جست‌وجوی استاد و پژوهشگر

Sabine Brunswickerمشاهده پروفایل

استاد

• Digital Innovation
• Artificial Intelligence
• Autonomous Systems
• +۴ مورد دیگر

Prof. Sabine Brunswicker is a Full Professor at Purdue University's Polytechnic Institute, Founder and Director of the interdisciplinary center for Artificial Intelligence for Digital, Autonomous and Augmented Aviation, and Director of the Research Center for Open Digital Innovation (RCODI). Previously, she served as Visiting Professor at Northwestern Institute for Complex Systems (2022) and ESADE Business School (until 2016), and Head of Open Innovation at Fraunhofer Institute for Industrial Engineering. Education: PhD in Engineering Sciences (with highest honor), University of Stuttgart, Germany (2011) MSc in Engineering & Management Sciences, University of Technology, Darmstadt, Germany (2005) MCom in Marketing & Consumer Behavior, University of New South Wales, Australia (2005) BSc in Engineering & Management Sciences, University of Technology, Darmstadt, Germany (2001) Research Focus: Brunswicker's work bridges computing, engineering, and behavioral sciences with emphasis on human-AI collaboration. She investigates human-autonomy teaming in drone operations, emotional intelligence in conversational AI for healthcare/legal domains, and organizational systems for open innovation using network science and reinforcement learning. Her research integrates digital transformation frameworks with practical applications in autonomous systems and self-organizing platforms. Scientific Awards: No specific awards were documented in the provided materials. Advising and Collaborations: As a user-inspired researcher, Brunswicker co-founded IMP³rove (innovation capability assessment platform) and launched Purdue IronHacks (data science platform for societal challenges). She maintains active industry partnerships and policy engagement, though specific student advisees and grant portfolios weren't detailed in the source text. Her work emphasizes real-world problem solving through machine learning and data visualization. Labs and Teams: She leads RCODI and the AI Aviation Center, fostering interdisciplinary collaboration across computing, engineering, and behavioral sciences to advance human-AI teaming in complex operational environments.

Lawrence Lessigمشاهده پروفایل

استاد

• Law and Technology
• Intellectual Property
• Constitutional Law
• +۳ مورد دیگر

Lawrence Lessig is the Roy L. Furman Professor of Law and Leadership at Harvard Law School . He previously taught at Stanford Law School (founding the Center for Internet and Society ) and the University of Chicago. A respected legal scholar, Lessig is also the founder of Equal Citizens and a founding board member of Creative Commons . He serves on the Scientific Board of the AXA Research Fund and is a member of the American Academy of Arts and Sciences and the American Philosophical Society. Education: BA in Economics and BS in Management, University of Pennsylvania MA in Philosophy, Cambridge University JD, Yale Law School Lessig's research bridges law and technology , focusing on intellectual property and internet governance, with recent work on institutional corruption —legal relationships that erode public trust, particularly in democratic systems. His scholarship includes critiques of campaign finance laws and proposals for constitutional reform. Recent publications include The Buckley Overreach (2025), analyzing campaign finance under originalism, and Conversation Networks (2025), exploring digital communication's impact on democracy. Earlier works like The End of End-to-End (2001) established him as a foundational thinker on internet architecture. Scientific awards and honors: Webby Award Free Software Foundation's Freedom Award Scientific American 50 Award Fastcase 50 Award Member, American Academy of Arts and Sciences Member, American Philosophical Society He has advised on constitutional law, notably Republic, Lost (2011) and They Don't Represent Us (2019), and has contributed to debates on digital rights , free culture , and AI ethics .

