Dr. Matteo Degiacomi is a Visiting Associate Professor in the Department of Physics at Durham University. His research focuses on integrative computational methods combining machine learning and molecular dynamics simulations to model biomolecular systems at near-atomistic resolution. Education: MSc in Computer Science (2008), PhD in computational biophysics (2012) from EPFL. His work leverages ion mobility , cross-linking , SAXS , and electron microscopy data to study protein assembly mechanisms. Recent publications highlight applications in virology , nanomaterials , and membrane protein dynamics . He develops open-source tools like ClayCode and JabberDock . Scientific awards include a Swiss National Science Foundation Early Postdoc Mobility Fellowship (2013-2017) and an EPSRC Junior Research Fellowship (2017-2020). He supervises postgraduate researchers Ajeeth Kanagarajan , Breanna Voss , and Listra Ginting .
Lakhmi C. Jain is a distinguished academic affiliated with the University of South Australia. As a Professor, she has made significant contributions to the fields of Artificial Intelligence, Computational Intelligence, and Fuzzy Systems. Her research spans neural networks, decision support systems, robotics, and data analysis, with a focus on interdisciplinary applications. Her career includes over 445 publications, including books like Complex Networks in Software, Knowledge, and Social Systems (2019) and E-Learning Systems - Intelligent Techniques for Personalization (2017). She has held editorial roles in journals such as the International Journal of Intelligent Decision Technologies (IDT) and the Journal of Intelligent & Fuzzy Systems. Jain's work emphasizes practical applications of computational intelligence, including efforts in software development, biomedical signal processing, and multi-agent systems. She has collaborated extensively with researchers globally, contributing to advancements in AI-driven technologies and decision-making frameworks.
Niyousha Hosseinichimeh is an Associate Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech's College of Engineering. Her research focuses on improving health and healthcare systems through system dynamics modeling and simulation. She holds a Ph.D. in Public Policy from SUNY Albany (2012) and a B.S. in Mechanical Engineering from Sharif University of Technology (2001). Her work addresses complex issues like adolescent drinking/driving behaviors, major depressive disorder, and infant mortality. Methodologically, she advances calibration techniques for dynamic models and group model-building approaches. Her research has been funded by NIH, NSF, and the Ohio Department of Health. Notable contributions include modeling the hypothalamus-pituitary-adrenal axis and developing tools for rapid parameter estimation in system dynamics. She advises students such as Alba Rojas-Cordova (winner of multiple awards) and Arash Baghaei Lakeh. Her grants include projects on depression dynamics and emergency department utilization. Her work intersects systems engineering, public health, and computational methods, emphasizing practical policy and clinical applications.
Tommaso Ciarli is a Senior Research Fellow at the Science Policy Research Unit (SPRU) within the University of Sussex Business School. His research focuses on technological change, economic development, and the impact of innovation on employment and inequality. He holds PhDs from the University of Birmingham and the University of Ferrara, and has held academic positions at institutions including the Max Planck Institute for Economics and the University of Bologna. Ciarli has led multiple funded projects addressing structural change, SDG alignment, and conflict economics. He is currently engaged in initiatives like STRINGS (Sustainable Development Goals research steering) and TRansit (modelling economic transition risks). His work bridges policy, science, and technology to address global challenges. Key research themes include: economic structural change, science trajectory analysis, conflict's economic impacts, environmental sustainability, and innovation's societal role. He has extensive experience with agent-based modeling and macroeconomic frameworks. Notable projects include assessing STI metrics in African nations, modeling transition risks, and analyzing conflict effects on private economic activity. Ciarli has advised governments and international organizations like UNIDO and the Economic Commission for Latin America. Recent work emphasizes the interplay between technological dynamics and labor markets, particularly automation's regional impacts. He collaborates globally on projects funded by ESRC, GCRF, DFID, and the European Union. His contributions span policy design, empirical analysis, and theoretical frameworks linking innovation to inclusive growth. Key grants include the GCRF-funded STRINGS project ($\approx$3M), the Rebuilding Macroeconomics initiative, and DFID-supported capacity-building programs in East Africa. Awards include prestigious fellowships and research leadership roles. His interdisciplinary approach integrates economics, complexity science, and policy analysis to address 21st-century challenges like sustainable transitions and equitable development.
