems. He has led projects such as the Living Link Lab, a heavily instrumented smart building testbed, and has developed open-source platforms for self-powered sensing and IoT ecosystems. His recent publications reflect a strong trend toward privacy-preserving federated learning, contactless occupancy sensing using WiFi and light, decentralized edge computing, and sustainable IoT systems. These works are published in top venues including SenSys, BuildSys, MobiCom, and IPSN, indicating a high impact in the systems and networking community. NSF CAREER Award (2022) Best Paper Award at DFHS’19 Multiple graduate fellowships and teaching awards for his students UVA Engineering Endowed Graduate Fellowships Link Lab Seminar Award CPS Rising Star recognition Brad Campbell has advised numerous PhD and master’s students, many of whom have gone on to academic and industry roles. He has secured significant research funding, including from the NSF, and has contributed to curriculum development in cyber-physical systems. He is actively involved in teaching courses on computer networking, IoT, and operating systems, and has co-taught wireless IoT courses across multiple institutions. His lab focuses on real-world deployment of IoT systems, emphasizing scalability, fault tolerance, and long-term sustainability. He continues to push the boundaries of what embedded systems can achieve in everyday environments, from homes to cities.
Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.
Professor Jason Dykes is a leading figure in the field of information and geovisualization at City, University of London, where he holds the position of Professor in the Department of Computer Science and co-directs the giCentre , a renowned research centre in visualization. He is affiliated with the School of Mathematics, Computer Science and Engineering and maintains an active research and teaching profile. His academic journey includes a PhD in Geography from the University of Leicester and extensive leadership in both research and education. Education: PhD in Geography, University of Leicester, 2000 MSc in Geographic Information Systems, University of Leicester, 1991 BA/MA in Geography, University of Oxford, 1989 Jason Dykes' research is centered on designing visual methods and tools for exploring, analyzing, and presenting information, with a strong emphasis on geographic data. His work integrates cartography, information visualization, GIScience, and human-computer interaction , leading to the development of innovative techniques such as geowigs, ODmaps, BallotMaps, and AttributeSignatures. He has published extensively in top-tier journals like IEEE Transactions on Visualization & Computer Graphics, with over 20 papers in the last decade, and co-authored the seminal book Exploring Geovisualization (2005). His research is supported by major funders including EPSRC and the EU, with projects like RAMP VIS (Covid-19 response) and VALCRI (criminal intelligence). The most recent articles highlight a consistent trend in applied and human-centered visualization , focusing on responsive design, education, pandemic modeling, and novel visual metaphors for complex data. His work increasingly emphasizes methodological rigor, design exposition, and the role of visualization in interdisciplinary and emergency contexts. Scientific Awards and Recognition: National Teaching Fellow, Higher Education Academy (2005) Best Paper Awards at GIS Research UK (consecutive years) Honorable Mentions, IEEE InfoVis (2009, 2010, 2016, 2018) Security Innovation Commercialisation Award (EU, 2022) Research Supervisor of the Year, City Student Union (2020) Innovations in Teaching Award and multiple teaching grants at City Jason Dykes has supervised eight PhD students to completion and advised many others, including notable researchers like Roger Beecham, Sarah Goodwin, and Susanne Bleisch. His teaching includes modules such as Visualizing Society and Data Presentation. He has received significant grant funding from UK research councils and the EU for projects like DIVA, VALCRI, and RAMP VIS. His service to the community includes leadership roles in IEEE VIS, ICA Commission on GeoVisualization, and editorial positions at IEEE TVCG and the Journal of Visualization and Interaction. He leads the giCentre , a dynamic research group that fosters innovation in visualization, and has been instrumental in establishing the field’s educational and methodological foundations through participation in Dagstuhl seminars and publications on visualization pedagogy.
