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Kristian HelinView profile

Professor

• Cancer biology
• Epigenetics
• Stem cells
• +5 more

Kristian Helin is Chief Executive and President of The Institute of Cancer Research (ICR), London, and a Professor with affiliations at the University of Copenhagen and Memorial Sloan Kettering Cancer Center. He founded/directed the Biotech Research & Innovation Centre (BRIC), Centre for Epigenetics, and Danish Stem Cell Center. His research focuses on epigenetic regulation, cancer biology, and stem cell differentiation. Education: Ph.D. Molecular Biology, University of Copenhagen (1991) M.Sc. Chemical Engineering, Technical University of Denmark (1988) Research Interests: Helin's work deciphers molecular mechanisms in cancer, emphasizing epigenetic drivers (e.g., H3K4/H3K36 methylation), transcriptional control, and therapeutic targeting. His lab identified E2F transcription factors, linked epigenetic dysregulation to leukemia/lymphoma, and develops drugs targeting kinases/epigenetic enzymes. Research spans acute myeloid leukemia, B-cell lymphoma, and solid tumors using CRISPR screens and preclinical models. Publication Trends: Recent articles (2023-2025) focus on epigenetic therapy, chromatin remodeling, and kinase signaling in cancer. Key themes include targeting NSD1/KDM5C/RIOK2 enzymes, combination therapies (EZH2/DOT1L inhibitors), and metabolic regulation in leukemia. Studies bridge basic mechanisms (enhancer regulation, insulator accessibility) with translational applications. Awards: Anders Jahre Prize (2014), ERC Advanced Grant (2011), Novo Nordisk Prize (2008) Memberships: Academia Europaea, Royal Danish Academy, EMBO Leadership: Helin co-founded EpiTherapeutics (acquired by Gilead) and leads the Epigenetics and Cancer lab at ICR. His team investigates AML pathogenesis and chromatin complexes like HUSH/NURF. Grants include ERC funding and innovation prizes.

• Numerical Mathematics
• Finite Element Analysis
• Optimal Control
• +3 more

Richard Franz Löscher is a researcher at the Institute of Applied Mathematics specializing in numerical methods for optimal control problems. He holds a BSc, Diplom-Ingenieur (Dipl.-Ing.), and Doctorate in Technical Sciences (Dr.techn.), demonstrating extensive technical education and engineering expertise. His educational qualifications include: BSc Diploma in Engineering (Dipl.-Ing.) Doctorate in Technical Sciences (Dr.techn.) Löscher's research centers on numerical mathematics with deep specialization in finite element methodologies for distributed optimal control problems governed by partial differential equations. His work addresses elliptic, parabolic, and hyperbolic control systems through regularization techniques, adaptive mesh refinement, and robust solver development. Key innovations include variable energy regularization frameworks, mass-lumping discretizations, and complexity-optimal space-time finite element systems that significantly advance computational efficiency and error estimation in constrained control environments. Analysis of his 2024-2026 publications reveals a cohesive research trajectory focused on overcoming computational bottlenecks in optimal control. His work consistently bridges theoretical rigor with practical implementation, emphasizing discretization schemes that balance accuracy and computational cost while addressing state/control constraints across diverse PDE systems. No scientific awards or honors were documented in available sources. Löscher maintains active research collaborations with prominent figures including Ulrich Langer and Olaf Steinbach, evidenced by co-authored publications and peer-review activities for journals like Journal of Computational and Applied Mathematics. His external research engagement includes a July 2024 visit to Delft University of Technology, highlighting international academic partnerships.

Lam JamesView profile

Professor

• Networked control systems
• Vibration control
• Control theory
• +7 more

Lam James is a Chair Professor of Control Engineering at the University of Hong Kong (HKU), affiliated with the Faculty of Engineering. He holds a BSc (1st Hons.) in Mechanical Engineering from the University of Manchester, and MPhil/PhD degrees from the University of Cambridge. His academic journey includes roles as a Croucher Fellow, Lecturer at the University of Melbourne, and faculty member at City University of Hong Kong before joining HKU in 1993. Professor Lam serves as Editor-in-Chief for four international journals including IET Control Theory and Applications and Journal of The Franklin Institute . His research focuses on networked control systems, vibration control, control theory, and multi-agent systems. With 600+ peer-reviewed publications, he maintains an H-index of 102 (Web of Science) and 108 (Scopus), recognized as a Highly Cited Researcher in multiple fields. Education: BSc Manchester (Mechanical Engineering), MPhil/PhD Cambridge Editorial Roles: 20+ journals, including leadership roles since 2012 His awards include Foreign Membership of Academia Europaea (2024), National Academy of Artificial Intelligence membership (2025), and two State Natural Science Awards (2015, 2019). He is a Fellow of multiple institutions including IEEE, IMechE, and HKIE.