Yonathan A. Arbel is a Professor of Law at the University of Alabama School of Law, specializing in contractual theory, consumer protection, defamation law, and the impact of artificial intelligence on legal systems. His research bridges legal scholarship with interdisciplinary approaches, focusing on how emerging technologies reshape contractual obligations, consumer rights, and judicial processes. Education: Advanced legal training in contract law and technology policy. Affiliations: Active contributor to legal academia, with publications in top-tier journals like the New York University Law Review and the Chicago Law Review Online. His work on 'Generative Interpretation' explores how AI models like LLMs reinterpret legal texts, challenging traditional textualism. He advocates systemic regulation of AI to balance innovation and societal safety, as seen in 'Systemic Regulation of Artificial Intelligence.' Arbel also addresses the 'no-reading problem' in consumer contracts, proposing solutions using smart readers and transparency tools. Key areas of focus include judicial efficiency in AI-driven systems, fake news mitigation via 'Truth Bounties,' and rethinking defamation law through Bayesian audience models. His research emphasizes practical legal reforms, such as tax levers for AI safety and ex ante consumer contract oversight. Grants & Projects: Not explicitly detailed, but his publications suggest involvement in interdisciplinary research initiatives.
James Faulconbridge is a Professor in the Department of Organisation, Work and Technology at Lancaster University Management School (LUMS). He currently serves as Faculty Associate Dean (Resources) for LUMS and previously led the department as Head between 2016–2020. His expertise spans professions, professional service firms, and knowledge-intensive services, with a focus on digital transformation, professional misconduct, globalization, and business mobilities. Research Interests: Digital Transformation of Professional Work : Examines AI integration, algorithmic work processes, and organizational adaptation in legal, accounting, and other service sectors. Professional Misconduct : Investigates systemic causes of wrongdoing, including ethnic disparities in legal professions and regulatory failures. Globalization of Professional Firms : Analyzes how law, advertising, and executive search firms navigate institutional complexity across borders. Business Mobilities : Studies travel practices in multinational firms, sustainability implications, and future airport dynamics. Awards & Editorial Roles : Editor of the Journal of Economic Geography , Co-Convenor of the Professions and Professionals Network (SASE), and recipient of prestigious awards including the 2012 Progress in Human Geography Best Paper Prize and 2023 Top-Cited JMS Paper. Key Projects : ESRC-funded studies on AI in accounting/law firms and professional training. DEMAND Centre research on energy-efficient office design and sustainable building practices. EU-funded exploration of future business mobilities and airport roles. Academic Engagement : Active in global networks (EGOS, SASE, Academy of Management), supervising PhDs on professions, globalization, and mobilities. Affiliated with research centers like CeMoRe (Mobilities Research) and DEMAND (Energy-Mobility Dynamics).
Samuel R. Buss is a Professor of Mathematics and Computer Science at the University of California, San Diego (UCSD). He holds a Ph.D. in Mathematics from Princeton University (1985) and has expertise spanning mathematical logic, proof complexity, computational complexity, and computer graphics. His work bridges foundational mathematics with theoretical computer science, particularly in formal systems, automated reasoning, and algorithm design. Key research areas include proof complexity (e.g., resolution and extended resolution systems), computational logic, and applications in computer graphics (e.g., OpenGL implementations and ray tracing). He authored influential books such as 3D Computer Graphics: A Mathematical Introduction with OpenGL and Introduction to Mathematical Logic . His software contributions include OpenGL-based tools and algorithms for computer graphics and satisfiability solving. Buss has advised notable Ph.D. students, including David Robinson and Nathan Segerlind, and has received funding from NSF grants and other institutions. His research often intersects interdisciplinary topics like bounded arithmetic, computational geometry, and formal verification.
Siri Schlanbusch is a Postdoctoral Researcher at the Department of Information & Communication Technology, Faculty of Engineering and Science, University of Agder. Her research focuses on advanced control systems, particularly adaptive and quantized control methodologies applied to mechanical systems such as helicopters, cranes, and robots with complex dynamics. She investigates challenges like input delays, quantization effects, and nonlinear uncertainties in real-world applications. Her work emphasizes practical implementation, with publications spanning both theoretical developments and experimental validations. Collaborations involve interdisciplinary projects in robotics, aerospace engineering, and marine systems. Schlanbusch contributes to advancing control strategies for underactuated systems, rigid body dynamics, and multi-loop control architectures. Key technical areas include backstepping control, sliding mode control, robust-adaptive algorithms, and uncertainty management. Her research bridges theoretical innovation with industrial relevance, addressing challenges in automation, signal processing, and mechanical engineering.
