جست‌وجوی استاد و پژوهشگر

Cristian Ciobanuمشاهده پروفایل

استاد

• Nanoscale Surface Physics
• Two-Dimensional Materials
• Computational Materials Design
• +۳ مورد دیگر

Cristian Ciobanu serves as Professor in the Department of Mechanical Engineering at Colorado School of Mines, where he has maintained continuous faculty appointment since 2004. His academic journey includes postdoctoral research at Brown University prior to joining Mines, with progressive promotions from Assistant to Associate to full Professor by 2014. Educational background: PhD in Physics, The Ohio State University (2001) MS in Physics, The Ohio State University (1998) BS in Physics, University of Bucharest (1995) His research program integrates computational and experimental approaches to address fundamental challenges in nanoscale surface physics and two-dimensional materials . Specialized expertise includes evolutionary algorithms for atomic structure optimization, development of materials for renewable energy applications, and investigation of self-organized nanostructures on crystal surfaces. Current work emphasizes machine learning applications in high-entropy alloy design and piezoelectric property engineering of layered systems. Publication trends reveal sustained focus on transition metal dichalcogenides, computational materials discovery, and piezoelectric response enhancement through alloying. Recent work increasingly incorporates machine learning for materials design while maintaining strong experimental validation through advanced microscopy and spectroscopy techniques. Key recognitions include: NSF Career Award (2009-2014) Research Excellence Award at Colorado School of Mines (2013) Fellow of the Institute of Physics (elected 2014) Ohio State Presidential Fellowship (2000-2001) Research funding has been secured through competitive mechanisms including the NSF Career Award, supporting his authorship of over 60 technical publications and a coauthored book on atomic structure determination. He actively advises graduate students in computational materials science and nanotechnology research within the Mechanical Engineering department. His scholarly activities are complemented by professional memberships in the Materials Research Society, American Physical Society, and American Vacuum Society. While specific laboratory facilities aren't detailed in source materials, his publication record indicates capabilities in computational modeling, scanning probe microscopy, and thin film characterization relevant to nanoscale materials research.

Jan Bernauerمشاهده پروفایل

دانشیار

• Nuclear Physics
• Particle Physics
• Proton Structure
• +۳ مورد دیگر

Jan Bernauer is an Associate Professor in the Department of Physics and Astronomy at Stony Brook University with a joint position at RIKEN BNL Research Center. He obtained his Ph.D. from Johannes Gutenberg University Mainz in 2010 and previously held research positions at MIT from 2010-2018. Education: Ph.D. in Nuclear Physics, Johannes Gutenberg University Mainz (2010) Diplom in Physics, Johannes Gutenberg University Mainz His research focuses on precision nuclear physics at the intersection of particle and nuclear physics, including proton form factor measurements, two-photon exchange effects, and beyond-Standard-Model searches. Current projects involve sPHENIX streaming readout, MUSE (muon scattering), and TPEX (two-photon exchange) experiments. Research outputs emphasize precision measurement techniques, with recent work on detector development (40% of publications) and QCD fundamentals (30%). Collaborative projects span 15+ institutions including MIT, DESY, and Jefferson Lab. Awards & Recognition: Infinite Kilometer Award (MIT, 2017) NSF Career Award Stony Brook Foundation Award Research Teams: Leads a group with 2 postdocs, 3 graduate students, and 4 undergraduates developing novel detector systems for RHIC and EIC. Current grants support instrumentation development for streaming readout in particle physics experiments.

Harrison Huibin Zhouمشاهده پروفایل

استاد

• High-Dimensional Data Analysis
• Nonparametric Estimation
• Statistical Decision Theory
• +۳ مورد دیگر

Harrison Huibin Zhou is the Henry Ford II Professor of Statistics and Data Science at Yale University. He has held leadership roles, including Department Chair of Statistics and Data Science (2018–present) and former Chair of Statistics (2012–2017). His academic career at Yale spans over two decades, with promotions from Assistant Professor (2004–2009) to Associate (2009–2010) and full Professor (2010–present). Research Interests: Dr. Zhou specializes in high-dimensional statistical theory, including nonparametric estimation, minimax theory, and applications in network analysis, machine learning, and functional data analysis. His work bridges theoretical foundations with computational methods, addressing challenges in modern statistical decision-making. Publications: His recent work focuses on spectral clustering, quantum state tomography, and optimal estimation in high-dimensional models. Notable contributions include theoretical guarantees for algorithms like the EM method in Gaussian mixtures and advancements in community detection in networks. Teaching: He teaches advanced courses such as Functional Data Analysis, Nonparametric Estimation, and Decision Theory, reflecting his expertise in statistical methodology and theory. Professional Service: Organized workshops on topics like Empirical Processes (2015) and High-Dimensional Data (2012), underscoring his role in fostering academic collaboration.

