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Adrian WellerView profile

Research Professor

• Artificial Intelligence
• Machine Learning
• Explainability
• +9 more

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.

Osbert BastaniView profile

Associate Professor

• Machine Learning
• Neurosymbolic AI
• Program Synthesis
• +10 more

Osbert Bastani is an Associate Professor at the Department of Computer and Information Science, University of Pennsylvania, leading the trustml@Penn research group. He is affiliated with the ASSET , PRECISE , and PRiML centers, and the PLClub research group. His research focuses on Trustworthy Neurosymbolic Systems , Synthesizing Neurosymbolic Programs , and Machine Learning for Programmer Productivity , with applications in verification, fairness, and human-AI collaboration. He received the NSF CAREER Award in 2023. His recent publications (2024-2025) emphasize AI Safety , LLM Robustness , and Algorithmic Fairness , including work on adversarial robustness, conformal prediction, and program synthesis. Students he has advised include Sagnik Anupam, Stephen Mell, Jason Ma, Shuo Li, and others. Awards: NSF CAREER Award (2023)

• Educational Leadership
• Comparative Research
• Innovation in Education
• +3 more

Dr. Dong Nguyen is an Associate Professor in Leadership Management and Change in Education at Durham University's School of Education. He serves as Director of the Master’s Programme in Educational Leadership and Change, which focuses on leadership, management, and research in education. Additionally, he is Editor-in-Chief of the International Journal of Educational Management (IJEM), a core journal in educational leadership. His career includes roles as a lecturer (Assistant Professor) and Programme Leader at the University of Glasgow, a Research Associate at Nanyang Technological University, and a teacher in Vietnam. Nguyen’s research emphasizes building leadership capacity in the Global South, comparative education studies, and innovation in education. He has led projects such as an impact evaluation of a Rwanda school leadership development program (2023–2026) funded by VVOB and a review of school leadership’s role in teacher retention funded by the Education Endowment Foundation (EEF). His work explores leadership practices across sectors like education, business, and healthcare, with a focus on equitable systems and professional learning. Nguyen has received a Discretionary Award from Durham University (2023) and has delivered numerous invited talks, including at the Chinese University of Hong Kong (2024), the Asian Conference on Business and Economic Studies (2024), and Stockholm institutions (2023). He has served as an external examiner for UK universities (e.g., Leeds, Newcastle) and evaluator for grants like UK Research & Innovation and Swiss National Science Foundation. His supervision focuses on topics like school leadership, inter-organizational collaboration, and professional development. Nguyen’s recent articles highlight leadership’s role in teacher retention, autonomy, and PLCs in the Global South. He advocates for leadership practices that foster teacher collaboration, instructional support, and participatory decision-making, particularly in contexts like Singapore and Vietnam. His funded projects and editorial roles underscore his commitment to evidence-based educational policy and practice.

• Bayesian statistics
• Stochastic simulation
• Markov chain Monte Carlo
• +5 more

Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology

• Business Process Management
• Process Mining
• Software Engineering
• +3 more

Marlon Dumas is a Professor of Information Systems at the University of Tartu's Faculty of Science and Technology, with a 20-year academic career spanning Estonia and Australia. He holds a PhD in Computer Science from the University of Grenoble 1, France, and has served as Head of Chair and Programme Director in Software Engineering programs. Specializes in Business Process Management (BPM) and Process Mining Current research focuses on prescriptive process monitoring, simulation modeling, and data privacy Recipient of 25+ scientific awards, including multiple Test of Time Awards and the Estonian National Research Award in Technical Sciences Editorial leadership: Area Editor for Information Systems (Elsevier) and ERC Starting Grant Panel Chair His work bridges theoretical advancements in BPM with practical applications in financial services and anti-money laundering. He has developed tools like SIMOD, Kronos, and Kairos for process optimization and analysis. His research integrates AI/ML techniques (reinforcement learning, causal inference) with traditional process modeling. Key trends in his recent publications include: Prescriptive monitoring systems combining causal inference and machine learning Privacy-preserving process mining techniques (differential privacy, anonymization) Resource availability modeling and multi-objective process optimization LLM applications for process analysis and intervention policies Scientific honors include: 2024 BPM Best Paper & Prototype Awards 2023 ICPM Best Prototype Award 2019 ERC Advanced Grantee 2017 Estonian National Research Award in Technical Sciences 2019 MODELS Test of Time Award 2017 BPM Best Prototype Award He has mentored PhD candidates as thesis examiner and contributed to 30+ conference program committees, including General Co-Chair roles at ESEC-FSE 2019 and CAiSE 2018. His work has been supported by European Research Council grants and Estonian Science Foundation projects.