Nicolas Godboutمشاهده پروفایل

استاد

• Photonics
• Optical Fiber Components
• Quantum Cryptography
• +۶ مورد دیگر

Nicolas Godbout is a Full Professor and Department Director of the Department of Engineering Physics at Polytechnique Montréal. He holds a Ph.D. from Polytechnique Montréal and serves as Head of the Fiber Optics Laboratory and as a Researcher at the Center for Optics, Photonics and Lasers (COPL). His academic leadership extends to teaching courses including Fundamentals of Photonics, Waveguide Optics, Lasers, Quantum Optics, and Current Subjects in Photonics. Dr. Godbout's research spans multiple areas of photonics with particular emphasis on optical fiber components, quantum cryptography, quantum information, optical telecommunications, and nonlinear optics. His work bridges fundamental theoretical investigations with practical applications in telecommunications, biomedical imaging, and quantum technologies. He has made significant contributions to photonic lantern development, quantum key distribution systems, and optical fiber component design. Analysis of his recent publications reveals a strong trend toward interdisciplinary research combining photonics with biomedical applications, quantum information processing, and advanced computational modeling. His work demonstrates consistent innovation in optical fiber technology, with increasing focus on quantum applications and biomedical instrumentation over the past decade. The development of open-source tools like SuPyMode and PyMieSim highlights his commitment to advancing research methodology in the field. $377,000 awarded for Quantum Photonics Quebec projects (2022) Appointment as director of INTRIQ (2019) Dr. Godbout has supervised an extensive number of graduate students, with 9 completed Ph.D. theses and 21 Master's theses under his guidance, plus one currently in progress. His research has been supported by significant funding, including semiconductor research initiatives that received $120 million from the Canadian government as recently as July 2024. He actively collaborates with industry through Castor Optics, a company he co-founded with Professor Caroline Boudoux that specializes in optical fiber components. As Head of the Fiber Optics Laboratory and researcher at COPL, Dr. Godbout leads a dynamic research team focused on advancing photonics technology. His laboratory work spans from fundamental quantum optics research to practical applications in telecommunications and biomedical imaging. Recent activities include significant contributions to semiconductor research initiatives at Polytechnique Montréal, reflecting his leadership in positioning the institution at the forefront of advanced technology development.

Bert de Vriesمشاهده پروفایل

استاد

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +۳ مورد دیگر

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

• Political Science
• Statistics
• Data Analysis
• +۶ مورد دیگر

Dave Armstrong is a Professor and Director of Placement at the University of Western Ontario, holding the Canada Research Chair (CRC). He leads the Centre for Computational and Quantitative Social Science (CCQSS) and earned his PhD from the University of Maryland. His work focuses on statistics, data mining, and political conflict analysis. PhD, University of Maryland Director, Centre for Computational and Quantitative Social Science (CCQSS) His research explores: Non-linearity in statistical models and its impact on effect sizes The Costs of Contention project analyzing political conflict consequences Visualization techniques for pairwise statistical comparisons using Shiny and D3.js Recent publications span urban-rural divides, municipal governance, and statistical methodology. Awards include a five-year Norwegian Social Science Research Council grant (2016), editorial board membership at the American Journal of Political Science (2013), and undergraduate research stipends (2010).

Leonhard Dobuschمشاهده پروفایل

استاد

• Organizational Openness
• Open Strategy
• Intellectual Property Rights
• +۶ مورد دیگر