• Stochastic Analysis
• Mathematical Finance
• Option Pricing
• +۵ مورد دیگر

Blanka Horvath is a Lecturer at King's College London and Honorary Lecturer at Imperial College London's Department of Mathematics (Faculty of Natural Sciences). Her research focuses on stochastic analysis and mathematical finance, particularly in numerical methods, machine learning applications, and volatility modeling (e.g., SABR and rough volatility models). She holds a PhD from ETH Zurich (2015), a Diplom in Mathematics from the University of Bonn, and an MSc in Economics from the University of Hong Kong. She has organized major conferences such as the SIAM MMF 2017 mini-symposium and co-organized the Rough Volatility Meeting at Imperial College. Her honors include the 2019 Risk Rising Star Award and the 2024-25 LMS Emmy Noether Fellowship. She collaborates with institutions like UBS, The Alan Turing Institute, and Quantennium LTD. Her teaching includes courses on numerical methods in finance and Python/R programming. She supervises PhD and MSc students in areas like rough volatility, machine learning, and quantitative finance. Recent work explores quantum GANs for option pricing and regime detection using Wasserstein distances.

Rachel Grangeمشاهده پروفایل

استاد

• Nanophotonics
• Nonlinear Optics
• Quantum Optics
• +۳ مورد دیگر

Rachel Grange is a Full Professor in the Department of Physics at ETH Zurich and Head of the FIRST Center for Micro- and Nanoscience. Her research focuses on nanoscale material investigations, particularly using metal-oxides like lithium niobate and barium titanate for classical and quantum photonic devices. Education: Ph.D. in Ultrafast Laser Physics from ETH Zurich (2006). Career: Postdoctoral work at EPFL (2007–2010), group leader at Friedrich Schiller University in Jena (2011–2014), and progressive roles at ETH Zurich since 2015 (Assistant Professor, Associate Professor, Full Professor from 2025). Her recent work emphasizes integrated photonic platforms for quantum computing, nonlinear optics, and miniaturized electro-optic spectrometers. She explores both top-down and bottom-up fabrication techniques for nanophotonic structures, with applications in neuromorphic computing and mid-infrared communication. Grange leads the FIRST Center, advancing micro- and nanoscience technologies. She teaches courses like Nanomaterials for Photonic Devices and contributes to the development of scalable photonic systems for next-generation computing and quantum technologies.

Benjamin Turnbullمشاهده پروفایل

دانشیار

• Cyber Security
• Simulation
• Digital Forensics
• +۶ مورد دیگر

Associate Professor Benjamin Turnbull is Deputy Head of School at UNSW Canberra's School of Systems & Computing. His research focuses on cybersecurity, simulation, and emerging technologies, aiming to develop decision support systems for cyber resilience. He leads large-scale research projects funded by organizations like CSIRO, Australian Defence Force, and the US Naval Research Laboratory, totaling over $3 million AUD in grants. Teaching contributions include co-creating the Bachelor of Cyber Security program and directing multiple postgraduate cybersecurity offerings. His educational design emphasizes industry-relevant courses, from undergraduate to executive programs like the UNSW Online Cyber Security Masters. He has extensive experience in curriculum design, content development, and online education. Research interests span cyber situation awareness, secure simulation platforms, and automated learning from big datasets. Notable projects include the UNSW-MG24 microgrid cybersecurity dataset and frameworks like OQFL (quantum-based federated learning) for intelligent transportation systems. His work bridges theory and practice, with outputs including software tools and policy recommendations for cyber resilience in critical infrastructure. Key collaborations include the Cyber Cooperative Research Centre and DST Group. He has authored over 100 peer-reviewed publications, focusing on IoT security, blockchain-enabled learning, and cyber-physical-social systems resilience. His grants emphasize applied research with direct societal impact, such as mitigating supply chain cyber risks and enhancing microgrid cybersecurity.

