Find Academic Supervisors

Đorđe Žikelić is an Assistant Professor of Computer Science at the School of Computing and Information Systems at Singapore Management University (SMU) in Singapore. He completed his PhD in 2023 at the Institute of Science and Technology Austria (ISTA) under Krishnendu Chatterjee and Petr Novotný, receiving both Outstanding PhD Thesis and Outstanding Scientific Achievement awards. Prior to his doctorate, he earned bachelor's and master's degrees in mathematics from the University of Cambridge. His educational background includes: PhD in Computer Science, Institute of Science and Technology Austria (ISTA), 2023 Bachelor's and Master's in Mathematics, University of Cambridge Dr. Žikelić's research focuses on advancing formal methods to ensure software and AI systems are correct, safe, and trustworthy. His work bridges theoretical aspects of formal reasoning about probabilistic systems with practical automated verification methods. His primary research interests span three interconnected areas: Program Analysis and Verification: He develops techniques for analyzing probabilistic programs, numerical programs, and efficient quantifier elimination methods, addressing fundamental challenges in verifying complex software systems. Trustworthy AI and Safe Autonomy: He creates formal verification frameworks for learning-enabled control systems and neural networks, ensuring AI operates safely in uncertain environments through methods like runtime monitoring and certificate repair. Probabilistic System Verification: He explores broader applications including bidding games on graphs and blockchain protocol analysis, extending formal methods to novel domains beyond traditional finite-state verification. His publication trajectory shows a consistent progression from theoretical foundations to practical applications, with recent work increasingly focused on integrating formal verification with machine learning. His 2024-2025 publications demonstrate growing expertise in verifying learning-based systems and developing practical tools like PolyQEnt for quantified entailment solving. His scientific achievements have been recognized with: Outstanding PhD Thesis Award at ISTA Outstanding Scientific Achievement Award at ISTA Distinguished Paper Award at FM 2024 Dr. Žikelić serves on program committees for major conferences including TACAS, PLDI, AAAI, and CAV. He actively mentors through the Programming Languages Mentoring Workshop (PLMW) at PLDI 2025. His research group at SMU focuses on developing novel algorithms for verifying correctness of programs and AI systems, with current projects spanning formal methods, artificial intelligence, and programming languages.

• Formal Methods
• Program Analysis and Verification
• Trustworthy AI
• +5 more

Victor Klockmann is a Junior Professor of Microeconomics, specifically focusing on the Economics of Digitization at the University of Würzburg's Faculty of Management and Economics, Department of Economics. He also serves as an Associate Research Scientist at the Center for Humans and Machines, Max Planck Institute for Human Development in Berlin, and is an Affiliated Researcher at the Frankfurt Laboratory for Experimental Economic Research (FLEX) at Goethe University Frankfurt. His academic career spans multiple prestigious institutions with a focus on the intersection of economics, artificial intelligence, and human behavior. PhD in Economics (Dr.rer.pol), Goethe University Frankfurt, 2021 (Summa cum laude) M.Sc. Quantitative Economics, Goethe University Frankfurt, 2018 M.Sc. Mathematics, Goethe University Frankfurt, 2016 B.Sc. Mathematics, Goethe University Frankfurt, 2014 Professor Klockmann's research focuses on the economic and ethical implications of artificial intelligence, behavioral and experimental economics, game theory, and organizational economics. His work examines how new technologies impact organizations and human behavior, the interaction and cooperation between humans and non-human agents, and the future of work in times of technological change. His experimental approach combines theoretical economics with laboratory experiments to understand the nuanced dynamics of human-AI interactions. Analysis of his publications reveals a strong emphasis on ethical considerations in AI deployment, particularly regarding distributional fairness, social preferences toward machines, and intergenerational responsibility. His work spans multiple disciplines, bridging economics, computer science, psychology, and ethics, with a consistent focus on experimental methodologies to generate empirical evidence about human behavior in technological contexts. Scientific Awards and Recognition: External Funding from DFG for Strategic Interactions in Organizational Decision-Making (2024) Funding from Hessian Center for AI for Cooperation with Machines (2023) PhD Paper Award at IAREP/SABE Conference (2019) Prize for Best Master in Quantitative Economics (2019) Professor Klockmann actively supervises bachelor's and master's theses in Business Management, Economics, Business Informatics, and related fields. His research has attracted significant external funding from the German Research Foundation (DFG), the Hessian Center for Artificial Intelligence, and the Leibniz Institute for Financial Research SAFE. His current projects explore strategic interactions with generative AI, cooperation in human-algorithm settings, and the organizational implications of new technologies. He is affiliated with the Man and Machine research team at the Max Planck Institute, where he investigates human-AI interaction dynamics, and contributes to the Frankfurt Laboratory for Experimental Economic Research (FLEX), which specializes in experimental approaches to economic questions. His research environment combines cutting-edge experimental facilities with theoretical economic analysis to address pressing questions about technology's role in society.