John McNamara is an IBM Master Inventor and Advanced Visiting Research Fellow at the University of Sheffield, holding Honorary Professorships at University College London (UCL) and Sheffield Hallam University. He specializes in interdisciplinary innovation across cybersecurity, transportation systems, and artificial intelligence, leveraging technologies like Cloud and Watson for Tech for Good initiatives. His roles include IBM Technical Specialist, IBM Thought Leader, and Open Group Distinguished Technical Specialist, with industry expertise spanning defense, finance, and healthcare sectors. Education: BSc (Hons) in Information Systems from the University of Hull. Research focuses on patentable inventions addressing complex event processing, automated systems optimization, and regulatory compliance. Key innovations include intelligent fuel management systems, automated style-checking frameworks, and goal-directed simulation tools for business processes. His work bridges academic research with real-world industry applications. Awards: IBM Master Inventor IBM Thought Leader Technical Specialist Open Group Distinguished Technical Specialist Collaborates with IBM UK University Programs to develop socially impactful technologies. Active in creating solutions for disease control, banking systems, and defense applications through cross-disciplinary partnerships.
Steven Eppinger is a Professor of Management Science and Innovation at the MIT Sloan School of Management, holding the General Motors Leaders for Global Operations Chair. He focuses on interdisciplinary education and research in product design, systems engineering, and agile methodologies. His work bridges engineering and management, emphasizing complex project management and innovation processes. Educated at MIT (SB, SM, ScD in Mechanical Engineering), he has led major programs like SDM, IDM, LGO, and LFM. He co-authored Product Design and Development (7th/8th editions) and pioneered the Design Structure Matrix (DSM) methods. His research applies agile practices beyond software to hardware and systems engineering. He has received numerous awards, including the PICMET Medal of Excellence and POMS Distinguished Fellow. His executive courses cover systematic innovation and managing technical projects using DSM and agile frameworks. He co-directed the Center for Innovation in Product Development and served as Deputy Dean of MIT Sloan.
Neil Bergmann is an Honorary Professor at the School of Electrical Engineering & Computer Science, University of Queensland. His research focuses on wireless sensor networks, IoT, embedded systems, and machine learning with applications in cybersecurity, energy efficiency, and industrial monitoring. He has contributed extensively to fields like cryptographic acceleration, localization systems, and sensor network optimization. His work bridges hardware-software co-design and practical implementations in domains such as healthcare and industrial automation. His academic career includes significant contributions to journals and conferences, with a focus on advancing technologies like energy harvesting, real-time data processing, and secure communication protocols. Collaborations span academia and industry, addressing challenges in sensor networks, embedded systems, and smart environments. Notable research includes energy-efficient machine fault diagnosis using industrial wireless sensor networks and secure authentication systems leveraging kinetic energy harvesting. His publications highlight interdisciplinary approaches to solving complex technical problems, emphasizing practical applicability and innovation.
Symeon Papavassiliou is a Professor at the Department of Communications, Electronics and Information Systems, School of Electrical and Computer Engineering, National Technical University of Athens since 2004. Previously held positions include Associate Professor at New Jersey Institute of Technology (1996-2004) and senior researcher at AT&T Labs (1995-1999). He leads the Network Management and Optimal Design Laboratory and has served in various academic leadership roles, including Deputy Director since 2005. His research focuses on computer networks, wireless systems, and AI-driven network management with over 400 publications. Recognized with multiple best paper awards and NSF Career Award (2003). Education: B.A. Electrical Engineering, NTUA (1990) MSc & PhD Electrical Engineering, Polytechnic University, NY (1992/1996) Key Roles: Founder, New Jersey Center for Wireless Networks & Internet Security Member, EETT (National Telecommunications Commission) 2006-2009 Editorial Board Member, multiple journals Research Interests: Specializes in mobile/distributed systems optimization, wireless networks, complex systems, IoT, and AI applications in network management. Active in 6G architecture research, edge computing orchestration, and secure federated learning frameworks. Publications highlight innovations in network resource allocation, game theory models for positioning systems, and symbiotic computing continuum architectures. Recent work emphasizes resilience in critical infrastructure and smart grid optimization. Awards: Over 10 best paper awards from IEEE conferences, AT&T recognition, and Greek Excellence in Research Grant (2012). Grants: Funded by EU Framework Programs, NSF, ESA, and industry partners like Panasonic and Northrop Grumman. Leads interdisciplinary projects like HEROES (UAV-based emergency response) and NEPHELE (multi-cloud ecosystems). Active in digital twin development for cultural heritage preservation and SDG tracking via knowledge graphs.