Juan Carlos Cuevasمشاهده پروفایل

استاد

• Theoretical Physics
• Nanophysics
• Molecular Electronics
• +۴ مورد دیگر

Prof. Juan Carlos Cuevas is a Professor of Theoretical Nanophysics at the Universidad Autónoma de Madrid (UAM). He holds a PhD in Physics from UAM (1999) and has led research groups in molecular electronics and nanoscience. His work focuses on superconductivity, quantum transport, and radiative heat transfer at the nanoscale. Key areas of research include: theoretical analysis of molecular junctions, superconducting nanostructures, and near-field thermal phenomena. Cuevas has co-authored influential books such as *Molecular Electronics* (World Scientific, 2017) and pioneered studies on single-molecule conductance and quantum interference effects. Recent contributions include discoveries on phonon interference in molecular junctions (2025), thermodynamic uncertainty relations in superconductors (2025), and advanced machine learning approaches for radiative heat optimization (2024). His work bridges theoretical models with experimental insights from scanning tunneling microscopy and nanofabrication techniques.

Christopher Gilliamمشاهده پروفایل

استادیار

• Signal Processing
• Radar Systems
• Sampling Theory
• +۵ مورد دیگر

Dr. Christopher Gilliam is an Assistant Professor in Applied Signal Processing at the University of Birmingham's Department of Electronic, Electrical and Systems Engineering. He holds an MEng (1st Class Hons) in Electrical & Electronic Engineering (2008) and a Ph.D. in Signal Processing (2013), both from Imperial College London. Prior to joining Birmingham in 2022, he was a Postdoctoral Fellow at The Chinese University of Hong Kong (2013–2017) and a Research Fellow at RMIT University, Australia (2017–2022). Research Interests: Sensor signal processing, radar imaging, sampling theory, motion estimation, quantum navigation, and medical imaging. Labs: Microwave Integrated Systems Laboratory (MISL). Committees: Member of IEEE Signal Processing Society and APSIPA Technical Committees. His work focuses on advancing signal processing techniques for radar systems, navigation, and medical imaging. Recent research highlights include drone-based SAR imaging, motion correction in MRI, and fusion of classical/quantum sensors for inertial navigation. He is actively supervising PhD students and contributes to projects sponsored by DSTG. Publications span radar SLAM, probabilistic navigation algorithms, and deep learning-driven medical imaging solutions. His research bridges theoretical signal processing with practical applications in autonomous systems and healthcare.

Manjana Milkoreitمشاهده پروفایل

پژوهشگر ارشد

• Global Environmental Governance
• Climate Politics
• Sustainability Transformations
• +۳ مورد دیگر

Manjana Milkoreit is a Research Fellow at the University of Oslo's Department of Sociology and Human Geography, part of the Faculty of Social Sciences. She holds a Ph.D. in Global Governance from the University of Waterloo (Canada) and a Master of Public Policy from Harvard Kennedy School. Previously, she was an Assistant Professor at Purdue University and a Postdoctoral Researcher at Arizona State University’s Wrigley Institute. Her work focuses on global environmental governance, climate policy, and the role of cognition in decision-making. She coordinates governance research for the Global Tipping Points Report and leads projects like the Imagination and Climate Futures Initiative. Academic interests include science-policy interfaces, social tipping points, and future-oriented sustainability governance. Education: Ph.D. in Global Governance (University of Waterloo), MPP (Harvard Kennedy School). Key Positions: Affiliate at Norwegian Institute of International Affairs (NUPI), Sustainability Scholar at Arizona State’s Global Futures Lab. Research Themes: Climate change governance, cognitive approaches to policy, Earth system resilience, and anticipatory governance frameworks. Projects & Teams: Co-leads the RESULTS project on sustainability transformations and the Democrisis initiative exploring democracy and climate crisis intersections. Engages in interdisciplinary collaborations linking academia, policymakers, and civil society through tools like serious gaming and scenario planning. Grants & Collaboration: Funds include projects on governance innovation for tipping points and participatory climate action frameworks. Her work emphasizes bridging cognitive science with environmental policy to address complex global challenges.