Dr. Radu Jianu is a Lecturer in the Department of Computer Science at City, University of London , where he has been a faculty member since 2016. He is affiliated with the giCentre , a leading research group in information visualization. He earned his PhD and MSc in Computer Science from Brown University, USA, and a Diploma in Engineering from the Polytechnic University of Timisoara, Romania. His academic career includes a previous role as Assistant Professor at Florida International University (2012–2016). His research focuses on Data Visualisation, Visual Analytics, and Human-Computer Interaction . He conducts interdisciplinary collaborations with domains such as biology, food policy, and energy decarbonisation, aiming to develop interactive visual tools that enhance data understanding and decision-making. His methodological approach includes user studies, eye-tracking, and the design of novel visualization techniques. Dr. Jianu teaches Programming in Java and Cognition and Technologies , and he coordinates the Programming Bootcamp. He also holds administrative responsibilities as the Progression and Support Director in the Computer Science Department and is a member of its Executive Committee (ExCo). His recent publications reflect a growing interest in LLM-assisted visual analytics, gaze-aware systems, and collaborative human-AI analytical frameworks . He has published in top venues such as IEEE TVCG, CHI, EuroVis, and Nature Immunology, with several best paper awards. His work on the RAMPVIS project highlights his contributions to visualization in public health emergencies. Scientific Awards: Best Paper Award, Symposium on Graph Drawing (2018) Best Short Paper Award, EuroVis (2020) Advising and Grants: Dr. Jianu supervises multiple PhD and MSc students, including Dany Laksono (Energy Decarbonisation) and Maeve Hutchinson (NLP-mediated Visualization). His students have co-authored high-impact, award-winning papers. He has been involved in funded research initiatives such as RAMPVIS, which received support from UKRI/EPSRC for developing visual analytics infrastructure during the COVID-19 pandemic. Labs and Teams: He is an active member of the giCentre at City, University of London, a hub for visualization research. He also collaborates with interdisciplinary teams in epidemiology, immunology, and computer science, contributing to large-scale projects like the Immunological Genome Project and RAMPVIS.
Malvina Nissim is a leading researcher in computational linguistics and NLP at the University of Groningen's Department of Artificial Intelligence, with a focus on multilingual modeling, bias mitigation, and human evaluation frameworks. Key Contributions : Developed CALAMITA (Italian LLM benchmark), IT5 models for Italian language processing, and ReproHum framework for NLP evaluation reproducibility Research Pillars : Multilingual reasoning consistency, perspective-based text analysis, and figurative language modeling Her work spans activation steering techniques, cross-lingual transfer learning, and the creation of specialized language resources like the EurekaRebus dataset and MAGPIE idiom corpus. She pioneered methods for gender bias measurement in BERT and developed the SocioFillmore tool for perspective visualization. Recent publications explore model uncertainty as MCQ difficulty proxy, Italian headline generation benchmarks, and multilingual multi-figurative language detection. She actively participates in teaching initiatives like the "NLP with Bracelets" workshop for Italian high school students. Scientific Awards : ACL Best Paper Award (2025) EMNLP Outstanding Reviewer (2023) EVALITA Leadership Recognition (2024) She advises PhD students in model bias analysis and has contributed to the development of the Dutch Abusive Language Corpus (DALC) and the ReproNLP reproducibility framework. Her collaborations span institutions in Italy, Netherlands, and international NLP communities.
Professor Daniel Catchpoole serves as Deputy Head of School (Research) at the School of Computer Science, University of Technology Sydney (UTS), holding dual appointments at UTS and The Children's Hospital at Westmead. With over 20 years of research experience, he bridges computational sciences and pediatric cancer research through the Biomedical Data Science Lab in the Australian Artificial Intelligence Institute. His work integrates data analytics, artificial intelligence, and software development with molecular cancer biology to transform pediatric cancer treatment pathways. PhD in Cancer Cell Biology, University of New South Wales (1991-1995) Founding Fellow, Royal College of Pathologists Australasia (2010-present) Head, Children's Hospital at Westmead Tumour Bank (2001-present) Professor Catchpoole's research focuses on translational applications of genomics in childhood cancers, particularly acute lymphoblastic leukemia and neuroblastoma. His work combines high-throughput genomic technologies with advanced computational analysis to develop systems biology approaches for cancer patient assessment. Recent projects explore virtual reality applications for complex genomic data visualization and copper chelation therapies to enhance neuroblastoma immunotherapy. His research has received significant funding from Cancer Institute NSW, Sony Foundation, ARC, and NHMRC. His publication record spans biomedical data science, cancer genomics, and virtual reality applications in oncology. Recent work demonstrates leadership in 3D latent diffusion models for tumor segmentation, biobank economics, and innovative immunotherapies. His research consistently addresses the critical need for actionable knowledge from complex multidimensional biomedical data. Editorial Board Member, Cancers (2023) Associate Editor, Innovations in Digital Health, Diagnostics and Biomarkers (2019) Founding member and first President, Australasian Biospecimens Network Association Professor Catchpoole has supervised 17 Honours students (including 6 First Class Honours), 3 MSc students, and 12 PhD candidates across multiple institutions, with 6 current PhD students. His collaborative research bridges UTS's Faculty of Engineering and IT with The Children's Cancer Research Unit at The Children's Hospital at Westmead. Significant research funding includes Cancer Institute NSW grants, Sony Foundation VR projects, and ARC Discovery Projects focused on genomic data analysis and clinical decision support systems. His leadership extends to building frameworks for translational research, managing biobanks and clinical data linkages, and navigating governance requirements for cancer research. The Tumour Bank at Kids Research, CCRU, represents his long-standing commitment to pediatric cancer infrastructure development.