Yunjie YangView profile

Associate Professor

• AI-powered sensing and imaging
• Machine learning
• Soft sensors & electronics for robotics
• +5 more

Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.

• Dependable Distributed Systems
• Web Engineering
• Convergence of Voice and Data
• +5 more

Karl Michael Göschka is an Associate Professor at Vienna University of Technology (TU Wien) in the Department of Distributed Systems (E194-02) within the Faculty of Computer Science. His academic title of Privatdozent indicates he has completed habilitation, the highest academic qualification in the German/Austrian system. He maintains an active research and teaching profile with courses scheduled through 2026S, including Bachelor Thesis supervision, Computer Science Projects, and PhD Seminars. His research spans over two decades with consistent publications from 2004 to 2022. Göschka's primary research interests focus on Dependable Distributed Systems, Web Engineering, and the convergence of voice and data technologies. His work demonstrates particular expertise in middleware, service-oriented architecture, wireless sensor networks, and fault tolerance mechanisms. He has supervised numerous master's and diploma theses since 2006, with his most recent doctoral supervision completed in 2022. Göschka's publication record shows a clear evolution from foundational work in distributed systems and replication (2004-2013) to more recent contributions in wireless sensor networks and dependable computing (2020-2022). His research consistently addresses the challenge of balancing dependability, performance, and security in distributed environments, with notable contributions in temporal decoupling techniques and adaptive systems. GIT-Preis des Österreichischen Vereins für Elektrotechnik (1999) Würdigungspreis des Ministeriums für Wissenschaft und Forschung (1998) GIT-Förderpreis des Österreichischen Vereins für Elektrotechnik (1994) Göschka has led and participated in multiple significant research projects including TRADE (2008-2011) on adaptive performance optimization, COMPASS (2005-2007) for automotive software systems, S-Cube (2008-2012), ALL-TIMES (2007-2010), and DeDiSys (2004-2007) on dependable distributed systems. His research has strong practical applications in automotive systems, online auctions, and critical infrastructure monitoring.

Wolfgang KunzView profile

Professor

• Hardware Safety and Security
• Formal Hardware Verification
• Embedded Computing Systems
• +5 more

Wolfgang Kunz is a Full Professor (C4, W3) and Chair of Electronic Design Automation at the Technische Universität Kaiserslautern since 2001. His academic career spans multiple prestigious institutions, including Goethe-University Frankfurt/Main and the University of Massachusetts, Amherst. He has held leadership roles such as Dean (2005-2007) and Vice-Dean (2007-2009) at TU Kaiserslautern. Habilitation (Dr. rer. nat. habil.), Computer Science, University of Potsdam (1996) Doctoral degree (Dr.-Ing.), Electrical Engineering, University of Hannover (1992) Dipl.-Ing. degree, Karlsruhe Institute of Technology (1989) His research focuses on hardware verification, security, and optimization, particularly in embedded systems and processors. His work on formal verification methods has been commercialized by companies like Synopsys, Mentor Graphics, and Siemens EDA. His 2016-2021 publications address critical security issues such as Spectre/Meltdown and introduce innovative verification frameworks adopted by industry leaders like Infineon and OneSpin Solutions. Scientific awards include the IEEE Fellow (2006), German IT Society Award (2005), and TU Kaiserslautern Distinguished Teaching Award (2016). He has served on editorial boards of major journals and coordinated the Erasmus Mundus European Master Program in Embedded Computing Systems since 2010. Key students: Jörg Bormann, Raik Brinkmann, Tobias Ludwig Collaborations: Siemens EDA, Infineon, AbsInt, Intel SCAP Spin-offs: LUBIS EDA, OneSpin Solutions

Marta Zofia KwiatkowskaView profile

Professor

• Automated verification
• Probabilistic model checking
• Temporal logics
• +3 more

Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.

• Computer Vision
• Autonomous Driving
• Robotics
• +7 more

Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools

Li BaowenView profile

Professor

• Phononics
• Thermal Metamaterials
• Nano Heat Transfer
• +2 more

Dr. Li Baowen is Chair Professor at Southern University of Science and Technology (SUSTech) with joint appointments in the Department of Physics and Department of Materials Science and Engineering. A pioneer in phononics and thermal metamaterials, he previously held endowed professorships at University of Colorado Boulder and UC Berkeley. His research focuses on controlling heat transfer at nano scales, developing thermal metamaterials like thermal cloaks, and applying complex networks to physical systems. Dr. Li has published over 400 papers including 3 in Reviews of Modern Physics and 30 in Physical Review Letters, with more than 34,800 citations (H-index 98). He is recognized with the Brillouin Medal from the International Phononics Society and is a Fellow of the American Physical Society. He founded research centers including the China-EU Joint Lab for Nanophononics at Tongji University. His current research explores quantum phononics, machine learning applications in thermal materials, phonon lasers, and quantum sensing technologies.

