Professor Emma Rich is affiliated with the University of Bath as a Professor of Physical Activity and Health Pedagogy and Director of the SPHERE Research Centre (Centre for Sport, Physical Activity and Health Equality). Her work bridges sociology and education , focusing on intersections between digital health technologies , body politics , and health inequities in educational and sport contexts. University: University of Bath Role: Professor & Research Centre Director Research Interests : Emma’s expertise spans critical pedagogy , digital health studies , obesity policy critique , and gendered body narratives . She pioneers feminist new materialist approaches to analyze how digital platforms shape health identities and practices among youth. Recent Publications examine digital health’s impact on body dissatisfaction , teacher mind maps , and spatial dynamics in digitized health education. These works emphasize datafication and quantified self trends in adolescent health behaviors. Awards & Recognition : Elected Fellow of the Academy of Social Sciences (2022) Nominated for FSHI Book Prize (2024) Bristol Bath Healthcare Research Impact Award (2019) Leadership & Collaborations : She leads international projects like the Wellcome Trust-funded Digital Health Generation and DigiHealthPE (UNA Europa), collaborating with institutions across the UK, Australia, and New Zealand. Her work integrates UN Sustainable Development Goals , particularly those addressing health equity and digital inclusion .
Magnus Bakke Botnan is an Assistant Professor at the Department of Mathematics, Vrije Universiteit Amsterdam, holding a VIDI career grant (€850,000) since 2018. His research bridges pure and applied mathematics within topological data analysis (TDA), focusing on multiparameter persistence, computational topology, and applications to sciences. PhD in Mathematics, Norwegian University of Science and Technology (NTNU), 2015 Postdoc at TU Munich, 2016-2018 His research group includes postdocs Hannah Rocio Santa Cruz Baur and Rui Dong, and PhD student Enes Devecioğlu. Recent work involves signed barcodes, rank decompositions, and stability of persistence modules. He co-authored the first comprehensive tutorial on multiparameter persistence with Mike Lesnick. Notable contributions include proving the NP-hardness of computing interleaving distance, establishing universality of bottleneck distance for extended persistence diagrams, and developing computational methods for non-branching complexes. Publications span journals like Foundations of Computational Mathematics , Discrete & Computational Geometry , and conferences SoCG, NeurIPS, and ICRA. Scientific Awards: VIDI Career Grant (€850,000) He has taught courses including Complex Analysis, Calculus, Topological Data Analysis, and seminars on analysis and dynamical systems. Actively organizes Applied Topology Days and collaborates on projects integrating TDA with physics, computer science, and statistics.
Prof. Torsten Wolfgang Kuhlen serves as a Universitätsprofessor at RWTH Aachen University, leading the Teaching and Research Area for Virtual Reality and Immersive Visualization within the Department of Computer Science. He is affiliated with Chair of Computer Science 12 (High Performance Computing), the Visual Computing Institute, and remains an integral part of the RWTH IT Center where his research group operates one of the world's largest Virtual Reality laboratories including the 30 sqm aixCAVE visualization chamber. The group maintains strong connections with Computational Science & Engineering Division, National High Performance Computing Center for Computational Engineering Science (NHR4CES), and VR in Science and Industry Network NRW e.V. Prof. Kuhlen's research spans virtual reality, immersive visualization, and multimodal 3D user interfaces with applications across simulation science, production technology, neuroscience, and medicine. His work combines basic research on advanced methods and algorithms with interdisciplinary collaborations involving RWTH Aachen institutes, Forschungszentrum Jülich, and industry partners. Recent publications demonstrate strong focus on audiovisual perception, immersive analytics, collaborative virtual environments, and practical VR applications in education and manufacturing. His research group has produced significant work on listening effort in virtual environments, immersive authoring techniques, and VR applications for scientific visualization. Notable projects include VRScenarioBuilder for automated vehicle testing and applications in monitoring additive manufacturing processes. The group actively participates in major conferences including IEEE VIS and EuroVis, with several award-winning contributions. Prof. Kuhlen has advised PhD students including Martin Bellgardt who recently completed his doctoral degree on "Increasing Immersion in Machine Learning Pipelines for Mechanical Engineering". The research group maintains state-of-the-art VR infrastructure including the aixCAVE facility which is open to all RWTH research groups.
