جستجوی استاد راهنمای دانشگاهی

Osman Yağanمشاهده پروفایل

استاد پژوهش

• Machine Learning
• Data Science
• Network Science
• +۷ مورد دیگر

Osman Yağan is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with affiliate faculty status in the School of Computer Science. He is also a core member of CyLab Security and Privacy Institute. Prior to joining CMU in 2013, he was a Postdoctoral Research Fellow at CyLab. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2011) and a B.S. from Middle East Technical University (2007). His research focuses on modeling, analysis, and optimization of computing systems, leveraging applied probability, network science, data science, and machine learning. Key areas include multi-armed bandits, resilient machine learning, contagion processes in networks, and cybersecurity. Research Interests include Machine Learning, Data Science, Network Science, Cybersecurity, and Robustness in Cyber-Physical Systems. He has advised numerous students, including current PhD candidates Yurun Tian, Orkun İrsoy, and Ishank Juneja, as well as notable alumni such as Mansi Sood (now at MIT) and Jun Zhao (Assistant Professor at Nanyang Technological University). Key Awards include the CIT Dean's Early Career Fellowship, IBM Academic Award, and Best Paper Awards at ICC 2021, IPSN 2022, and ASONAM 2023. His work spans theoretical contributions (e.g., contagion models in multi-layer networks) and applied research (e.g., mitigating cascading failures in power systems). He leads or co-leads grants from ONR, NSF, and ARO, focusing on resilient machine learning, network robustness, and pandemic modeling.

Christoph Keplingerمشاهده پروفایل

استاد

• Soft Robotics
• Functional Polymers
• Energy Capture
• +۴ مورد دیگر

Christoph Keplinger serves as Managing Director of the Max Planck Institute for Intelligent Systems (MPI-IS) in Stuttgart, Germany, leading the Robotic Materials Department since 2020 and assuming overall institute leadership in 2023. He holds dual academic appointments as Honorary Professor at the University of Stuttgart and Eminent Visiting Professor of Soft Robotics at the University of Colorado Boulder, establishing him as a pivotal figure in bridging fundamental materials science with advanced robotics. His interdisciplinary approach integrates physics, chemistry, and engineering to pioneer breakthroughs in soft robotic systems. Keplinger's academic foundation includes a PhD in Soft Matter Physics from Johannes Kepler University Linz, Austria, followed by postdoctoral research at Harvard University focusing on mechanics and chemistry of soft materials. This unique background enabled his transition into robotics innovation, particularly in electrohydraulic actuation systems. His research program centers on three synergistic pillars: (I) soft robotics development through novel actuator technologies like HASEL artificial muscles; (II) energy capture mechanisms using soft materials; and (III) functional polymers engineered for robotic applications. This work produces transformative hardware that mimics biological functionality, with significant implications for human-robot interaction, medical devices, and sustainable robotics systems. His group employs cutting-edge materials synthesis and characterization techniques to create lifelike robotic components. Analysis of recent publications reveals dominant trends in wearable haptic interfaces, electrohydraulic actuation systems, and tremor-suppression technologies. The research consistently leverages HASEL (Hydraulically Amplified Self-healing Electrostatic) technology to achieve muscle-like performance in soft actuators, with applications spanning from fingertip haptic feedback to underwater manipulation systems. This trajectory demonstrates a clear progression from fundamental material properties toward practical implementations in medical rehabilitation and human augmentation. His exceptional contributions have earned prestigious recognition: 2017 Packard Fellowship for Science and Engineering, awarded for high-impact interdisciplinary research 2021 Alexander von Humboldt Professorship (declined to remain at MPI-IS), Germany's most valuable international research award 2013 EAPromising European Researcher Award from the European Scientific Network for Artificial Muscles As principal investigator, Keplinger leads a dynamic interdisciplinary research group while securing competitive funding for frontier projects. His entrepreneurial vision materialized in 2018 through co-founding Artimus Robotics, where he serves as Chief Science Officer to commercialize HASEL technology. This dual commitment to academic research and industry translation exemplifies his dedication to real-world impact, particularly in creating biodegradable and sustainable soft robotic solutions. The Robotic Materials Department operates state-of-the-art facilities for materials fabrication, robotic integration, and haptic interface development. The team maintains strong collaborations across MPI-IS departments and external institutions including the University of Colorado Boulder, fostering innovation in sustainable robotics through initiatives like biodegradable electrohydraulic actuators. Current projects focus on wearable tremor suppression systems, electrohydraulic locomotion platforms, and energy-autonomous soft robots that address critical challenges in medical rehabilitation and human augmentation.