Leonhard Dobusch is a full Professor of Business Administration with a focus on Organization at the University of Innsbruck's Faculty of Business and Management, specifically within the Institute for Organisation and Learning. He has held this position since February 2016, after serving as a Junior Professor at Freie Universität Berlin from 2012-2016. Professor Dobusch maintains active international collaborations with researchers at institutions including ETH Zurich, University of Oxford, University of Zurich, and University of Duisburg-Essen. University of Innsbruck: Professor of Business Administration (since 2016) Freie Universität Berlin: Junior Professor of Management (2012-2016) Freie Universität Berlin: Postdoc at Chair for Inter-Organizational Cooperation (2009-2012) Stanford Law School: Research Fellow at Center for Internet & Society (2008) Max Planck Institute for Social Research: Postdoc Fellow (2008-2009) Professor Dobusch's research centers on three interconnected areas that challenge conventional organizational thinking. His work on organizational openness examines how principles like open source software, open science, and open innovation manifest in practice, revealing how formal openness often leads to unintended exclusion. His second research stream investigates alternatives to intellectual property rights in regulatory uncertain environments, particularly in pharmaceutical innovation where he studies approaches to vaccine development beyond traditional patent systems. Thirdly, he develops the concept of 'organisationality' to redefine how we understand organization in increasingly fluid social systems. His research has significant implications for companies, public administrations, and scientific institutions navigating the challenges of openness, regulatory uncertainty, and new organizational forms in the digital age. Professor Dobusch's publication record demonstrates consistent high-impact contributions to organizational studies, with articles appearing in top journals including Organization Studies, Journal of Management Studies, and Long Range Planning. His work shows a clear trajectory from studying open source software adoption in city administrations (his doctoral research) to broader questions about organizational forms, openness, and intellectual property in complex systems. 2025: Best Reviewer Award of the Journal Organization Theory 2025: Prof of the Year Award in Rhetoric and Didactics 2022: Best Paper Award of the Strategy Practice Interest Group 2020: Ideas Worth Teaching Award by Aspen Institute for 'Organizing in Times of Crisis' 2020: LehrePlus!-Preis der Universität Innsbruck 2016: LehrePlus!-Preis for 'Open Organizations and Organizing Openness' course Professor Dobusch actively integrates his research into teaching, exemplified by his award-winning wiki-based course 'Open Organizations and Organizing Openness' and the collaborative online course series 'Organizing in Times of Crisis', which received international recognition. He currently leads a three-year DFG/FWF-funded research project 'Organising Creativity under Regulatory Uncertainty: Alternative Approaches to Intellectual Property' with Professor Sigrid Quack. Within professional networks, he serves as Chair of the Executive Board of the Interest Group 'Strategizing Activities and Practices' at the Academy of Management and regularly leads sub-themes at the European Group of Organization Studies Colloquium on Organizational Openness. Professor Dobusch contributes to several research communities through his blogs 'osconjunction.net' and 'governancexborders.com', and participates in the Momentum-Kongress that connects academic research with social and political practice. His work bridges theoretical innovation with practical relevance, particularly in how organizations can navigate the tensions between openness and closure, formal regulation and creative adaptation.

Mark Oskinمشاهده پروفایل

استاد مدعو

• Computer Architecture
• Parallel Computing
• Graph Processing
• +۱۲ مورد دیگر

Mark Oskin is an Adjunct Professor at the School of Computer Science and Engineering , University of Washington , focusing on Software & Hardware Systems . He leads the Sampa Group and collaborates on projects like HammerBlade and BlackParrot. University: University of Washington School: School of Computer Science and Engineering Department: Department of Electrical & Computer Engineering His research spans Computer Architecture , Parallel Computing , and Graph Processing , with additional expertise in Quantum Computing , Open Source Hardware , and Distributed Shared Memory . Ongoing work includes custom manycore devices for graph execution and open-source RISC-V designs. Past projects like Grappa and WaveScalar advanced distributed memory and dataflow execution. Recent publications include BlackParrot: An Agile Open Source RISC-V Multicore for Accelerator SoCs (IEEE Micro 2020) and Perceptual Compression of Video Storage and Processing Systems (SoCC 2019), reflecting trends in hardware-software co-design, quantum systems, and energy-efficient video processing. Best Paper Award , USENIX ATC 2015 IEEE Micro Top Picks , 2009 Mark has advised numerous students, including Amrita Mazumdar (IoT video compression startup), Brandon Lucia (CMU), and Steve Swanson (UC San Diego). He co-founded Corensic, a startup exploring deterministic multithreaded execution.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +۱۲ مورد دیگر

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

Sriramkrishnan Muralikrishnanمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• High Performance Scientific Computing
• Plasma Physics
• +۴ مورد دیگر

Sriramkrishnan Muralikrishnan is a Research Staff member at the Department of Mathematics and Education within the Jülich Supercomputing Center (JSC) at Forschungszentrum Jülich, Germany. His work focuses on developing advanced computational methods for high-performance scientific computing, particularly in plasma physics and related multi-physics applications. Dr. Muralikrishnan's research spans several key computational domains: Numerical Analysis and High-Order Methods High Performance Scientific Computing for Exascale Architectures Plasma Physics Simulations Fast Solvers and Preconditioners Parallel-in-Time Integration Techniques Performance Portable Programming His recent publications demonstrate a strong focus on particle-based computational methods, particularly Particle-in-Cell and Particle-in-Fourier techniques. His work consistently addresses challenges in energy conservation, scalability across architectures, and noise reduction in plasma simulations. A significant portion of his research involves developing performance-portable frameworks that can efficiently leverage modern supercomputing hardware from different vendors without code rewrites. Dr. Muralikrishnan is actively involved in open-source scientific software development: Lead developer of IPPL (a performance portable library for grids and particles) Developer of OPAL (an open-source particle accelerator library) His research has direct applications in plasma physics, fusion energy research, and advanced accelerator design, with a strong emphasis on making computational methods accessible through open-source development and advocating for diversity in scientific computing.