Bruno Takahashi is the Brandt Endowed Professor of Environmental Communication at Michigan State University, holding a joint appointment in the School of Journalism and AgBioResearch. He serves as Research Director of the Knight Center for Environmental Journalism and maintains affiliations with the Health and Risk Communication Center, the Environmental Science and Policy Program, and the Center for Latin American and Caribbean Studies at MSU. Born and raised in Lima, Peru, Dr. Takahashi earned his bachelor's degree in communication from Universidad de Lima, followed by M.S. and Ph.D. degrees in Environmental Science from SUNY ESF. Bachelor's in Communication, Universidad de Lima, Peru M.S. in Environmental Science, SUNY ESF Ph.D. in Environmental Science (specializing in environmental communication and participatory processes), SUNY ESF Dr. Takahashi's research program focuses on news coverage of environmental issues, environmental journalism practices in Latin America and U.S. Latino media, and identity in science communication. His work emphasizes counter-hegemonic environmental discourses in Latin American contexts, examining complex networks of actors, media, and communication processes embedded in post-colonial and social and environmental justice dynamics. He has conducted extensive field research in Peru, Bolivia, and Puerto Rico, with particular attention to environmental communication during disasters and in Indigenous communities. His recent scholarly output reveals a strong trend toward examining climate change communication through diverse cultural lenses, with significant attention to Latin American perspectives, immigrant experiences in the United States, and identity factors in science communication. His publications frequently address decolonial approaches to environmental communication and the need for more inclusive international scholarship that centers Global South perspectives. Scientific awards and recognitions include: 2024 AEJMC First Place in Latin American Communication Research 2021 Fellow of the Institute for Diverse Leadership, AEJMC 2019 Knudson Latin America Book Prize Multiple top paper awards from ICA and AEJMC conferences Dr. Takahashi actively mentors a diverse research team of Ph.D. students, post-doctoral associates, and MA students, with former students now holding positions at universities including University of Nevada, University of Minnesota, and Emory University. His research is supported by significant grants including a $2.8 million NSF grant for the SciComm Identities Project, funding from the Climate and Land Use Alliance, and multiple State Department and Embassy grants for environmental journalism training in Latin America. He has developed and led education abroad programs to Peru (2018, 2024) and the Netherlands/Belgium (2022), providing experiential learning opportunities for students in environmental communication. As Research Director of the Knight Center for Environmental Journalism, Dr. Takahashi leads initiatives supporting environmental journalists globally. His current projects include examining environmental discourses in the Peruvian Amazon related to oil spills affecting Indigenous communities, studying decolonial environmental journalism practices in Bolivia and Peru, and co-leading Working Group 5 on Public Engagement and Governance for The Lancet Countdown Latin America, which has generated significant media coverage in outlets like CNN and El País.
