جست‌وجوی استاد و پژوهشگر

• Condensed Matter Physics
• Quantum Transport
• Magnetoresistance Phenomena
• +۳ مورد دیگر

Jesus Iñarrea Las Heras is an Associate Professor at the Department of Physics, Faculty of Sciences, Universidad Carlos III de Madrid. His research focuses on theoretical and computational studies of quantum transport phenomena in two-dimensional electron systems (2DES) under external radiation fields. Key areas include microwave/terahertz-driven magnetoresistance oscillations, radiation-induced zero-resistance states, and the interplay between plasmons, phonons, and electron dynamics in ultra-clean systems. His work emphasizes the theoretical modeling of radiation-driven electron orbits, coherent states, and cat states to explain experimental observations such as off-resonance magnetoresistance spikes, beating patterns, and negative giant magnetoresistance effects. He has contributed to understanding phenomena like plasmon-phonon coupling, polarization sensitivity, and applications in nanoantennas and high-frequency detectors. Publications highlight advancements in explaining radiation effects in 2DES, including Rashba spin-orbit coupling systems, dc/microwave field interactions, and terahertz band applications. Research spans from fundamental physics (e.g., Landau level dynamics, quantum superpositions) to applied nanotechnology (e.g., tunable plasmons, ultra-sensitive detectors). No specific awards or grants are listed in the provided data. His academic contributions are primarily through peer-reviewed articles and collaborations in condensed matter physics and nanoelectronics.

Timothy Handyمشاهده پروفایل

پژوهشگر ارشد

• Supernova Theory
• Computational Astrophysics
• Stellar Evolution
• +۳ مورد دیگر

Timothy Handy is a Postdoctoral Research Fellow at the University of Michigan's Climate and Space Sciences and Engineering department, associated with the Center for Laser Experimental Astrophysics Research. He earned his PhD in Computational Science from Florida State University (2014) under Prof. Tomasz Plewa, focusing on core-collapse supernova theory. His research bridges computational astrophysics and high-energy density physics, specializing in supernova explosion mechanisms, hydrodynamic instabilities (e.g., Rayleigh-Taylor), and plasma dynamics. He has conducted experiments at facilities like OMEGA and NIF to study astrophysical phenomena under extreme conditions. Key research interests include stellar evolution, nucleosynthesis, and the interplay between computational models and observational data. His work addresses challenges like shock revival in supernova progenitors and turbulence in supernova remnants. Timothy's contributions span both theoretical modeling and experimental design in laser-driven plasma systems. His publications emphasize late-stage supernova dynamics, Rayleigh-Taylor instability growth under high-energy fluxes, and turbulence in high-energy-density plasmas. He collaborates with experimental teams to validate numerical simulations against laboratory astrophysics data.

• Emotion Recognition
• Facial Expression Analysis
• Machine Learning
• +۵ مورد دیگر

Kamlesh Mistry is an Assistant Professor in the Computer and Information Sciences Department at Northumbria University. His research focuses on Emotion Recognition, Facial Expression Analysis, Optimization Algorithms, and Machine Learning applications in Computer Vision and Humanoid Robotics. He holds a PhD from his work on intelligent facial expression recognition, supervised by Professor Li Zhang. Dr. Mistry has contributed to over 34 research outputs since 2007, with notable recent work in 2025 introducing adaptive nature-inspired optimization frameworks and multimodal emotion recognition systems. His research interests span facial expression recognition under varying conditions, optimization algorithm design (e.g., Firefly, Differential Evolution), and deep learning applications for semantic segmentation, medical imaging, and anomaly detection. Collaborations include studies on privacy-preserving location-sharing and short-term forecasting models for energy and weather systems. Recent publications highlight advancements in multimodal emotion recognition using transformers and variational autoencoders, semantic segmentation via GAN-synthesized images, and pose-invariant facial expression systems. His work emphasizes practical applications in healthcare, robotics, and cybersecurity. Advising and grants are not explicitly detailed in the provided text, but his doctoral thesis demonstrates expertise in evolutionary feature optimization and facial point detection. No scientific awards are mentioned.