Peter Kazanzidesمشاهده پروفایل

استاد پژوهشی

• Robotics
• Medical Robotics
• Augmented Reality
• +۴ مورد دیگر

Peter Kazanzides is a Research Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University, where he joined the faculty in 2002. His research focuses on robotics, medical robotics, augmented reality, and computer-assisted interventions with primary applications in computer-integrated surgery. His educational background includes multiple degrees from Brown University: ScB (1983) in Electrical Engineering AB (1983) in Computer Science ScM (1985) in Electrical Engineering ScM (1987) in Applied Mathematics PhD (1988) in Electrical Engineering Kazanzides is a member of the Robotics, Vision, and Graphics research group and directs the Sensing, Manipulation, and Real-Time Systems (SMARTS) laboratory. His work spans surgical robotics, mixed reality, and systems engineering, with emphasis on computer-assisted surgery in extreme environments including minimally invasive surgery, microsurgery, and space teleoperation. The SMARTS lab develops real-time sensing systems, augmented/mixed reality interfaces using head-mounted displays, high-performance motor control, and sensor fusion technologies, with strong focus on system integration and open-source platforms like the da Vinci Research Kit (dVRK). Analysis of his recent publications (2024-2025) reveals dominant trends in surgical robotics autonomy, augmented reality navigation, force estimation, and digital twin technologies. Key themes include AI-driven task automation, haptic feedback enhancement, real-time instrument segmentation, and simulation environments for surgical training, primarily leveraging the da Vinci Research Kit framework. As director of the SMARTS lab within the Laboratory for Computational Sensing and Robotics (LCSR), Kazanzides leads a collaborative ecosystem including the Computer Integrated Interventional Systems (CIIS) Lab, Advanced Medical Instrumentation and Robotics (AMIRO) Lab, Dynamical Systems and Controls Lab (DSCL), Computer Aided Medical Procedures (CAMP) Lab, Medical UltraSound Imaging & Intervention Collaboration (MUSiiC) Lab, and Photoacoustic & ULtrasonic Systems Engineering (PULSE) Lab. His lab maintains responsibility for the development and support of the open-source da Vinci Research Kit, a critical resource for surgical robotics research worldwide.

• Machine Learning
• Datasets
• Reliable Generalization
• +۵ مورد دیگر

Ludwig Schmidt is an Assistant Professor in the Computer Science Department at Stanford University and a member of Stanford Data Science. He also serves as a member of the technical staff at Anthropic and LAION, contributing to both academic and industrial research in machine learning. Dr. Schmidt completed his PhD at MIT, where he received the prestigious George M. Sprowls Award for best PhD theses in computer science, followed by a postdoctoral position at UC Berkeley. His educational background provides a strong foundation for his research at the intersection of theoretical and applied machine learning. Dr. Schmidt's research focuses on the empirical foundations of machine learning, with particular emphasis on datasets, reliable generalization, multimodality, and language models. His work addresses critical challenges in ensuring machine learning models perform consistently across different domains and data distributions. His research group has made significant contributions to open source machine learning through projects like OpenCLIP, DCLM, and the LAION-5B dataset, which have become important resources for the machine learning community. An analysis of Dr. Schmidt's recent publications reveals a strong focus on dataset quality, multimodal learning, and language model training. His work spans from fundamental research on generalization and robustness to practical applications in vision-language systems and tabular data. A recurring theme is the importance of high-quality, diverse datasets for training robust machine learning models, with several papers addressing dataset curation, evaluation methodologies, and the impact of data quality on model performance. New Horizons Award at EAAMO Best paper awards at ICML & NeurIPS Best paper finalist at CVPR Sprowls dissertation award from MIT (George M. Sprowls Award) Dr. Schmidt actively mentors doctoral students and postdoctoral researchers. His current advisees include doctoral candidates Liangyu Chen, Shiye Su, Elaine Sui, Audrey Xie, John Yang, Yuhui Zhang, and Wanjia Zhao. He serves as Doctoral Dissertation Reader for Kyle Hsu and Aishwarya Mandyam, and as Postdoctoral Faculty Sponsor for Benjamin Feuer and Mike Merrill. His research has attracted significant funding that supports these students and enables his group to contribute to open source projects like OpenCLIP and LAION-5B. Dr. Schmidt leads a research group focused on empirical machine learning foundations. The group actively contributes to open source machine learning through code repositories and datasets, including OpenCLIP, OpenFlamingo, LAION-5B, and the DataComp datasets. Their work bridges theoretical insights with practical applications, developing tools and resources that advance the entire machine learning community.