• Economics and Ethics of Artificial Intelligence
• Behavioral and Experimental Economics
• Game Theory
• +5 more

Dr. Gabriella Pizzuto is a Lecturer in Robotics and Chemistry Automation with a joint appointment in the Department of Computer Science and Department of Chemistry at the University of Liverpool. She serves as Research Area Lead for the Royce Digital Chemical Materials Design Research Area, holds a Royal Academy of Engineering Research Fellowship, and acts as ECR Co-Chair for the EPSRC AI Hub in Chemistry (AIChemy). Her educational background includes a Ph.D. in Computer Science (2020) from the University of Manchester, where she was a Marie-Sklodowska Curie Early Stage Researcher. During her doctoral studies, she held visiting scholar positions at the University of Edinburgh and the Italian Institute of Technology, followed by a postdoctoral research associate position at the Edinburgh Centre for Robotics. Dr. Pizzuto's research sits at the critical intersection of robotics and applied machine learning for scientific discovery. Her work specifically targets: Multimodal robot skill learning in unstructured environments Failure recovery systems for chemistry laboratory automation Safe human-robot collaboration frameworks Accelerated materials discovery through autonomous experimentation Her research group develops learning-based methods to enable robotic scientists to operate with increasing autonomy in complex experimental settings. Dr. Pizzuto's scientific recognition includes: Royal Academy of Engineering Research Fellowship Marie Skłodowska-Curie Early Stage Researcher Fellowship Her research trajectory demonstrates strong grant leadership, having served as Lead Research Associate on the ERC Synergy Grant 'Autonomous Discovery of Advanced Materials' (ADAM) before establishing her independent research program. Current funding is supported through her Royal Academy Fellowship and leadership roles in national research hubs. Dr. Pizzuto leads a dynamic research group focused on developing intelligent robotic systems for chemistry laboratories, with particular emphasis on creating adaptive platforms that can learn from experimental failures and collaborate effectively with human researchers to accelerate scientific discovery.

• Robotics
• Applied Machine Learning
• Human-Robot Collaboration
• +3 more

Dr. Carl Fernandes serves as Clinical General Practice Associate Professor in Primary Care & Public Health at Brighton and Sussex Medical School, University of Sussex. A Brighton native, he holds MBBS, BSc, MRCGP (2013), MSc (with distinction in Clinical Education), MAcadMEd, and FHEA qualifications. His role encompasses teaching general practice across all undergraduate years with specialized focus on Years 4-5 GP curriculum. His educational background includes medical training at The Royal Free and University College Medical School, followed by GP specialization through University College London Hospitals. He returned to Brighton to teach after clinical practice, developing expertise in simulated consultations and headache management pedagogy. Research centers on undergraduate medical education in general practice , with dual streams: contemporary pedagogy (consultation skills, clinical uncertainty management, technology-enhanced learning) and historical medical research (Brighton's 19th-century medical practitioners). His work demonstrates consistent publication output in medical education journals with increasing focus on practical frameworks like 'The Brighton Guide' for consultation dynamics. Recent publications (2023-2025) reveal three dominant trends: 1) NHS sustainability through general practice ('holding patient care' concept), 2) Innovative teaching methods ('show don't tell' demonstrations), and 3) Historical analysis of compassion concepts ('tenderness' in patient care). This triangulation of past, present, and future practice defines his scholarly approach. Distinction in MSc Clinical Education Fellow of the Higher Education Academy As Personal Clinical Tutor and academic supervisor for F2 doctors in Years 4-5, he guides students through GP placements and simulated consultations. His supervision emphasizes 'supervised independence' - gradual autonomy within safe boundaries. Current projects expanding primary care exposure include 'out-of-area' placement programs and student self-arranged placement initiatives, addressing critical workforce pipeline challenges. He collaborates extensively within a diverse academic GP team, focusing on curriculum development for headache management and consultation skills. His historical research on Brighton's medical heritage provides unique context for modern practice, particularly regarding physician-patient relationship evolution.

• Medical Education
• General Practice
• Primary Care
• +3 more

Professor Tanja Brandl-Götz serves as Professor of General Pedagogy with a focus on Early Childhood Education and Program Director for the Bachelor's program in Early Childhood Education at Protestant University of Applied Sciences Nuremberg. A member of the Social Science Institute for Research and Transfer (SWIFT), she brings over two decades of combined academic and practical experience in social pedagogy, having previously led the Fachakademie for Social Pedagogy Hensoltshöhe and coordinated the Familienzentrum Sonnenhof project. Her educational background includes a PhD in Philosophy from Friedrich-Alexander-Universität Erlangen-Nürnberg (2016), Diploma in Educational Sciences from Philipps-Universität Marburg (2007-2009), Diploma in Social Work from Evangelische Fachhochschule Nürnberg (2003-2007), and certification as a state-recognized educator (1998-2001). Additional qualifications include systemic counseling training (2016) and Social Business Administration studies (2007-2008). Brandl-Götz's research centers on early childhood education dynamics, with expertise in play pedagogy, resilience development, and qualitative social research methodologies. She investigates pedagogical processes through the lens of children's perspectives, examining how educational partnerships function during crises like the pandemic and addressing emerging issues such as gender diversity in childhood development. Her work consistently bridges theoretical frameworks with practical applications in kindergarten settings. Analysis of her 15 most recent publications (2011-2025) reveals evolving research trajectories: early work focused on foundational pedagogical theories and play-based learning, transitioning to resilience frameworks during the pandemic, and most recently addressing children's agency in educational design and gender diversity. The publications demonstrate strong interdisciplinary connections between educational theory, child psychology, and social policy implementation. Outstanding Teaching Award 2014 (recognized in Forum der Lehre proceedings) As Program Director, Brandl-Götz oversees curriculum development and student supervision for the Early Childhood Education program, emphasizing reflective practice and theory-practice integration. Her leadership in projects like the Familienzentrum Sonnenhof and 'Kita als sicherer Ort' safety initiative demonstrates successful grant acquisition and implementation. Current research focuses on participatory educational design informed by children's perspectives. Through her membership in SWIFT, Brandl-Götz contributes to interdisciplinary research transfer initiatives that connect academic scholarship with practical applications in social pedagogy and early childhood education settings across Bavaria.