Eric WongView profile

Assistant Professor

• Machine Learning
• Artificial Intelligence
• Explainable AI
• +5 more

Eric Wong is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania, affiliated with the ASSET Center and leading the Brachio Lab. His research focuses on robust and reliable machine learning, including model debugging, adversarial robustness, and explainable AI. He holds a PhD from Carnegie Mellon University (CMU), advised by J. Zico Kolter, and completed a postdoc with Aleksander Madry. His work bridges theory and practice, addressing challenges in model interpretability, safety, and scalability. Teaching includes CIS 5200 (Machine Learning), CIS 3333 (Mathematics for Machine Learning), and a specialized course on debugging ML pipelines. Notable contributions include the FIX Benchmark for interpretable features and defenses against LLM jailbreaking attacks. He received an Amazon Research Award in 2024 and has published extensively in top conferences like ICML, NeurIPS, and ICLR. Affiliations: University of Pennsylvania (CIS), ASSET Center, Brachio Lab Education: PhD in Machine Learning (CMU), Postdoc at MIT Key Projects: FIX Benchmark, DOLPHIN framework, SmoothLLM defense Awards: Amazon Research Award (2024) Lab Focus: Safe AI, model debugging, neurosymbolic learning

• Management Education
• Project Management
• Information Management
• +3 more

Prof. Dr. Frank Ulbrich is a Lecturer and Programme Director for the BSc Business Administration at the Lucerne School of Business (HSLU). He holds a PhD in Business Administration from the Stockholm School of Economics. His academic career spans roles at universities in Sweden, the UK, Canada, and Switzerland, alongside IT & Management consulting experience. Research focuses on management education, project management, information management, and organizational change. He has published extensively in areas like shared services, digital transformation, and curriculum development. Notable awards include multiple Emerald Literati Awards and a Fellowship from the Higher Education Academy. Education: PhD in Business Administration (Stockholm School of Economics) Affiliations: Institute of Business and Regional Economics at HSLU Teaching Subjects: Academic Methods, Higher Education Management, Project Management, Digital Transformation Recent presentations include discussions on bridging academia-industry gaps, curriculum integration of SDGs, and data-driven learning strategies. His work emphasizes aligning education with labor market needs and advancing evidence-based teaching practices.

• Child Welfare
• Secure Accommodation
• Poverty and Social Inequalities
• +3 more

Dr Martin Elliott is a Senior Research Fellow at the Children's Social Care Research and Development Centre (CASCADE), Cardiff University, and holds roles as Research Development Adviser for Health and Care Research Wales and academic lead for the all-Wales ExChange programme. His work focuses on child welfare inequalities, poverty, secure accommodation, and services for disabled children. With 17 years in statutory children’s services, he transitioned to academia via a PhD analyzing looked-after children in Wales. He has secured £3.4M+ in research funding, including a major CASCADE partnership grant. Educated with a DipSW (1997), BA(Hons) Community Studies (1998), MSc Social Science Research Methods (2013), and PhD (2018), his expertise spans mixed-methods research. Awards include the ESWRA doctoral thesis award (2020) and BASW’s British Journal of Social Work prize (2021). His research explores socio-economic dimensions in social work practice, policy impacts, and system equity. Key grants include studies on child welfare interventions, kinship care, and secure accommodation outcomes. He leads projects analyzing Wales’ Flying Start program, workforce regulation impacts, and crisis mental health services. CASCADE collaborates internationally on child welfare systems, reflecting his strategic focus on translating research into policy. His work bridges academic inquiry with frontline practice, addressing systemic challenges in child protection and welfare delivery.