Anne Marie Svaneمشاهده پروفایل

دانشیار

• Topological Data Analysis
• Probability Theory
• Mathematical Statistics
• +۳ مورد دیگر

Anne Marie Svane is an Associate Professor at the Department of Mathematical Sciences, Aalborg University, specializing in topological data analysis, stochastic geometry, and probability theory. Her research bridges theoretical mathematics with applied statistics, focusing on geometric functionals and computational methods. Education: PhD in Mathematics from Aarhus University. Her recent work explores cobordism obstructions, Gibbs processes, and applications in climate science and medical research. Key contributions include: Advancing kernel persistence methods for topological data analysis. Developing central limit theorems for spatial point processes. Modeling moisture dynamics in building physics with climate data. Investigating the interplay between digital algorithms and geometric structures. She collaborates on interdisciplinary projects like AI-Aalborg Intelligence and contributes to educational initiatives such as Girls' Day in Science.

Wei Jinمشاهده پروفایل

مدرس

• High-speed optical transmission systems
• Low-cost optical access networks
• Seamless optical metro-access network convergence
• +۳ مورد دیگر

Dr. Wei Jin is a Lecturer (Teaching and Research) at the School of Computing and Engineering, Bangor University. He holds a Ph.D. in Optical Engineering from the University of Electronic Science and Technology of China (2017). Previously, he served as a lecturer at Southwest Petroleum University (2017–2018) and a postdoctoral researcher in the Optical Communications Research group at Bangor (2019–2021), before securing his current lectureship. His research focuses on high-speed optical transmission systems, low-cost optical access networks, and advanced digital signal processing (DSP) algorithms. He has authored/co-authored over 75 peer-reviewed publications. Dr. Jin teaches courses including ICE-2601 Data Systems, Management & Eth and ICE-4414 RF & Optical MEMS , and supervises undergraduate, MSc, and PhD projects. His work emphasizes seamless network convergence, reconfigurable optical components, and security in optical communication systems. Key contributions include experimental demonstrations of advanced transceiver designs and network architectures for 5G and beyond. He is affiliated with the Digital Signal Processing Centre of Excellence (DSP Centre) at Bangor University. Recent research trends in his publications highlight innovations in physical layer security using chaotic digital filters, seamless fiber-wireless access networks, and dynamic sub-wavelength switching. These advancements address challenges in next-generation optical networks, including low-cost scalability and robust security measures. His work bridges theoretical DSP algorithms with practical implementations in real-world communication systems. Awards: None explicitly mentioned in the provided texts. Grants: Not detailed in the current text excerpts. Labs/Teams: Member of the Optical Communications Research group and the Digital Signal Processing Centre of Excellence (DSP Centre).

• Anesthesiology
• Critical Care Medicine
• Mitochondrial Physiology
• +۷ مورد دیگر

Bert Mik is a researcher in the Department of Anesthesiology at Erasmus MC, Erasmus University Rotterdam, Faculty of Medicine. His work focuses on mitochondrial oxygenation, perioperative monitoring, and critical care outcomes, particularly in relation to acute kidney injury and blood transfusion. Research Interests: Advanced monitoring of mitochondrial function during surgery Early detection of sepsis using electronic nose technology Impact of oxygenation and transfusion on organ injury Application of artificial intelligence in physiological data analysis The recent publications indicate a strong trend toward integrating physiological monitoring with machine learning for early diagnosis and risk prediction in critical care settings. His work often involves prospective and multicenter cohort studies, with a focus on cardiac and critically ill patients. Scientific Contributions: Development of novel monitoring techniques for mitochondrial oxygen consumption Investigation of mitochondrial oxygen tension as a biomarker for transfusion outcomes Feasibility studies on AI-driven diagnostic tools in ICU settings Bert Mik collaborates extensively within the Erasmus MC anesthesiology research group, including researchers such as F. A. Harms, C. J. de Wijs, and R. J. Stolker. He has contributed to over 69 research outputs, including articles and book chapters. Supervised work is indicated, though specific advisees are not listed. No scientific awards are mentioned in the available text. Laboratory and Research Network: His research is embedded within the anesthesiology research network at Erasmus MC, focusing on translational physiology and clinical innovation in perioperative and intensive care medicine.