• Early Childhood Education
• Play Pedagogy
• Resilience Research
• +6 more

Yiwei Lyu serves as Assistant Professor in the Department of Computer Science and Engineering at Texas A&M University, joining the faculty in August 2025 after completing her Ph.D. at Carnegie Mellon University. Her research program bridges control theory, machine learning, and social science to develop safe, socially-compliant autonomous systems. Her educational background includes: Ph.D. in Electrical and Computer Engineering, Carnegie Mellon University (2025) B.S. in Electronic Information Engineering, The Chinese University of Hong Kong, Shenzhen (2019) Professor Lyu's work centers on risk-aware safe control for multi-agent systems, with emphasis on verifiable safety guarantees in human-robot interaction. She pioneers methods integrating control barrier functions with social preference modeling to enable robots that navigate complex environments while respecting human norms. Her research spans autonomous driving, multi-robot coordination, and human behavior prediction, consistently addressing the critical challenge of safety assurance in uncertain real-world scenarios. Analysis of her 15 most recent publications reveals a cohesive trajectory: evolving from foundational safe control (2021-2022) to sophisticated risk-aware frameworks (2023-2024) that incorporate social compliance and learning. Her work consistently targets high-impact applications in autonomous vehicles while maintaining theoretical rigor, with 7 papers receiving best paper awards or nominations since 2021. Her exceptional contributions have been recognized through: MIT EECS Rising Star (2024) - top global early-career honor IEEE/ACM Human-Robot Interaction Pioneer designation (2024) Qualcomm Innovation Fellowship (2023) Multiple best paper awards at ICRA, IROS, and AAMAS venues Professor Lyu actively builds her research group, having welcomed her first PhD student in August 2025. Her competitive fellowship funding and rapid publication record indicate strong grant support potential. She serves on editorial boards (ICRA 2026 Associate Editor) and professional committees (Junior Co-chair, Multi-Robot Systems Technical Committee), demonstrating growing leadership in the robotics community. As a new faculty member, Professor Lyu combines fresh perspective with proven research excellence, offering students unique opportunities to shape the future of safe autonomy at the intersection of engineering and social sciences.

• Safe Control
• Verification
• Behavior Planning
• +6 more

Dr. Gemma Williams serves as an Honorary Visiting Lecturer at Brighton and Sussex Medical School (BSMS), University of Sussex, while maintaining key affiliations as an Associate Member of the Heasman Flow Lab at York St John University and a Member of the Westminster Commission on Autism. An interdisciplinary researcher working at the intersection of cognition, linguistics, and critical neurodiversity studies, she centers lived autistic experience to advance social justice through participatory methodologies. Her research program critically examines how neurodivergent experiences are shaped by social, sensory, and structural contexts. Core interests include autistic communication (particularly the Double Empathy Problem), healthcare access barriers, loneliness and belonging, sensory environment design, autistic reproductive health, and flow states. She employs qualitative, creative, and autoethnographic methods—always co-produced with neurodivergent communities—to develop frameworks promoting neurodivergent flourishing rather than pathologization. Dr. Williams' publication record demonstrates significant impact across academic and practical domains. Her work appears in leading journals including Autism , Neurodiversity , and Journal of Pragmatics , with recent articles establishing foundational concepts in autistic flow theory and co-created research models. She has authored the influential monograph Understanding Others in a Neurodiverse World (2024) and is finalizing Neurodiversity in English Language Teaching: A Primer (2026). Scientific recognition includes: ESRC Postdoctoral Fellowship in Social Policy Her research translation extends beyond academia through commissioned reports for NHS England, the National Development Team for Inclusion, and international organizations. She actively supervises graduate researchers and delivers professional training to healthcare systems globally. Current projects include co-leading the 'Time for Autism' programme at BSMS and contributing to the Heasman Flow Lab's investigations of autistic wellbeing. Dr. Williams operates research-practice integration through her consultancy, translating findings into organizational change via workshops, accessibility audits, and policy development—demonstrating how academic rigor directly improves neurodivergent lived experience.

• Neurodiversity
• Autism
• Qualitative Research
• +7 more