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Dr. Matteo Montecchi is a Senior Lecturer (Associate Professor) in Marketing at King’s Business School, King’s College London, where he also serves as Theme Lead for Sustainable Consumption at the Centre for Sustainable Business and Programme Director for the Strategic Marketing (Open Executive) programme. He teaches core modules such as Consumer Behaviour, Digital Marketing, and Research Methods, and leads executive education initiatives. Previously, he was a Senior Lecturer at the London College of Fashion, University of the Arts London, and has held visiting positions at Milan Politecnico, Università Cattolica del Sacro Cuore, and Università Federico II. Montecchi earned his PhD in Marketing from King’s College London, an MRes in Marketing from Birkbeck College, an Executive Master in Marketing and Sales from SDA Bocconi and ESADE, and a Bachelor’s in Business Economics from the University of Modena and Reggio Emilia. He also holds a PgCert in Academic Practice and is a Fellow of the Higher Education Academy (FHEA). His research focuses on the digital transformation of marketing, particularly the role of artificial intelligence and blockchain in enhancing transparency and trust. He investigates ethical engagement with diverse consumer groups, inclusion, and corporate responsibility, with a special interest in marginalized communities. His work integrates consumer behavior, digital interactions, and decision-making with technological innovation, offering actionable insights for sustainable and responsible business strategies. The most recent 15 publications reflect a strong trend in AI in retail, brand transparency, consumer trust, ethical data use, voice technologies, and social sustainability. His research spans journals in marketing, psychology, interactive marketing, and business ethics, demonstrating interdisciplinary impact. Scientific Awards: KingsCAT: Capture and Analysis Tool for Social Media Research at King’s College London (2024) – Recognized as part of a collaborative team for advancing digital research infrastructure and media analysis. Montecchi is actively involved in PhD supervision and is accepting new students. He has led research projects using social media analytics (KingsCAT) and has contributed to strategic debates on grand challenges in marketing. His work connects academic research with real-world managerial applications, particularly in digital strategy and ethical innovation. He is a key contributor to interdisciplinary research through tools like KingsCAT, which supports collaborative social media analysis, and his publications often involve co-authorship with experts in data science, psychology, and organizational behavior.
Merlin Seller is a Lecturer in Design and Screen Cultures at the University of Edinburgh's Edinburgh College of Art, appointed in 2019. They teach theory and historical/cultural context across Film, Comics, Media and Game Studies. Seller co-founded the Game Worlds research cluster within the Centre for Data, Culture and Society. Education: MA from St Andrews University MSt from Oxford University PhD from University of East Anglia (UEA) on transmedia works between film, photography and painting in interwar England Seller's research interests span Game Studies, Film Studies, Horror, Non-human theory, and Queer/Trans approaches to games. Their work explores (Post-)Phenomenology, visuality in games, and the representation of nonhuman entities in screen-based media. Seller identifies as a proudly pansexual and trans academic with a background in Art History and Visual Cultural Studies. Analysis of Seller's publications reveals a strong interdisciplinary focus bridging Game Studies with critical theory. Their work frequently examines the intersection of nonhuman perspectives, queer theory, and phenomenological experience in games and film. Recurring themes include temporal mechanics, ecological consciousness, and the materiality of digital interfaces, demonstrating a consistent engagement with contemporary theoretical frameworks in media studies. Seller supervises PhD students including Yun Lu, Trina Tian (Siyu), and Danni C. Pascuma. They also teach courses such as 'Design, Play and Games,' 'Contemporary Cinema,' and 'Introduction to Queer Studies,' while supervising Honours dissertations. Seller co-organized the 'Affecting Game Space' conference through the Game Worlds research cluster. Their creative practice includes plein air paintings of videogame environments and dark comedy comics focused on speculative futures, visible through their portfolio at dearplayer.org.