Didier SornetteView profile

Professor

• Prediction of social, commercial and marketing success
• Hawkes process
• Financial crisis observatory
• +14 more

Didier Sornette is Professor on the Chair of Entrepreneurial Risks at ETH Zurich since 2006, with concurrent affiliations as Professor at the Swiss Finance Institute, Special Professor at Tokyo Tech's Institute of Innovative Research, and Chair Professor (part-time) at Southern University of Science and Technology (SUSTech) in China. He founded the Financial Crisis Observatory (FCO) in 2008 to rigorously test financial market predictability during bubbles and co-developed the collaborative platform xYotta since 2012. Research Focus: Predictability and control of crises in complex systems, including financial crashes, earthquakes, social network dynamics, and medical applications (immune systems, epilepsy). Key Concept: Coined 'Dragon-kings' to describe extreme events with identifiable precursors, emphasizing their predictability. Scientific Awards AAAS Fellow (2013) Member of the Swiss Academy of Engineering Sciences (2019) E. N. Lorenz Lecture (2010), Ehrenfest Colloquium (2011) He has mentored 36 PhD students, supervised 120 master theses, and guided 38 post-docs (as of December 2019).

Peng ShigeView profile

Professor

• Nonlinear expectations and stochastic calculus
• Probability theory
• Nonlinear partial differential equations
• +5 more

Peng Shige is a Professor of 1st class at the School of Mathematics, Shandong University, China. He has held the Distinguished Professor title under the Ministry of Education (Cheung Kong Scholarship) since 1999. His academic journey includes degrees from Shandong University (Physics diploma, 1971-1974), Paris-IX (1985), and Aix-Marseille University (PhD 1986, Habilitation 1992). Research focuses on nonlinear expectations, stochastic calculus, partial differential equations, and financial mathematics. Key contributions include foundational work on backward stochastic differential equations (BSDEs), the g-expectation framework, and the G-expectation theory extending probability axioms to nonlinear settings. These innovations have advanced stochastic control, financial risk modeling, and differential games. Honors include the 2020 Future Science Award, 2011 Princeton Global Scholar, and 2005 Chinese Academy of Sciences Academician status. He delivered a plenary lecture at the 2010 International Congress of Mathematicians. Peng's work integrates theoretical breakthroughs with applied domains like financial engineering. His research has been widely cited (~8k citations) and shaped modern stochastic analysis methodologies.

• Microbial Biofilms
• Environmental Microbiology
• Antibiofilm Drug Development
• +4 more

Staffan Kjelleberg is a Distinguished University Professor at Nanyang Technological University (NTU), Singapore, and Director of the Singapore National Biofilm Consortium (SNBC) and Singapore Centre for Environmental Life Sciences Engineering (SCELSE). He holds previous positions as Scientia Professor at the University of New South Wales (UNSW), Australia, and has led major research initiatives globally. His academic career spans over four decades, with roles including Head of School at UNSW and Professorships at the University of Gothenburg, Sweden. Education: BSc (Chemistry and Biology, 1975), PhD (Microbiology, 1981), and Docent (Microbiology, 1983) from the University of Gothenburg. He has authored over 384 journal papers with significant citations, reflecting his leadership in microbial biofilm research. Research focuses on microbial biofilms and microbiomes, addressing environmental sustainability, public health, and industrial applications. He employs an interdisciplinary approach to study biofilm community dynamics, matrix properties, and translational technologies for biofilm control. Key contributions include discoveries on quorum sensing inhibitors, biofilm dispersal mechanisms, and eDNA roles in biofilm structure. Honours include Fellowships from the Australian and American Academies of Microbiology, Web of Science Highly Cited Researcher status, and Editor roles for 15 international journals. He leads major programs like the Marine Climate Change Science initiative and has co-directed global research centers such as the Centre for Marine Bio-Innovation. Advising and grants: While specific student names are not listed, his extensive leadership in research programs indicates mentorship of numerous scholars. His work bridges fundamental and applied microbiology, impacting environmental and biomedical fields. Labs/Teams: Directs SCELSE and SNBC, co-founded the Centre for Marine Bio-Innovation, and collaborates internationally on biofilm and microbiome research.