• Cloud Computing
• Fog Computing
• Edge AI
• +۷ مورد دیگر

Sukhpal Singh Gill is an Assistant Professor (Lecturer) in Cloud Computing at the School of Electronic Engineering and Computer Science, Queen Mary University of London (UK). He holds a PhD, ME, and BE in Computer Science and is a Fellow of the Higher Education Academy (FHEA). His roles include Programme Director for MSc Advanced Computer Science and MSc Business Analytics, as well as Deputy Chair of the Main Misconduct Panel. He leads the GillNet Research Lab and is the Editor-in-Chief of the International Journal of Applied Evolutionary Computation (IJAEC) , with editorial roles in IEEE IoT, Nature Scientific Reports, and other journals. Education: PhD in Computer Science ME in Computer Science BE in Engineering Research Interests: Focus on Cloud Computing, Edge AI, IoT, Energy Efficiency, and Quantum Computing. His work bridges theoretical advancements with practical applications in healthcare, smart cities, and sustainable computing. Notable projects include AI-driven frameworks for carbon-neutral cloud resource management, blockchain-empowered healthcare systems, and quantum cloud computing models. Teaching: Teaches modules such as Cloud Computing (Postgraduate), Fundamentals of Web Technology (Undergraduate), and Semi-structured Data and Advanced Data Modelling (Postgraduate/Undergraduate). He emphasizes inclusive curriculum design and innovative teaching tools like the Q-Module-Bot for AI-supported learning. Awards & Grants: Recipient of 12,500+ citations and an H-index of 54 (Google Scholar). Secured grants for projects on edge AI, federated learning, and sustainable cloud computing. Winner of awards including the IEEE IT Professional Magazine Outstanding Reviewer Award (2024) and Elsevier's Best Paper Award (2023). Labs & Teams: Leads the GillNet Research Lab , focusing on cutting-edge research in cloud-edge computing, AI, and quantum systems. Collaborates with industry partners on projects like HealthEdgeAI and AIoT-driven smart healthcare systems .

Yi-Zhuang Youمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Quantum Entanglement Dynamics
• Topological Phases
• +۴ مورد دیگر

Yi-Zhuang You is an Associate Professor in the Department of Physics at the University of California, San Diego (UCSD). He holds a Ph.D. from Tsinghua University (2013). His research focuses on theoretical investigations of correlated topological phases, quantum entanglement dynamics, and machine learning applications in many-body systems. Key areas include deconfined quantum criticality, symmetry-protected topological (SPT) phases, and the interplay between topology and quantum matter. His work bridges condensed matter physics and high-energy physics, exploring topics such as topological responses in gauge theories, entanglement holography, and quantum machine learning. Recent studies involve machine learning-driven approaches to quantum state preparation, symmetry discovery, and tomographic reconstruction of quantum systems. His contributions span theoretical frameworks for understanding topological transitions, fractionalization in lattice models, and the role of symmetry in quantum critical phenomena. Notable research highlights include the study of symmetric mass generation as a deconfined quantum criticality mechanism, the application of classical shadow tomography for efficient quantum state estimation, and the development of algorithms for self-similar dynamics modeling. His publications frequently intersect with experimental proposals for observing topological phases in materials like graphene and iridates. Dr. You’s affiliations include the UCSD Physics Department, with collaborations extending to institutions globally. His research is supported by grants focusing on quantum information, topological materials, and machine learning applications in physics. While no specific awards are listed, his work has been widely cited in high-impact journals across condensed matter and theoretical physics.

Paul Franzonمشاهده پروفایل

استاد

• Quantum Information Science
• Machine Learning & AI Hardware
• 3D Integration
• +۴ مورد دیگر

Paul Franzon is the Cirrus Logic Distinguished Professor and Associate Department Head for Graduate Affairs at the Department of Electrical and Computer Engineering, North Carolina State University. He holds a PhD and Bachelor's in Electrical Engineering and a Bachelor's in Physics/Mathematics from the University of Adelaide, Australia. His research focuses on quantum information science, machine learning-driven hardware design, 3D integration, and high-speed systems. Education: PhD in Electrical Engineering, University of Adelaide (1988) Bachelor's in Electrical Engineering, University of Adelaide (1984) Bachelor's in Physics and Mathematics, University of Adelaide (1982) Research Interests: Quantum computing and algorithm optimization AI-driven design automation for 3D integrated circuits High-speed communication systems Hardware security and FPGA acceleration Awards & Honors: IEEE Fellow (2006) Alcoa Foundation Distinguished Engineering Research Award (2005) NC State Alumni Distinguished Undergraduate Professor Award (2003) NSW Australia Expatriate Scientist Award (2003) Advising & Grants: Advised PhD student Priyank Kashyap (2023 graduate) Recipient of NSF Young Investigators Award (1993) Labs & Collaborations: Center for Advanced Electronics Through Machine Learning (CAEML) IEEE EPS Society (Associate Editor)

• Urban Computing
• Spatiotemporal Data Management
• Artificial Intelligence
• +۳ مورد دیگر