Yongmin Liuمشاهده پروفایل

استاد

• Nano Optics
• Nanomaterials Engineering
• Plasmonics
• +۵ مورد دیگر

Yongmin Liu is a Professor in Mechanical and Industrial Engineering and Electrical & Computer Engineering at Northeastern University, and a member of the Cross-College Magnetics Center. He holds a PhD in Applied Science and Technology from UC Berkeley (2009), with earlier degrees from Nanjing University. His research focuses on nano-optics, metamaterials, plasmonics, and their applications in optical devices and systems. His interdisciplinary work bridges engineering, physics, and AI, with notable contributions to metasurface design and optical neural networks. Education: PhD, Applied Science and Technology, UC Berkeley (2009) M.S. and B.S., Physics, Nanjing University (2003, 2000) Research Interests: Nano-optics, nanoscale materials engineering, metamaterials, plasmonics, and applied physics. His group develops novel optical materials and devices for applications like super-resolution imaging, efficient light harvesting, and biomedical detection. Recent projects include AI-driven photonic materials design and meta-optical neural networks. Key Achievements: Recipient of the Søren Buus Outstanding Research Award (2024) NSF CAREER Award (2017) and ONR Young Investigator Award (2016) Elected SPIE Fellow (2023) and Optica Fellow (2023) Lab & Collaborations: Head of the Yongmin Liu Research Group, collaborating with institutions like Georgia Tech and Purdue University. Recent grants include a $1.5M NSF DMREF grant for AI-driven photonic materials and a $468K NSF grant for meta-optical neural networks.

Jun Liuمشاهده پروفایل

استادیار

• Advanced energy materials
• Nano/micro-mechanics
• Self-powered electronics and systems
• +۲ مورد دیگر

Jun Liu is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the School of Engineering and Applied Sciences, University at Buffalo. His research focuses on advanced energy materials, nano/micro-mechanics, and self-powered systems, with applications in triboelectric energy harvesting and scanning probe microscopy. Education: PhD, Materials Engineering, University of Alberta (2018) MS, Materials Science, Shanghai University (2015) BE, Materials Science and Engineering, Nanchang University (2012) Research Interests: Development of tribovoltaic and triboelectric systems for self-powered electronics Mechanical energy harvesting via dynamic heterojunctions and Schottky contacts 3D-printed hydrogel structures for energy absorption and flexible electronics Nanoscale characterization using atomic force microscopy Design of nanocomposite sensors and catalytic materials Publication Trends: His work emphasizes triboelectricity, nanoscale energy conversion, and sustainable materials. Recent articles explore bionic tactile sensing, tunable hydrogels, and quantum dynamics in sliding interfaces. Awards: SONY Faculty Innovation Award (2021) Nature Springer MINE Young Scientist Award (2020) International Contest of Applications in Nano/Micro Technology Prize (2013) Laboratory: Advanced Energy Materials and Nanomechanics Lab at University at Buffalo.

Yuguo Chenمشاهده پروفایل

استاد

• Network Analysis
• Monte Carlo Methods
• Statistical Inference
• +۷ مورد دیگر

Yuguo Chen is a Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign (UIUC), serving as Interim Department Chair and Director of the Illinois Statistics Office. He holds affiliations with the Department of Computer Science, Information Trust Institute, Coordinated Science Lab, and Illinois Informatics Institute. Chen earned his PhD in Statistics from Stanford University (2001) and a B.S. in Mathematics from the University of Science and Technology of China (1997). His research focuses on Monte Carlo methods, network data analysis, state space models, bioinformatics, and Bayesian inference. Key interests include scalable network estimation, community detection, and applications in public health, education, and computational biology. Recent work highlights include advancements in dynamic network modeling, Bayesian latent class models for cognitive diagnosis, and statistical methods for analyzing multi-layer networks. His contributions have been recognized through awards such as the American Statistical Association Fellowship (2018) and the Charles Edison Lectureship (2018). Editorial Roles: Associate Editor of Journal of the American Statistical Association , Journal of Computational and Graphical Statistics , and Journal of Algebraic Statistics . Grants & Consulting: Directs the Illinois Statistics Office, providing interdisciplinary research support. Active in collaborative projects involving healthcare, education, and computational infrastructure. Labs & Teams: Leads initiatives at the Coordinated Science Lab and Information Trust Institute, integrating statistical methods with cybersecurity and data-driven decision-making.