Peter Uhrigمشاهده پروفایل

استاد

• Digital Linguistics
• Big Data in Linguistics
• Corpus Linguistics
• +۱۲ مورد دیگر

Peter Uhrig is a Professor at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), holding the Chair of Digital Linguistics with a Focus on Big Data within the Institute of English and American Studies. He is based in Erlangen, Germany, and actively contributes to research and teaching in computational and cognitive linguistics. His research interests lie at the intersection of linguistics, computation, and cognition, with a strong emphasis on corpus-based analysis , construction grammar , multimodal communication , and digital methods in language research . He investigates phenomena such as collocation, argument structure, creativity in language, and spoken word comprehension using large-scale datasets and advanced computational models. His recent publications reveal a clear trend toward interdisciplinary, data-intensive research. He frequently collaborates on projects involving multimodal corpora , gesture analysis , spoken language processing , and computational modeling , often in collaboration with researchers from computer science and cognitive neuroscience. His work is published in leading journals in linguistics and cognitive science. How Collostructional Analysis Contributes to the Description of Argument Structure Constructions with Slots for that-and Infinitive Clauses (2024) The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics (2024) World Futures through RT’s Eyes: Multimodal Dataset and Methodology (2024) Prof. Uhrig has co-edited several academic volumes and plays a key role in developing research infrastructure, such as the Red Hen Protocol for anonymizing audiovisual data and tools for multimodal analysis. While specific grant funding is not detailed, his involvement in large collaborative projects indicates active grant-supported research. He also contributes to academic service through editorial work and conference organization. He is involved in building digital infrastructure for multimodal research, including work on gesture retrieval systems and data anonymization protocols. His lab or research group appears to focus on integrating computational tools with linguistic theory, particularly within the framework of construction grammar and cognitive linguistics.

Darla M. Castelliمشاهده پروفایل

استاد

• Physical Activity and Health
• Pedagogy
• Cognitive Neuroscience
• +۳ مورد دیگر

Darla M. Castelli is Chair of the Department of Physical Therapy, Human Movement and Rehabilitation Sciences at Northeastern University's College of Bouvé Health Sciences. She holds a PhD in Pedagogy from the University of South Carolina, MS in Exercise Physiology from Northern Illinois University, BS in Kinesiology from Plymouth State University, and a Data Science Certificate from The University of Texas at Austin. PhD in Pedagogy – University of South Carolina MS in Exercise Physiology – Northern Illinois University BS in Kinesiology – Plymouth State University Data Science Certificate – University of Texas at Austin Her research focuses on the intersection of physical activity, cognitive health, and metabolic outcomes in children and emerging adults. Using advanced methods like fNIRS and computational modeling, she investigates how movement impacts brain function, academic achievement, and social-emotional well-being. Current work includes NIH-funded obesity prevention studies among Latina mothers. Recent publications highlight trends in gamification for health behavior change, integrated physical-computational education models, and neurophysiological responses to activity/sedentary patterns. Her Behavioral and Cognitive Health Lab at Northeastern explores these connections through multidisciplinary approaches. 2023 McCloy Research Award (SHAPE America) 2022 North American Society Fellow 2020-21 SHAPE Curriculum & Instruction Award 2020 Catherine Ennis Scholar (AERA) 2020 SHAPE America Scholar Award Darla teaches advanced courses in Research Methods, Cognition & Exercise, Pediatric Exercise Science, and Physical Activity & Public Health. She directs the Behavioral and Cognitive Health Lab and contributes to the Whole Communities-Whole Health initiative at UT Austin.

• Computer Architecture
• Systems & Networking
• Approximate Computing
• +۶ مورد دیگر