Professor Robert Eason is a leading academic at the University of Southampton, specializing in photonics and laser technology. His research spans interdisciplinary areas combining Machine Learning , Medical Diagnostics , and Microfluidics . Research Interests : Eason focuses on AI-driven laser applications, including deep learning for phototherapy , autonomous laser machining , and low-cost paper-based diagnostic devices . His work bridges photonics with biomedicine and advanced manufacturing. Recent Publications : His 2025 article in Scientific Reports explores AI simulations for psoriasis treatment, while 2024-2022 works address laser-controlled microfluidics, deep learning in microscopy, and reinforcement learning for laser machining. Supervision : He supervises PhD student Georgia Mourkioti in laser-based research projects. External Roles : Eason has served as a speaker at international conferences including the International Symposium on Laser Precision Microfabrication (2018), LAISER (2019), and Deep Learning for Control of Light-Matter Interactions (2022).
Sumit Chopra is an Associate Professor at the Grossman School of Medicine , affiliated with the Department of Radiology at New York University. His work focuses on integrating machine learning and artificial intelligence with medical imaging to enhance diagnostic accuracy and clinical decision-making. Research interests include: Deep learning applications in prostate cancer imaging and MRI reconstruction Development of open-access medical imaging datasets (e.g., FastMRI Prostate) Improving biopsy decision strategies via representation learning AI-driven Alzheimer's disease risk prediction using electronic health records Advancements in radiologic assessment for pancreatic cystic lesions Email: Sumit.Chopra@nyulangone.org
Kristian J. Hammond is the Bill and Cathy Osborn Professor of Computer Science at Northwestern University's McCormick School of Engineering. He directs both the Master of Science in Artificial Intelligence Program and the Center for Advancing Safety of Machine Intelligence (CASMI). His research focuses on artificial intelligence, natural language generation, narrative generation, conversational interfaces, and ethical AI applications across domains like law, education, and journalism. Hammond co-founded Narrative Science, leveraging AI for automated journalism from data. Education: PhD, MS, and BA in Philosophy (all from Yale University). His work spans technical innovation and societal impact, with notable contributions to AI transparency, bias mitigation, and machine learning ethics. Hammond has authored influential articles on AI governance, conversational systems, and the future of work in an automated economy. His leadership roles emphasize interdisciplinary collaboration between computer science, business, and humanities. Research highlights include developing AI systems that enhance human capabilities, exploring ethical frameworks for machine intelligence, and advancing AI safety through initiatives like CASMI. He frequently engages in public discourse via TEDx talks and commentaries on AI's societal implications, emphasizing the need for human-centered technology design.
Dr. Debraj Roy is a Visiting Professor at the University of Amsterdam (UvA), affiliated with the Faculty of Science, Mathematics and Computer Science and the Informatics Institute. His research focuses on agent-based modeling, socio-economic dynamics, environmental resilience, and blockchain technology. He investigates complex systems such as urban slums, disaster recovery, and climate adaptation using computational methods like remote sensing and machine learning. His work bridges theory and practice, offering insights into policy design for sustainable development and social equity. Key research interests include slum dynamics, poverty traps, and the application of blockchain oracles for decentralized systems. He employs advanced techniques such as global sensitivity analysis and manifold learning to explore multi-scale socio-environmental challenges. His recent articles highlight trends in carbon pricing, flood risk valuation, and multi-agent systems. Earlier work concentrated on urban inequality in cities like Bangalore and Mexico City, leveraging geospatial and statistical tools. No scientific awards or grants are explicitly listed. His advising and team collaborations are unspecified in the provided text.
/prod01/channel_3/media/migration/research-groups/Petar-Kormushev--tojpeg_1463870974521_x4.jpg)