Carlos Fernandez-Granda is an Associate Professor of Mathematics and Data Science at New York University, holding joint appointments at the Courant Institute of Mathematical Science and the Center for Data Science. He currently serves as the Interim Director of the Center for Data Science. His academic career spans over a decade at NYU, where he has taught probability and statistics to data-science students. Dr. Fernandez-Granda's research focuses on designing and analyzing data-science methodology, with current emphasis on machine learning applications in medicine, climate science, and scientific imaging. His work bridges theoretical foundations with practical applications across multiple domains. His notable contributions include: Development of the COBRA (COnfidence-Based chaRacterization of Anomalies) score for automatic assessment of impairment and disease severity Applications of machine learning to improve climate projections through the M2LInES project Research on magnetic resonance fingerprinting for quantitative tissue parameter estimation Development of AI systems for medical diagnostics including Alzheimer's detection and breast cancer diagnosis Dr. Fernandez-Granda is the author of the book "Probability and Statistics for Data Science," published by Cambridge University Press. The book serves as a comprehensive guide to the two pillars of data science, featuring real-world datasets and addressing fundamental challenges like overfitting, the curse of dimensionality, and causal inference. His research has been supported by grants from the National Science Foundation (Division of Mathematical Sciences, grants 1616340 and 2009752) and the Alzheimer's Association (grant AARG-NTF-21-848627). Dr. Fernandez-Granda is actively involved in several collaborative projects: M2LInES project: An international collaboration focused on improving climate projections using machine learning to capture unaccounted physical processes at the air-sea-ice interface Math and Data group: Exploring the intersection of mathematical theory and data science applications
Georg Fantner is an Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) with dual appointments in the School of Engineering (STI) within the Institute of Bioengineering and the School of Life Sciences (SV) for teaching. He directs the Laboratory for Bio- and Nano-Instrumentation (LBNI) and holds leadership roles including President of the Open Science Strategic Committee and the Association des Professeurs de l'EPFL. Research Focus: Bioinstrumentation, Nanotechnology, Scanning Probe Microscopy, and Metrology Teaching: Structural Mechanics for Life Sciences, Metrology, and Metrology Practicals His research pioneers advanced instrumentation for nanoscale characterization, emphasizing data-driven approaches to enhance microscopy techniques. Recent work integrates deep learning with scanning probe microscopy for real-time biological imaging and develops novel MEMS devices for fluid-compatible nanoscale manipulation. Key innovations include hermetically sealed sample chambers for pathogen studies and deterministic nanotopography engineering. Professor Fantner actively mentors 7 current PhD students and has supervised 14 graduates. His laboratory fosters interdisciplinary collaboration across engineering, physics, and life sciences to advance nanoscale measurement technologies and instrumentation development.
Minh Hue Nguyen is a Senior Lecturer in EAL/TESOL Teacher Education at Monash University's School of Curriculum, Teaching and Inclusive Education within the Faculty of Education. She holds a PhD in Education (TESOL focused) from Monash University and has taught at Vietnam National University, Deakin University, and the University of Melbourne. Her educational background includes: PhD in Education (TESOL focused), Monash University (2015) MA in Applied Linguistics, Victoria University of Wellington (2008) BA in English Language Teaching, Vietnam National University (2003) Nguyen's research centers on teachers' professional learning, curriculum, and pedagogy in TESOL and EAL contexts, with specific focus on emotional experiences, identity development, mentoring, agency, and collaboration. She explores sociocultural contexts of teacher development through activity theory and sociocultural perspectives, examining how institutions support teachers' learning journeys from preservice to in-service stages. Recent work investigates professional learning for teacher educators and implementation of the Victorian EAL Curriculum. Her 15 most recent publications (2024-2025) reveal a strong thematic focus on language teacher agency, identity negotiation, and multilingual pedagogies. The research increasingly examines emotional dimensions of teaching, cross-cultural identity tensions, and collaborative models between EAL and content teachers, with significant contributions to understanding how teachers navigate complex educational contexts while developing professional identities. Her scientific recognition includes: Penny McKay Award Special Commendation Monash Education Research Community's Publication Award ATEA/Kay Martinez Award for Best Paper Monash Dean of Education’s ECR Project Award Advancing Women's Research Success Grant Vietnamese Government Merit-based Scholarships Nguyen actively supervises PhD research in TESOL teacher professional learning, teacher identity, and curriculum development, though is currently unavailable for new PhD students until 2027. She contributes to editorial boards for Teaching and Teacher Education, Second Language Teacher Education, and System journals, and serves on the Australian Teacher Education Association. Her work supports UN Sustainable Development Goal 4 (Quality Education) through inclusive pedagogical frameworks. She leads research projects including 'Elucidating practices to assist EAL learners to acquire specialised science vocabulary' and 'Establishing an online community-of-practice model for learner agency during work placements,' demonstrating commitment to practical educational innovations.