Weng Fai WONG is an Associate Professor and Deputy Head of the Department of Computer Science at the School of Computing, National University of Singapore (NUS). With over three decades of academic experience at NUS, he has established himself as a leading researcher in computer systems, with particular expertise in the interface between hardware and software stacks. Dr. Wong received his B.Sc. (First Class Honors) and M.Sc. from the National University of Singapore in 1989 and 1991 respectively, followed by a Dr.Eng.Sc. from the University of Tsukuba in 1993. His academic journey began at NUS (then DISCS) in 1985, where he progressed from student to Senior Tutor in 1989, and later returned from Japan as a Lecturer in 1993. Dr. Wong's research focuses on systems and networking, with special emphasis on hardware-software co-optimization. His current research interests include approximate computing , neuromorphic computing , and hardware acceleration for deep learning. His work spans computer architecture , embedded systems , compilers and runtime systems , and programming languages . He has made significant contributions to optimizing software for novel hardware including FPGAs, GPUs, and non-volatile memory technologies. His recent publications (2023-2025) demonstrate a strong focus on energy-efficient AI computing, with particular emphasis on spiking neural networks, large language model acceleration, and FPGA-based solutions for graph processing and machine learning workloads. His research shows a clear trajectory toward green AI through hardware-software co-design that minimizes energy consumption while maintaining computational effectiveness. Dr. Wong is a Member of ACM and a Senior Member of IEEE. His paper "Exploiting half precision arithmetic in Nvidia GPUs" was a Best Paper Finalist at the IEEE High Performance Extreme Computing Conference (HPEC 2017). As Deputy Head of the Department of Computer Science at NUS, Dr. Wong plays a key leadership role in academic administration while maintaining an active research program. His work has been supported by numerous research grants, though specific details are not provided in the available information. Dr. Wong leads research in the Systems & Networking area at NUS, with particular focus on the Hardware-Software Interface Laboratory. His team explores innovative approaches to bridge the gap between theoretical computer science and practical hardware implementation, with applications spanning from edge computing to large-scale data centers.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Hongbo Liu is a researcher at Indiana University - Purdue University Indianapolis , Department of Computer Information and Graphics. With a focus on Artificial Intelligence, Machine Learning, and Network Analysis , Liu has contributed extensively to computational intelligence through 118+ publications since 2004. Multi-disciplinary research spanning Graph Theory, Swarm Intelligence, and Deep Learning Recent work includes Robust Gated Models for Temporal Networks and Self-Adaptive Neuroevolution Systems (2024-2025) Key research themes include: Dynamic network analysis and link prediction Crowd behavior modeling and trajectory forecasting Swarm-based optimization for complex systems Fuzzy logic and granular computing applications Neural network architectures for image and text processing Liu's publications demonstrate strong collaborations with researchers like Ajith Abraham, Yu Yang, and Bo Zhang across 15+ academic journals and conferences . The work spans from theoretical graph algorithms (2015-2017) to applied systems in autonomous robotics and blockchain (2024).

• Precision Livestock Farming
• Data Analysis
• Image and Signal Processing
• +۴ مورد دیگر

Helen Schomburg is a researcher at the Institute of Animal Welfare and Animal Husbandry (ITT), focusing on advanced technological solutions to enhance animal welfare and optimize farming practices. Her work integrates Precision Livestock Farming with Machine Learning and Image Processing to develop automated monitoring systems for livestock. Education: Dr. rer. nat. (Doctorate in Natural Sciences) Research Interests: Her research spans Precision Livestock Farming , Data Analysis , and Machine Learning , with a focus on applying Pattern Recognition and Signal Processing to assess animal behavior and health. She specializes in creating digital tools for real-time welfare monitoring in pigs and poultry. Publications & Projects: Schomburg's recent work includes designing the Bite-o-Mat device for tail biting detection in pigs and prototype systems for broiler chicken activity monitoring using elevated platforms with integrated sensors. Her contributions emphasize reducing labor intensity and improving early intervention through automated data analytics. Labs & Teams: She collaborates with colleagues like Prof. Dr. L. Schrader, Dr. J. Knöll, and Dr. A. Patt, contributing to initiatives such as the ErhEb project under the European Partnership Animal Health & Welfare. Her efforts align with the Experimental Station Celle, promoting innovation in farm animal environments.

• Plasma Physics
• Laser-Plasma Interactions
• Particle Acceleration
• +۷ مورد دیگر

Professor Robert Bingham is a leading academic in the Department of Physics at the University of Strathclyde, part of the Faculty of Science. His research is centered on plasma physics, laser-plasma interactions, and high-energy density physics, with strong applications in fusion, astrophysics, and particle acceleration. He is actively involved in major international research initiatives and leads several funded projects. University: University of Strathclyde School: Faculty of Science Department: Department of Physics Academic Rank: Professor Email: robert.bingham@strath.ac.uk His educational background is not explicitly detailed, but his extensive research output and leadership roles suggest a strong foundation in physics and engineering. He has contributed to over 425 research outputs, including high-impact publications in journals such as Nature Communications and Physical Review Letters . Robert Bingham's research interests span plasma instabilities, nonlinear wave coupling, quantum vacuum phenomena, and laser-driven particle acceleration. His work bridges theoretical modeling and experimental validation, often using high-power lasers and advanced computational simulations. He is particularly known for his contributions to understanding radiation-beam-plasma interactions and collective effects in high-intensity fields. The recent publications reflect a strong trend toward probing fundamental physics using advanced laser and plasma technologies. Themes include axion detection, relativistic pair plasmas, ion acceleration in turbulent magnetic fields, and quantum sensing via atom interferometry. These works demonstrate a consistent focus on high-energy density physics, nonlinear dynamics, and the intersection of plasma physics with particle and astroparticle physics. While no specific scientific awards are listed in the provided text, his role as Principal Investigator on multiple EPSRC-funded projects and his extensive publication record in top journals indicate significant recognition in the field. Bingham has supervised or collaborated with numerous researchers, particularly as a Principal or Co-investigator on large-scale projects such as 'Critical Mass' and 'Probing the Quantum Vacuum'. These projects often involve interdisciplinary teams and industry partnerships, aiming to translate fundamental research into practical applications. Funding has been secured from major bodies like EPSRC, supporting long-term research programs in plasma acceleration and quantum vacuum studies. He is actively involved in research groups and collaborations focused on laser-plasma acceleration (e.g., ALPHA-X project), ionospheric plasma experiments (e.g., EISCAT), and high-power laser facilities. His work often involves international networks and data sharing, as seen in collaborative datasets and multi-institutional publications.