Enrica Dall'AraView profile

Associate Professor

• Practice-based research
• Public space design
• Urban renewal
• +3 more

Dr. Enrica Dall'Ara serves as the Associate Dean of Planning and Landscape Architecture and an Associate Professor at the University of Calgary's School of Architecture, Planning and Landscape. Her work bridges academic research and professional practice, exemplified through her firm PARC, which specializes in public space design, urban renewal, and the rehabilitation of industrial sites. She emphasizes interdisciplinary collaboration, integrating fields like environmental engineering and biology into landscape architecture. Education: Laurea in Architettura (Master Degree equivalent in Architecture), University of Ferrara, Italy Master in Landscape Architecture, ETSAB, Polytechnic University of Catalonia, Spain PhD in Landscape Design, University of Florence, Italy Research Interests: Dr. Dall'Ara focuses on practice-based research, public space design, service landscapes, and the integration of cultural advocacy into landscape architecture. Her work explores site-specific design solutions, the role of agriculture in urban-rural dynamics, and the preservation of traditional rural landscapes. She advocates for designs that serve life through poetic, functional, and culturally sensitive approaches. Contributions: Through her teaching, Dall'Ara encourages students to view design as research, fostering critical thinking and interdisciplinary dialogue. Her firm’s projects, such as the roundabout gardens in Imola, Italy, demonstrate her commitment to merging ecological, functional, and aesthetic considerations in landscape interventions. Professional Affiliations: Canadian Society of Landscape Architects (CSLA) Alberta Association of Landscape Architects (AALA) Associazione Italiana di Architettura del Paesaggio (AIAPP) Ordine degli Architetti, Pianificatori, Paesaggisti e Conservatori (Province of Forlì-Cesena, Italy)

Andrew ChildsView profile

Professor

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +2 more

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

Reza ShokriView profile

Associate Professor

• Data Privacy
• Trustworthy Machine Learning
• Security
• +7 more

Reza Shokri is a Dean's Chair Associate Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His research lies at the intersection of data privacy, security, and trustworthy machine learning, with a focus on quantifying privacy risks and developing robust, fair, and interpretable models. PhD in Computer Science, EPFL His research interests center on data privacy and trustworthy machine learning , particularly in the context of deep learning and federated systems. He investigates how machine learning models memorize training data, leading to privacy leakage, and designs frameworks to audit and mitigate such risks. His work bridges theoretical guarantees with practical applications, emphasizing the trade-offs among privacy, fairness, robustness, and utility. His recent publications (2023–2025) reveal a strong trend in analyzing privacy in large language models (LLMs), membership inference attacks, federated learning, and fairness. These works are published in top venues such as NeurIPS, ICML, ICLR, CCS, and FAccT, highlighting his leadership in both AI and security communities. Notable scientific awards include: Asian Young Scientist Fellowship (2023) Intel Outstanding Researcher Award (2023) Best Paper Award, ACM FAccT (2023) IEEE S&P Test-of-Time Award (2021) Caspar Bowden Award for Privacy Enhancing Technologies (2018) NUS Presidential Young Professorship (2019–2023) VMware Early Career Faculty Award (2021) He has advised numerous PhD and Master’s students, many of whom have contributed to high-impact publications. He has also received research grants from major industry partners including Meta, Google, Intel, and VMware. He leads the Data Privacy and Trustworthy Machine Learning Lab at NUS and has served on program committees for top conferences such as IEEE S&P, ACM CCS, and FAccT, including co-chairing roles at HotPETs and Shadow PC of IEEE S&P. He has delivered tutorials at ICML and CCS on privacy auditing in machine learning. His lab focuses on developing tools and frameworks—such as the ML Privacy Meter—for assessing and improving the privacy properties of machine learning models, with applications in regulatory compliance and secure AI deployment.

• Computer Networks
• Network Security
• Machine Learning in Networking
• +3 more

Mariano Scazzariello is a Lecturer at KTH Royal Institute of Technology, Sweden, affiliated with the School of Electrical Engineering and Computer Science and the Department of Network and Systems Engineering. He teaches the course 'Network Systems with Edge or Cloud Datacenters (IK2227)'. His research focuses on advanced networking topics including machine learning in networks, high-speed packet processing, network emulation, and software-defined networking innovations. His work spans contributions to network emulation tools like Kathará and Megalos, stateful packet processing at terabit scales, and leveraging large language models (LLMs) for network configuration and vulnerability detection. Recent research emphasizes low-latency protocols (e.g., SRv6/DetNet integration) and GPU-centric networking on commodity hardware. Mariano’s publications (2020–2025) highlight expertise in network function virtualization, ASIC-based switching, and optimizing network configurations through AI-driven approaches. He has pioneered frameworks for evaluating routing protocols and virtualizing large network scenarios at scale.