Avery Bermanمشاهده پروفایل

استادیار

• Medical Physics
• Functional Neuroimaging
• Biomedical Engineering
• +۵ مورد دیگر

Avery Berman is an Assistant Professor in the Department of Physics at Carleton University and a Scientist at the University of Ottawa Institute of Mental Health Research (IMHR) at The Royal. His work focuses on advancing functional MRI (fMRI) techniques for high-resolution imaging of brain activity and physiology, with applications in neuroscience and mental health disorders. PhD in Biomedical Engineering and MSc in Medical Radiation Physics from McGill University Postdoctoral research at Harvard Medical School and the Martinos Center for Biomedical Imaging Research Interests include: High-resolution fMRI at 7 Tesla Biophysical modeling of vascular networks Quantitative biomarkers for oxygen metabolism PET-MRI hybrid imaging systems Neurovascular coupling in mental illness Scientific Awards include: NSERC Canada Graduate Scholarship (Master's) CIHR Canada Graduate Scholarship (Doctoral) CIHR Postdoctoral Fellowship (top 10/600 applicants) NSERC Postdoctoral Fellowship (top Physics section recipient) Research Funding from NSERC, CFI, and institutional support from Carleton University and IMHR. His lab develops the open-source BOLDsωimsuite software for fMRI signal modeling and collaborates with Canada-wide vascular training programs.

• Artificial Intelligence
• Computer Science
• Swarm Robotics
• +۵ مورد دیگر

Ramón Luis Rizo Aldeguer is a University Professor in the Department of Computer Science and Artificial Intelligence at the Higher Polytechnic School of the University of Alicante. He has held this position since 1996 and continues to be actively involved in teaching and research as recently as 2025. He previously served in various leadership roles including Director of the Department of Computer Science and Artificial Intelligence (1997-2004) and Deputy Director of the Institutional Projects Area at the University of Alicante (2012-2020). His educational background includes a PhD in Computer Science from the Polytechnic University of Valencia (1992) and a degree in Mathematics from the University of Valencia (1977). He has been a member of the Spanish Association for Artificial Intelligence since 1990 and has held leadership positions within the organization. Rizo Aldeguer's research focuses on artificial intelligence with particular emphasis on swarm robotics, UAV deployment, and deep reinforcement learning. His work bridges theoretical foundations with practical applications in robotics and autonomous systems. He has made significant contributions to educational methodologies, particularly in integrating computational tools into engineering education. His publication record shows a consistent trajectory in swarm intelligence and robotics, with recent publications (2018-2023) demonstrating increasing sophistication in applying deep reinforcement learning to complex multi-agent systems. His research spans both theoretical advancements and practical implementations in robotics and autonomous systems. Fifteen five-year research periods (trienios) Six teaching merit periods Five six-year research periods (sexenios) President of Organizing Committee of VI Conference of Spanish Association for Artificial Intelligence (1995) President of Scientific Committee of CAEPIA (1999) Rizo Aldeguer has supervised 14 doctoral theses, with many receiving the highest honors (SOBRESALIENTE CUM-LAUDE). He has participated as a researcher in over 30 competitive public research projects, serving as principal investigator in 12 of them. His educational projects include innovative teaching methods and the development of computational tools for engineering education. He has been instrumental in the design and implementation of computer science programs at both the University of Alicante and the Polytechnic University of Valencia. He is a founding member of the University Institute for Computer Research and directed the Industrial Computing and Artificial Intelligence research group from 1992 to 2004. His current research continues to focus on swarm robotics and intelligent systems, with active participation in the Valencian Graduate School and Research Network of Artificial Intelligence since 2021.