Anna Maria Echterhölterمشاهده پروفایل

استاد

• history of science (18th and 19th century)
• historical-political epistemology
• epistemic decolonisation
• +۹ مورد دیگر

Anna Maria Echterhölter is Professor of Modern History: History of Science at the Department of History, University of Vienna, a position she has held since March 2018. She also serves as spokesperson of the key research area History of Science at the Faculty of Historical and Cultural Studies since March 2019. Previously, she was Visiting Professor of History of Technology at Technische Universität Berlin (2018) and Visiting Professor of Cultural History at Humboldt Universität zu Berlin (2017). Her academic journey includes fellowships at the Max Planck Institute for the History of Science and the German Historical Institute Washington DC. Echterhölter's educational background includes a Magister programme in literature and cultural studies from Freie Universität Berlin (1994-2001), with additional studies in physics. Her academic credentials were solidified with her dissertation on "Epistemic values in obituaries on scientists 1711–1860" (2009) and her habilitation thesis defended in February 2017. Her international academic experience includes semesters at Goldsmiths College London (1998), summer school at the University of Silesia in Katowice (1999), and the Goethe-Institute in Manila (1996). As a historian of science, Echterhölter specializes in social histories of quantification, particularly focusing on the measurement of resources and how units of measurement interact with patterns of justification in allocation schemes. Her research spans history of science (18th and 19th century) , historical-political epistemology , epistemic decolonisation , and the history of quantification and modern data technologies . She has made significant contributions to understanding colonialism, measurement and quantification in Oceania , technologies of money , and the history of auxiliary sciences and historical methods including metrology and chronology. Her work on Pacific perspectives through the lens of epistemic decolonization has been particularly influential in challenging colonial narratives. Echterhölter's recent publications reveal a clear trajectory toward examining the intersections of historical quantification practices with contemporary AI and data technologies. Her work increasingly focuses on how historical measurement systems inform current data practices, particularly in colonial contexts. A notable trend is her exploration of "enquétes" (colonial surveys) as serialized forms of knowledge production that shaped scientific fields and colonial administration. Her scholarship bridges historical analysis with critical examinations of modern computational methods, demonstrating how historical patterns of quantification continue to influence contemporary data practices and epistemological frameworks. Editor of Science in Context (since 2022) Editor of Historische Wissensforschung book series Founding member of ilinx magazine Reviews for ISIS, N.T.M., Centaurus, and other prestigious journals Supervisor in two sections of the Vienna Doctoral School of Historical and Cultural Studies Professor Echterhölter leads the key research area History of Science at the University of Vienna, which includes the MA History program and the joint MA programme "Epistemologies of Science and Technology." She has organized numerous significant conferences and workshops, including "Beyond Quantity: Research with Subsymbolic AI" (2022), "The Metrics of Energy: Accounting for Nature in the History of Social Sciences and Ecological Economics" (2023), and "Scales, Norms, Limit Values in Times of (Digital) Change" (2021). Her collaborative work with institutions like the Institute for Historical Research London on "Anthropocene Histories" demonstrates her commitment to international scholarly exchange and interdisciplinary approaches to the history of science.