Associate Professor Ke Deng is affiliated with the School of Computing Technologies at RMIT University. His research focuses on urban computing, spatiotemporal data analysis, and social networks, with expertise in data mining and artificial intelligence. He holds a PhD in Computer Science from The University of Queensland (2007), a Master's in Information and Communication Technology (2001), and a Bachelor's in Electrical Engineering (1994). Previously, he was a postdoctoral researcher at CSIRO ICT Centre and a researcher at Huawei Noah's Ark Lab. His work emphasizes practical applications of AI, such as fairness-aware recommendation systems, traffic scenario modeling, and energy-efficient protocols for IoT. Dr. Deng's career includes roles as an acting lecturer at The University of Queensland and co-supervisor of a PhD student. He has supervised numerous research projects, including advancements in quantum annealing for recommenders, fake news mitigation via reinforcement learning, and smart human sensing using millimeter-wave radar. His research outputs span journals like ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Education: PhD in Computer Science, The University of Queensland (2007) MSc in Information and Communication Technology (2001) BEng in Electrical Engineering (1994) Key Research Themes: Urban computing and smart cities Mechanisms for fair AI systems Energy-efficient IoT protocols Spatiotemporal data mining Grants and Collaborations: ARC Australian Postdoctoral Fellowship (2010–2012) Research at Huawei Noah's Ark Lab (2013) His recent projects highlight interdisciplinary innovation, such as quantum computing for feature selection and self-supervised networks for traffic scenario clustering. Dr. Deng is actively involved in mentoring PhD/Masters students and contributes to RMIT’s research initiatives in AI and urban informatics.

Paul Kockelmanمشاهده پروفایل

استاد

• Linguistic Anthropology
• Environmental Anthropology
• Semiotics
• +۵ مورد دیگر

Paul Kockelman is a Professor of Anthropology at Yale University, specializing in linguistic anthropology, semiotics, and environmental studies. He holds undergraduate degrees in mathematics and physics, an MS in physics, and a PhD in anthropology from the University of Chicago. His research focuses on the intersection of human agency, environmental degradation, and computational systems, with extensive fieldwork among Q’eqchi’-Maya communities in Guatemala. He served as editor of the Journal of Linguistic Anthropology (2016–2018) and is the author of numerous books and essays. Key research areas include the pragmatics of possible worlds, the semiotic dynamics of machine learning, and the ontological coupling between humans and algorithmic models. His work bridges cultural theory, science studies, and linguistic analysis, often employing mathematical models to explore meaning-making processes. His publications span books like Last Words: Large Language Models and the AI Apocalypse (2024) and A Mathematical Model of Meaning (forthcoming MIT Press), alongside foundational works in linguistic anthropology. His articles address topics from Mayan grammatical structures to the epistemic implications of AI. Grants include an EPA-funded dissertation on commons management. He maintains a website at www.envorganism.org .

Petar Popovskiمشاهده پروفایل

استاد

• Wireless Communication
• Internet of Things
• Ultra-Reliable Low Latency Communication
• +۱۲ مورد دیگر

Petar Popovski is a Professor at the Department of Electronic Systems within the Technical Faculty of IT and Design at Aalborg University, Denmark. His research focuses on next-generation wireless communication systems, with a strong emphasis on ultra-reliable low-latency communication (URLLC), Internet of Things (IoT), multiple access, and 6G technologies. He leads several high-impact research projects, including the Classique - Center for Classical Communication in the Quantum Era funded by the Danish National Research Foundation and WATER (Wireless Architectures for intelligent and Trusted connectivity in the posT-5G ERa) supported by Villum Fonden. His research interests span key areas in modern communication theory and systems, including random access , non-terrestrial networks , satellite communication , and machine learning for reliable communication . He is actively involved in advancing the integration of sensing and communication, digital twin technologies, and quantum-era classical communication frameworks. The recent publications highlight a strong trend toward deterministic and reliable access in wireless networks, integration of sensing and communication for industrial automation, and novel physical-layer techniques using reconfigurable intelligent surfaces. These works are published in top IEEE journals such as IEEE Transactions on Communications , IEEE Transactions on Haptics , and IEEE Transactions on Vehicular Technology . Award highlights include the Best Student Paper Award (2021) , recognizing his mentorship and collaborative research excellence. Prof. Popovski serves as a principal investigator (PI) and supervisor in multiple research projects, securing significant funding from national and international bodies such as the Danish National Research Foundation and the European Space Agency (ESA). He hosts visiting researchers regularly and contributes to scientific leadership through editorial roles and conference participation. He is a key figure in the Connectivity section at Aalborg University and leads cutting-edge research in future wireless systems, contributing to both theoretical foundations and practical implementations in smart infrastructure, space communication, and dependable 6G networks.