• Global biosphere dynamics
• Crop–climate interactions
• Land-use change
• +۳ مورد دیگر

Dr. Christoph Müller is a leading scientist at the Potsdam Institute for Climate Impact Research (PIK), Germany, where he has served as working-group leader of the Land Biosphere Dynamics group since 2012. He also co-leads the Global Biosphere and Water Modeling team and acts as the scientist-in-charge for the internationally renowned LPJmL global vegetation and crop model. Additionally, he is Co-lead of the Ag-GRID initiative within the Agricultural Model Intercomparison and Improvement Project (AgMIP) and serves as Topical Editor for Geoscientific Model Development . Education Diploma in Geoecology, University of Potsdam (2002) PhD in Geoecology, University of Potsdam & International Max Planck Research School (IMPRS) (2007) Research Interests Dr. Müller’s research centres on understanding and modelling the interactions between climate, land use, and the biosphere to support sustainable food-system transformations. His work integrates global-scale vegetation and crop models with climate projections, socio-economic scenarios, and observational data to assess: Impacts of climate change and extreme events on crop yields and food security Carbon, nitrogen, and water cycles in managed and natural ecosystems Land-based climate-mitigation strategies and their co-benefits or trade-offs Adaptation options for agriculture under global change He promotes open science and reproducible modelling workflows, exemplified by the LPJmL open-source ecosystem model and associated toolkits. Publication Profile & Trends Since 2014 he has authored or co-authored more than 200 peer-reviewed articles. Recent work (2024-2025) highlights three dominant themes: (1) quantifying underestimated negative impacts of climate extremes on crop yields, (2) assessing the sustainability of large-scale land-based mitigation measures, and (3) advancing model intercomparison frameworks (e.g., AgMIP, ISIMIP) to reduce uncertainty in global yield projections. His studies increasingly integrate economic and health perspectives, examining how dietary shifts and food-system transformations can achieve climate, environmental, and social co-benefits. Scientific Awards & Recognition While no formal awards are explicitly listed, several publications have received notable recognition: “Soil quality both increases crop production and improves resilience to climate change” (Nature Climate Change, 2022) – listed among China’s top ten major advances in agricultural science in 2023. “Large potential for crop production adaptation depends on available future varieties” (Global Change Biology, 2021) – top-downloaded article. “Climate change impacts on global agriculture emerge earlier in new generation of climate and crop models” (Nature Food, 2021) – widely cited in IPCC AR6. Leadership, Grants & Collaboration Dr. Müller leads or co-leads multiple international projects and working groups: Working Group Leader – Land Biosphere Dynamics, PIK Research Department 2 Co-Lead – Ag-GRID, Agricultural Model Intercomparison and Improvement Project (AgMIP) Scientist-in-Charge – LPJmL model development and application Topical Editor – Geoscientific Model Development journal These roles involve coordinating multi-institutional consortia, securing competitive grants, and mentoring early-career researchers. Laboratory & Data Resources Dr. Müller’s “team” is essentially the LPJmL modelling group at PIK, comprising post-docs, doctoral researchers, and software engineers who maintain and extend the LPJmL code-base, develop satellite-data fusion products, and provide model-driven policy support to governments and international organisations such as the IPCC, FAO, and World Bank.

• Software Correctness
• Cybersecurity
• Usability Engineering
• +۵ مورد دیگر

James Davis is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. His research focuses on engineering robust computing systems through socio-technical approaches, emphasizing software correctness, security, and usability. He applies empirical methodologies to evaluate the practical impact of technical solutions. Research interests include software supply chain security, deep learning reproducibility, regular expression optimization, IoT cybersecurity, and the socio-technical challenges in system design. His work bridges theoretical foundations with real-world applications, addressing issues like regex denial-of-service (ReDoS), model reuse in AI, and developer practices for safety-critical systems. Recent publications span topics such as actor reputation metrics in software supply chains, AI safety for downstream developers, and edge-computing optimizations for vision transformers. His interdisciplinary approach integrates empirical studies, formal verification, and human-centered design principles. No scientific awards are explicitly mentioned in the provided materials. His advising record is currently unspecified, though his research group likely engages in collaborative projects with industry and academia. He contributes to initiatives like the Sigstore ecosystem and open-source security tooling, reflecting his commitment to practical impact.