Laszlo Ujjمشاهده پروفایل

دانشیار

• Nonlinear Optics
• Ultrafast Laser Spectroscopy
• Coherent Raman Spectroscopy
• +۷ مورد دیگر

Dr. Laszlo Ujj is an Associate Professor in the Department of Physics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He has been a key contributor to both undergraduate and graduate-level physics education and maintains an active experimental research program in advanced optical spectroscopy. Education: Ph.D. in Physics, University of Szeged, Hungary (2001) Ph.D. in Nonlinear Spectroscopy/Physics, JPTE University of Pecs, Hungary (1990) M.S. in Theoretical Physics, JATE University of Szeged, Hungary (1983) Dr. Ujj's research focuses on nonlinear optics , ultrafast laser spectroscopy , and coherent Raman spectroscopy , with applications in bio-photonics and material analysis . He has developed state-of-the-art laser spectroscopy systems at UWF and previously at the University of Arizona. His work bridges experimental innovation and theoretical understanding in optical science. His recent publications reflect a strong trend toward label-free biological imaging , laser-induced breakdown spectroscopy (LIBS) for elemental analysis, and ultrafast dynamics in biomolecules . These works span disciplines including biophysics, materials science, and analytical chemistry, showcasing interdisciplinary impact. Scientific Recognition: h-index of 14 (Web of Science and Google Scholar) Over 599 citations by 2019 (Web of Science) Google Scholar: 727 citations, i10-index of 17 Presentations at American Physical Society and International Conference on Advanced Vibrational Spectroscopy Dr. Ujj has supervised numerous undergraduate researchers, many of whom have pursued advanced degrees at institutions such as Harvard University , the University of New Mexico , and the University of Arizona . His educational efforts include revising core physics courses and integrating research into the undergraduate curriculum. He teaches a wide range of courses including quantum theory, thermodynamics, electromagnetism, and laser physics. He also leads the Laser Spectroscopy Lab at UWF, where students engage in hands-on research with cutting-edge optical systems. Laboratory and Research Team: Dr. Ujj has developed and maintained advanced laser spectroscopy laboratories at both the University of Arizona and UWF. His lab focuses on coherent Raman microscopy, LIBS, and ultrafast spectroscopy, providing students with direct experience in experimental design, instrumentation, and data analysis.

Amir Hossein Payberahمشاهده پروفایل

دانشیار

• Equity and Justice in AI
• Large Language Models
• Co-Liberative Computing
• +۵ مورد دیگر

Amir Hossein Payberah is an Associate Professor of Computer Science at the Division of Software and Computer Systems (SCS) within the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology in Sweden. He earned his PhD from KTH in 2013, focusing on distributed systems, and later received a Docent degree in Computer Science from KTH in 2021. His academic journey includes a postdoctoral researcher role at RISE (2013-2015), a machine learning scientist position at Oxford University (2017-2018), and a return to KTH as Assistant Professor (2018-2022) before his current promotion to Associate Professor (2022–present). PhD in Information and Communication Technology, KTH (2008–2013) Docent in Computer Science, KTH (2021) MSc in Software Engineering of Distributed Systems, KTH (2006–2008) MSc in Computer Architecture, Amirkabir University of Technology (AUT), Iran (2000–2003) BSc in Computer Engineering, AUT (1996–2000) Dr. Payberah's research focuses on the intersection of equity, justice, and artificial intelligence , particularly in large language models. He leads the co-liberative computing research group, which integrates critical consciousness into computer science education and research to address systemic inequalities. His work challenges the neutrality of computing and emphasizes collaborative liberation for equitable technological development. As an educator, he has designed and taught courses on Data-Intensive Computing , Operating Systems , and Scalable Machine Learning at KTH, Amirkabir University, and the Swedish Institute of Computer Science. He currently serves as Program Director for the Information and Communication Technology (ICT) doctoral program and leads the WASP Legal, Ethical, and Societal Aspects cluster . Japan Society for the Promotion of Science BRIDGE Fellowship (2018) Dr. Payberah supervises PhD and Master’s students across diverse topics, including federated learning, explainable AI, large language model compression, and equity in algorithmic design. His students often collaborate with industry partners such as Ericsson, RISE, Peltarion, and Logical Clocks. His pedagogical philosophy bridges technical rigor with societal impact, reflected in his leadership of the co-liberative computing group and WASP cluster. He actively works on decentralized systems, critical AI, and socially responsible computing, with a career spanning roles at KTH, Oxford, and RISE. His academic contributions include mentoring over 30 graduate students and leading interdisciplinary initiatives in ethical AI.