Philip PooleView profile

Professor

• Nitrogen Fixation
• Plant-Microbe Interactions
• Rhizosphere Microbiology
• +3 more

Philip Poole is a Professor of Plant Microbiology at the University of Oxford's Department of Plant Sciences and Senior Research Fellow at Somerville College. His research focuses on plant-microbe interactions, nitrogen fixation, and rhizosphere microbiology. He has led major international projects including the BBSRC-NSF Synthetic Symbioses program (2014-2019) and the India-UK Nitrogen Fixation Consortium (2016-2019). With 26 grants as PI from the UK's BBSRC, he has secured over £10.5 million in funding. His work includes pioneering bacterial Lux biosensors for metabolite analysis, transcriptomics under sterile conditions, and metatranscriptomics in soil to study microbiome-plant interactions. Current projects model nitrogen fixation biochemistry in legume nodules and investigate rhizobia lifecycle transitions from rhizosphere colonization to symbiotic bacteroid differentiation. He co-directs the Oxford Centre for Plants for the 21st Century and serves on editorial/advisory boards for Microbiology UK, The Journal of Bacteriology, and Pivot Bio. His contributions include elucidating the ammonia-alanine pathway for nitrogen secretion and demonstrating symbiotic auxotrophy dependencies in bacteroids. Key achievements include developing global mutagenesis strategies (INSeq) and advancing understanding of microbial community structures in the rhizosphere. His research integrates molecular, genetic, and systems biology approaches to address global challenges in sustainable agriculture.

Yao LiangzhongView profile

Professor

• Renewable Energy Grid Integration
• Smart Grid
• HVDC Grid Control
• +4 more

Liangzhong Yao is a Professor and Director of the Smart Grid Research Institute at Wuhan University, China. He holds dual roles as Fellow of IEEE and IET, and has served in leadership positions such as Vice President of China Electric Power Research Institute (CEPRI) and Chair of IEC TC122. His expertise spans renewable energy grid integration, HVDC systems, smart grid technologies, and energy storage. Yao has led over 25 years of R&D projects with combined funding exceeding GBP 20 million and RMB 90 million, resulting in applied technologies in wind farms and HVDC grids. He has been awarded over 10 national and international accolades, including the IEC 1906 Standard Award and China Science and Technology Innovation Awards. Research focuses include AC-DC hybrid systems, distributed energy resource integration, and high-renewable energy grid operation. He has authored/co-authored 350+ publications, 60+ patents, and 4 books. Yao currently supervises 8 PhD and 10 Master's students, and serves on editorial boards of journals like CSEE Journal of Power Energy & Systems. His leadership roles in global standards bodies like IEC and CIGRE further highlight his contributions to advancing electrical engineering standards and practices.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +4 more

Olaf Steinbach is a University Professor (Univ.-Prof.) at the Institute of Applied Mathematics at Graz University of Technology. His academic career spans over three decades with continuous research activity from 1992 to the present, including publications scheduled for 2026. He serves as a project manager for several research initiatives including the Special Research Area (SFB) F90 Computational Electric Machine Laboratory, which runs from 2022 to 2026. Professor Steinbach's research interests primarily focus on Numerical Analysis and Computational Mathematics . His work centers around developing and analyzing advanced numerical methods, particularly Finite Element Methods (FEM) and Boundary Element Methods (BEM), for solving partial differential equations (PDEs) and optimal control problems. His research spans both theoretical aspects (such as error analysis, stability, and convergence) and practical applications (including electric machines, electromagnetics, and biomechanics). He has made significant contributions to space-time finite element methods, which treat time as an additional dimension in the discretization process, leading to more robust and efficient solvers for time-dependent problems. Analysis of his recent publications (2021-2026) reveals a strong focus on optimal control problems governed by partial differential equations, with particular emphasis on elliptic, parabolic, and hyperbolic PDEs. His work demonstrates a consistent pattern of developing robust numerical methods with rigorous error analysis, often incorporating regularization techniques to handle challenging constraints. The applications span computational electromagnetics (particularly electric machines), fluid dynamics, and wave propagation problems. His research increasingly incorporates advanced computational techniques including parallel computing and isogeometric analysis. Professor Steinbach has supervised numerous doctoral students and has been actively involved in organizing academic events, including summer schools on Boundary Element Methods. His collaborative network extends across multiple disciplines and institutions, reflecting the interdisciplinary nature of his work in computational mathematics. His research has been supported through multiple significant projects including DK-W1244 Doctoral Program on Partial Differential Equations, the EU CASOPT project on optimization of industrial devices, and the ongoing Special Research Area on Computational Electric Machine Laboratory. These projects demonstrate his leadership in establishing research frameworks that bridge theoretical mathematics with practical engineering applications. Professor Steinbach maintains an active research group within the Institute of Applied Mathematics, collaborating closely with researchers in computational engineering, electrical engineering, and biomechanics. His work on the Computational Electric Machine Laboratory represents a particularly strong interdisciplinary effort combining mathematical theory with electrical engineering applications.