Prof. Dr. Harald Wehnes serves as a Professor at the University of Würzburg within the Faculty of Mathematics and Computer Science, specifically affiliated with the Institute of Computer Science's Chair of Computer Science III (Communication Networks). His office is located in room A206 at the Hubland campus, with contact email wehnes@informatik.uni-wuerzburg.de. His research centers on project management methodologies, with particular emphasis on the Project Excellence Model and its practical applications. Prof. Wehnes has developed significant expertise in applying project management frameworks to complex IT infrastructure initiatives and healthcare systems. His work demonstrates how theoretical project management concepts translate into real-world implementation, especially in cross-organizational contexts. Analysis of his publication history reveals a consistent focus on practical project management applications, particularly the NIMBUS project case study which documented the consolidation of 12 data centers into a single state data center. His publications demonstrate evolving expertise from foundational programming work (evidenced by his 1981 book "Strukturierte Programmierung mit FORTRAN 77" which went through seven editions) to sophisticated project management frameworks. Prof. Wehnes has maintained active engagement with the German Project Management Association (GPM), presenting at numerous forums and events. His international reach is evident through presentations at institutions including the University of the United Arab Emirates and the University of Canterbury in New Zealand. From 2013-2020, he taught specialized courses on professional project management (Spezialvorlesung aus der Praxis: Professionelles Projektmanagement) at the University of Würzburg, sharing his extensive practical experience with students. His work environment within the Chair of Computer Science III connects his project management expertise with research areas including 5G & 6G network technologies, network and service management, and green communication networks.
Laura Ascenzi-Moreno serves as Professor of Bilingual Education and Bilingual Program Coordinator in the Childhood, Bilingual and Special Education Department at Brooklyn College, City University of New York (CUNY), School of Education. Her academic leadership focuses on developing educators capable of serving linguistically diverse student populations through equity-centered pedagogical frameworks. Her educational foundation includes a B.A. in Anthropology and Education from Swarthmore College (1994), an M.A. in Individualized Studies in Education from Harvard Graduate School of Education (1999), New York State Permanent Certification for PreK-6 (2002), a Bilingual ESL and Teacher Leadership Program from Bank Street College (2004), and a Ph.D. in Urban Education from CUNY Graduate Center (2012). Dr. Ascenzi-Moreno's research pioneers translanguaging applications across literacy instruction, assessment, and computational learning environments. She investigates how emergent bilinguals' linguistic repertoires can transform reading development, teacher knowledge construction, and multimodal assessment practices. Her work consistently centers equity through frameworks like syncretic reasoning and accompáñamiento, challenging deficit ideologies while promoting asset-based approaches to multilingual education. Analysis of her 2020-2024 publications reveals an accelerating interdisciplinary trajectory where translanguaging principles increasingly intersect with computer science education. This evolution demonstrates strategic expansion from foundational literacy research into computational literacies, with growing emphasis on co-design methodologies and teacher agency in developing multilingual CS curricula. Her scientific recognition includes the 2024 NCTE Outstanding Elementary Educator Award, Language Arts Distinguished Article Award, and major NSF grants totaling $1.3 million for computational literacy projects. Additional honors encompass Fulbright Scholarship work in Colombia, PSC-CUNY research awards, and Westinghouse Science Talent Search distinction. As Principal Investigator of NSF-funded PiLa-CS and former CUNY-NYSIEB Associate Investigator, she secures substantial grant support while mentoring teacher candidates. Her service includes NCTE Elementary Steering Committee leadership (2022-2026), journal reviewing, and Brooklyn's New York Teacher Table participation addressing educator recruitment/retention. Dr. Ascenzi-Moreno co-directs the Participating in Literacies in Computer Science project and maintains active collaboration with NYC schools through translanguaging professional development initiatives. Her work with the CUNY-NYSIEB project established foundational frameworks now implemented across New York bilingual programs.
Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .
Taylor Sparks is a Professor of Materials Science and Engineering at the University of Utah, where he also serves as Director of Graduate Affairs for the John and Marcia Price College of Engineering. He holds a PhD in Applied Physics from Harvard University, an MS in Materials from the University of California, Santa Barbara, and a BS in Materials Science & Engineering from the University of Utah. His research focuses on advancing materials discovery using machine learning to streamline and optimize material design, with applications in energy materials, dental materials, and sustainable engineering. His work integrates big data and materials informatics to explore new synthetic techniques, structure-property relationships, and sustainable materials that balance performance with economic factors. The Sparks Research Group has secured funding from agencies including DOE, NSF, DOD, and various industry partners. Sparks' recent research output demonstrates a strong trend toward leveraging artificial intelligence and machine learning to accelerate materials discovery, with particular emphasis on large language models for materials science, Bayesian optimization for experimental design, and novel approaches to crystal structure prediction. His work bridges the gap between theoretical predictions and experimental validation in materials science. NSF CAREER Award Royal Society Wolfson Visiting Fellow Acta Materialia Outstanding Reviewer Award for 2020 Honorary Outstanding Faculty Teaching Award of 2020-2021 Materials Science & Engineering Department Research Award for 2023 John G. Francis Prize for Undergraduate Student Mentoring Sparks has advised numerous graduate students who have gone on to successful careers in academia and industry. His research has been supported by significant grants from NSF, DOE, DOD, Army Research Office, and industry partners. His group has developed innovative tools including the Materialism Podcast, a materials science YouTube channel, and the Honegumi interface for Bayesian optimization, demonstrating his commitment to both research excellence and science communication. The Sparks Research Group operates multiple laboratories focused on materials characterization, synthesis, and informatics. They collaborate extensively with other institutions globally, host visiting researchers, and run outreach initiatives including the Materialism Podcast and YouTube channel to make materials science more accessible to broader audiences.
Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.
Mark Andrejevic is a Professor in the School of Media, Film, and Journalism at Monash University. He specializes in the socio-cultural implications of digital surveillance, data mining, and automated decision-making. His research spans Big Data ethics, privacy regulation, and the impact of technology on democracy. He leads major projects like the ARC Centre of Excellence for Automated Decision-Making and Society, focusing on AI’s societal implications. Andrejevic has been awarded Fellow of the Australian Academy of Humanities and the Nancy Baym Book Award. His work intersects with UN Sustainable Development Goals addressing justice and innovation. Research interests include automated surveillance systems, digital privacy policies, and the ethical governance of emerging technologies. He collaborates on projects such as facial recognition technology ethics and pandemic-era surveillance practices. His recent publications analyze platform accountability, algorithmic bias, and the societal effects of workplace monitoring technologies. He actively contributes to public discourse via media engagements and policy-focused talks on topics like facial recognition in education and pandemic-era data collection. Projects: ARC QEII Fellowship ($390k, 2010–2014), Australian Public Attitudes to AI, and facial recognition ethics studies. Grants: Over $390k from ARC for privacy research, plus ongoing funding through collaborative initiatives. Awards: Australian Academy of Humanities Fellowship (2020), Nancy Baym Book Award (2014). He supervises graduate students in Digital Media, Surveillance Studies, and Critical Theory. His interdisciplinary work bridges academia, policy, and industry to address technology’s societal challenges while advocating for democratic values.