• Clinical Toxicology
• Pharmacoepidemiology
• Poisoning
• +3 more

Professor Nicholas Buckley is a leading academic in Clinical Pharmacology at the University of Sydney and holds a Visiting Professor position at the University of Peradeniya, Sri Lanka. He serves as Research Director for the South Asian Clinical Toxicology Research Collaboration (SACTRC) and is a Consultant Clinical Pharmacologist & Toxicologist at the NSW Poisons Information Centre and Royal Prince Alfred Hospital. His work focuses on improving clinical toxicology practices, poison control policies, and understanding mechanisms of drug toxicity. Co-founder of SACTRC for agrochemical poisoning and snakebite research Chair of Australian Therapeutic Guidelines - Toxicology writing group Editorial roles in Clinical Toxicology, Drug Safety, and Australian Prescriber Research Interests include toxicovigilance, epidemiology of poisoning, acute kidney injury in poisoning/snakebite, pesticide safety interventions, antidote development, and pharmacoepidemiology of psychotropic drugs. His work combines clinical trials, population surveillance, and translational research. Scientific Contributions span 440+ peer-reviewed articles and 22 book chapters, with continuous funding since 2002. He has supervised over 20 higher degree students and leads international collaborations in low-and-middle-income countries through NIHR RIGHT4. Key Affiliations : Member of Charles Perkins Centre, Australian Medicines Handbook Editorial Advisory Board, and NIHR RIGHT4 programme.

• Entrepreneurship
• Innovation
• Entrepreneurship Education
• +5 more

Paschal Anosike is a Professor of Entrepreneurship and Innovation at the University of the West of England's Faculty of Business and Law. He serves as Director of the Centre for African Social and Economic Transformation (CASET) and Chair in African Research and Partnerships. Previously, he founded and directed the Centre for African Entrepreneurship and Leadership (CAEL) at Wolverhampton Business School. Education BA (Hons) MA PGCHE PhD Paschal's research focuses on advancing entrepreneurship ecosystems in Africa, with emphasis on innovation management, education, and sustainable development. His work bridges academic theory with practical solutions for African socioeconomic challenges. His publications highlight trends in entrepreneurial ecosystems, gender equality, religiosity, and institutional impacts on entrepreneurship. He has contributed to global policy discussions via the Africa Prosperity Index and co-created the Micro-Venture Accelerator Programme (m-VAP) for African universities. Scientific Awards Award-winning book: Entrepreneurship and Sustainable Development in Africa Paschal has received advisory and consultancy grants from the African Union Commission, European Commission, UNDP, GIZ, and the Legatum Institute. He founded the Forum for Innovation in African Universities (FIAU), a non-profit promoting university-industry collaboration.

• Macroeconomic Theory
• Monetary Economics
• Macroeconometrics
• +7 more

Jordi Galí is a Professor at the Department of Economics and Business at Universitat Pompeu Fabra (UPF), a Senior Researcher at the Center for Research in International Economics (CREI), and a Research Professor at the Barcelona School of Economics (BSE). He holds a PhD from MIT and has played a central role in shaping modern macroeconomic theory, particularly the New Keynesian framework used by central banks worldwide. Education: PhD in Economics, Massachusetts Institute of Technology (MIT), 1989 Master in International Management, ESADE, 1985 Bachelor in Economics, Universitat Pompeu Fabra, 1994 His research focuses on macroeconomic theory, monetary economics, and macroeconometrics. He is best known for his work on the New Keynesian Phillips Curve, optimal monetary policy rules, and the role of technology and expectations in business cycles. His influential book, Monetary Policy, Inflation and the Business Cycle , is a standard reference in graduate programs globally. The most recent articles highlight a continued focus on critical issues in modern macroeconomics: the implications of a low natural rate of interest (r*), the effectiveness of monetary policy at the zero lower bound, the role of wage and price flexibility, and the interaction between fiscal and monetary policy. His work increasingly integrates heterogeneity, financial frictions, and experimental methods, reflecting the evolving frontiers of the field. Scientific Awards: BBVA Foundation Frontiers of Knowledge Award (2025) Yrjo Jahnsson Award (2005) Premi Rei Jaume I d'Economia (2004) Premio Nacional de Investigación “Pascual Madoz” (2022) Three ERC Advanced Grants Foreign Honorary Member, American Economic Association (2020) Galí has advised numerous central banks, including the ECB, Federal Reserve, and Banque de France. He has held leadership roles as President of the European Economic Association (2012), co-editor of the Journal of the European Economic Association , and co-director of the CEPR International Macroeconomics Programme. He is a Research Fellow at CEPR, a Research Associate at NBER, and a Fellow of the Econometric Society. He has also been actively involved in public policy debates in Spain and Europe, particularly on issues of productivity, labor market reform, and fiscal policy. His research program continues to explore the design of stabilization policies in open and currency union economies.