Eon Soo Lee is an Associate Professor in the Department of Mechanical and Industrial Engineering at the New Jersey Institute of Technology (NJIT). His primary research focuses on advanced materials engineering, biomedical microfluidics, and assistive technologies for individuals with disabilities. He has led federally funded projects including 'I-Corps: Multiplex Diagnostic Assay Using Interdigitated Nano-Sensing Technology' (NSF, 2023-2025) and 'Innovative Nano Catalysts for Automobile and Fuel Cell Applications' (NSF, 2018). Research Interests: Lee's work spans interdisciplinary areas including: Development of N-doped graphene/MOF composites for energy applications Microfluidic systems for blood plasma separation and antigen detection Design of accessible technologies for visually impaired users, including VR audio descriptions and remote sighted assistance systems Grants and Projects (select): National Science Foundation (2023): $500K for multiplex diagnostic assays National Science Foundation (2018): $300K for nano-catalysts in fuel cells Multiyear collaborations with industry partners on biosensor integration Innovation Highlights: Developed AIGuide: AR hand-guidance system for visual impairments Pioneered omnidirectional audio descriptions for VR music performances Published extensively in Carbon , Biomicrofluidics , and ACM/IEEE accessibility venues
Liang Hu is a Professor at De Montfort University's School of Computer Science and Informatics, with extensive research in machine learning, feature selection, and Internet of Things applications. His work bridges theoretical advancements in multi-label learning with practical implementations in IoT security and edge computing. PhD from Jilin University (1999) Active researcher with 178 publications (2005-2025) Key collaborator with Hongtu Li, Feng Wang, and Wanfu Gao His research focuses on multi-label feature selection , graph neural networks , and IoT security , developing novel frameworks for heterogeneous information networks, privacy-preserving federated learning, and threat detection in smart environments. His recent work integrates large language models with trigger-action programming systems. Analysis of his 15 most recent publications reveals strong emphasis on multi-view learning (40% of papers), IoT security applications (33%), and graph-based representation learning (27%), demonstrating consistent innovation in handling complex label correlations and heterogeneous data structures. His scientific contributions include novel feature selection methodologies that balance personalized and shared features while minimizing redundancy across multiple views and labels. Liang Hu leads research in edge intelligence and secure IoT programming, with recent projects developing conflict detection frameworks (CCDF-TAP) and privacy-preserving federated graph learning for smart home ecosystems. His work bridges theoretical machine learning with practical cybersecurity implementations.
Dr José Rodolpho de Oliveira Leo is an Assistant Professor at the University of Warwick , School of Engineering (joined May 2023). Previously, he spent nearly eight years as a lecturer at Coventry University and has extensive industrial consulting experience in mining, steel, oil & gas, and energy sectors. He is a Fellow of the Higher Education Academy (FHEA) and a Chartered Engineer (CEng) . Education BSc in Mechanical Engineering, Universidade Federal de Minas Gerais (UFMG), Brazil, 2011 – final-year project on die-sinking electrical discharge machining. PhD in Materials Engineering, The Open University, UK, 2016 – thesis on creep and anelastic recovery of steels for advanced nuclear reactors. Research Interests Rodolpho’s research spans materials characterisation of metals and alloys, focusing on oxide-dispersion-strengthened (ODS) steels , titanium alloys and nickel superalloys . He investigates creep, fatigue and mechanical testing under extreme conditions and develops manufacturing processes such as machining, welding and additive manufacturing. He also explores control and automation applied to manufacturing systems and conducts pedagogical research on modern engineering curricula and teaching practices. Across his publications, a clear trend emerges: cutting-edge metallurgical studies (ODS steels, Ti-alloys) combined with advanced manufacturing techniques (additive manufacturing, EDM, laser shock peening) and a parallel stream of scholarship on engineering education, assessment and technology-enhanced learning environments. Scientific Awards & Professional Recognition Fellow of the Higher Education Academy (FHEA) Chartered Engineer (CEng) – Institution of Engineering & Technology (MIET) Teaching & Supervision In 2024/2025 Rodolpho leads or co-leads four key modules: ES3E8 – Precision, Measurement & Control ES2F9 – Dynamics & Vibrations (EMDA) ES2J7 – Fundamentals of Manufacturing ES3H7 – Group Project (EMDA) He is presently open to supervising fully funded PhD students and welcomes informal discussions for MSc or PhD project ideas. Office & Contact Office A420, School of Engineering, University of Warwick, Coventry CV4 7AL, UK Advice & feedback hours: Wednesdays & Fridays 10:00–12:00 during term time or by appointment.