Daniel E. Koditschek is the Alfred Fitler Moore Professor in the Department of Computer and Information Science at the University of Pennsylvania’s School of Engineering and Applied Science. He also holds primary appointments in the Department of Electrical and Systems Engineering and a research affiliation with the Department of Mechanical Engineering and Applied Mechanics. He is a leading figure in the GRASP Lab, where he leads the Kod*lab, a specialized group focused on physical interaction and locomotion in autonomous robots. His research lies at the intersection of dynamical systems theory and robotics, emphasizing legged locomotion, hybrid control systems, and bio-inspired design. Koditschek's work integrates formal mathematical modeling with empirical testing of physical robots that run, jump, climb, and manipulate objects. He actively explores how biological insights into animal mobility can inform robotic autonomy and control. His group maintains strong collaborations with biologists and emphasizes embodied intelligence in machine behavior. The recent publications reflect a strong trend in applying theoretical control frameworks—such as hybrid dynamical systems, averaging methods, and navigation functions—to practical robotic challenges in unstructured environments. Topics include terrain adaptation, energy-efficient locomotion, reactive planning, and affordance-based interaction. There is a clear focus on bridging abstract mathematical models with real-world robotic performance, particularly in legged and mobile manipulation systems. IEEE RAS Pioneer Award Heilmeier Research Award AFOSR MURI Award (2010) Daniel Koditschek has advised numerous PhD students and postdoctoral researchers, many of whom now hold faculty positions or leadership roles in robotics companies like Ghost Robotics and Boston Dynamics. His research is supported by major grants from the NSF and AFOSR, including the MURI award and REU/RET programs that engage K-12 and undergraduate educators. He has also been involved in international outreach, including activities at the Penn Wharton China Center. Koditschek leads the Kod*lab within the GRASP Lab’s PERCH facility, which houses advanced legged robots such as the Ghost Minitaur, XRHhex, Inu, Delta Hopper, and Jerboa platforms. The lab emphasizes experimental validation of control theories using custom hardware and real-world terrain challenges.
Laura Toni is an Associate Professor in the Department of Electronic and Electrical Engineering at University College London's Faculty of Engineering Sciences. She serves as the leader of a research team focused on advanced signal processing and machine learning applications, documented at https://lasp-ucl.github.io . Additionally, she holds prestigious affiliations as an ELLIS (European Laboratory for Learning and Intelligent Systems) Member and Turing Fellow Alumni. PhD in Electrical Engineering, University of Bologna (2009) MS in Electrical Engineering, University of Bologna (2005) Professor Toni's research spans theoretical and applied aspects of machine learning with particular emphasis on graph-based approaches. Her work integrates signal processing techniques with modern AI methodologies to address complex problems in communication systems, multimedia processing, and scientific discovery. She has made significant contributions to reinforcement learning theory, graph signal processing, and their applications across diverse domains including drug discovery and immersive technologies. Analysis of her recent publications reveals a strong focus on graph-based machine learning approaches, with increasing emphasis on reinforcement learning applications. Her work demonstrates a progression from theoretical foundations to practical implementations, particularly in multimedia processing, network science, and drug discovery applications. Many of her recent papers combine graph neural networks with diffusion models and reinforcement learning for complex prediction and generation tasks. Professor Toni has received notable recognition through her ELLIS membership and Turing Fellow Alumni status, which represent significant achievements in the European AI research community. ELLIS (European Laboratory for Learning and Intelligent Systems) Member Turing Fellow Alumni As an academic leader, Professor Toni supervises postgraduate students and leads a research team at UCL, focusing on cutting-edge projects at the intersection of signal processing and machine learning. Her team has secured research funding through various channels including European initiatives and industry partnerships, enabling them to pursue ambitious projects in graph learning, reinforcement learning, and multimedia processing. The team actively collaborates with institutions worldwide, including previous connections with UCSD and EPFL. Professor Toni leads the LASP research group at UCL (https://lasp-ucl.github.io), which focuses on Large-scale Adaptive Signal Processing for intelligent systems. The team comprises researchers working on graph signal processing, reinforcement learning, and multimedia applications, with strong connections to both theoretical foundations and practical implementations across various domains including healthcare, communications, and immersive technologies.