Hong Hanمشاهده پروفایل

استادیار

• Cancer Biology
• Gene Regulation
• RNA Splicing
• +۵ مورد دیگر

Hong Han is an Assistant Professor in the Department of Biochemistry & Biomedical Sciences within McMaster University's Faculty of Health Sciences and a member of the Centre for Discovery in Cancer Research (CDCR). She holds a Canada Research Chair and leads the Han Lab, which focuses on cancer biology, RNA regulation, and innovative high-throughput technologies for therapeutic discovery. Dr. Han earned her Ph.D. from the University of Toronto (2010-2016) and has established herself as a leading researcher in glioblastoma and alternative splicing regulation. Her interdisciplinary research integrates cancer biology, RNA science, and multilayer gene regulation to uncover mechanisms underlying cancer progression and treatment resistance. Her laboratory pioneers integrated technological platforms for large-scale genetic/drug screening and ultra-high-throughput single-cell profiling. The research focuses on three main areas: alternative splicing regulation in cancer (particularly glioblastoma and prostate cancer), multilayer mechanisms of glioblastoma heterogeneity and microenvironment evolution, and multiplexed screening approaches for therapeutic discovery in treatment-resistant cancers. Analysis of Dr. Han's recent publications reveals a strong emphasis on single-cell technologies to characterize glioblastoma heterogeneity, minimal residual disease states, and tumor-immune interactions. Her work increasingly bridges basic RNA biology with translational applications, particularly in developing novel therapeutic strategies targeting splicing networks and immune evasion mechanisms. Canada Research Chair Dr. Han teaches Advanced Techniques in the Biomedical Sciences (BIOCHEM 734). Her research program is supported by multiple funding sources, as evidenced by her extensive publication record in high-impact journals including Nature, Cell, Molecular Cell, and Nature Communications. She employs a comprehensive approach combining in vitro, in vivo, and patient cohort studies with cutting-edge genomic technologies. The Han Lab has developed innovative multiplexed screening platforms that enable simultaneous interrogation of thousands of conditions, ranging from CAR-T cells to small molecule therapeutics. This approach accelerates the discovery of novel cancer targets and therapeutic strategies for treatment-resistant cancers.

• Supramolecular Chemistry
• Coordination Chemistry
• Materials Science
• +۴ مورد دیگر

Kay Severin is a full professor at the Laboratory of Supramolecular Chemistry (LCS) within École Polytechnique Fédérale de Lausanne (EPFL) , Switzerland. His research focuses on the design and reactivity of metal-ligand assemblies, including coordination cages, metalloligands, and supramolecular receptors. He has pioneered the use of metalloligands for constructing heterometallic architectures and developed systems for anion extraction and stimuli-responsive hydrogels. Key funder: Swiss National Science Foundation (FNS) Collaborative work with Rosario Scopelliti and Farzaneh Fadaei Tirani Research Interests: Severin's work spans supramolecular chemistry, organometallic synthesis, and functional materials. Recent projects include: Dynamic palladium-based hydrogels with anion-responsive crosslinks Gold(I)-driven nano-onion structures via π-stacking Triazene-derived ligands for Sandmeyer-type reactions Metalloligand assembly of Fe/Pd/Au heterotrimetallic cages Publication Trends: Over 300 publications since 1994, with recent emphasis on: Coordination-driven self-assembly (2024: 6 articles) Triazene and diazoolefin reactivity (2025: 4 articles) Metal-ligand interactions in nanogels and vesicles (2024-2025: 3 articles) Environmental applications in anion extraction (2025: 1 article)

Dmitri Krioukovمشاهده پروفایل

دانشیار

• Network Science
• Complex Networks
• Mathematical Physics
• +۷ مورد دیگر

Prof. Dmitri Krioukov is an Associate Professor in the Department of Physics at Northeastern University and holds an affiliated faculty position in Electrical and Computer Engineering. He directs the DK-Lab at the Network Science Institute, focusing on theoretical aspects of complex networks, including latent network geometry, random geometric graphs, and navigation in networks. His work bridges mathematical physics and applied network science, with applications to real-world data such as the Internet's structure. Research interests revolve around the interplay between network topology and geometry, including studies of causal sets, graph curvature, and dynamics in complex systems. He has pioneered frameworks linking network growth to hyperbolic geometry, enabling efficient routing algorithms. Notable contributions include the discovery of latent geometric structures underlying real-world networks and their implications for navigation and scalability. He has been recognized for high-impact publications, including multiple Stanford University Annual Assessments placing him among the top 2% most-cited scientists in his field (2024, 2023, 2022). His lab's interdisciplinary approach integrates principles from physics, mathematics, and computer science to address fundamental questions in network science.

Wai Pang Ngمشاهده پروفایل

استاد

• Radio-over-Fiber
• Optical Communications
• Fiber Optic Sensors
• +۳ مورد دیگر

Wai Pang Ng is a Professor and Head of the Department of Mathematics, Physics and Electrical Engineering at Northumbria University. He holds a BEng (Hons) in Communications and Electronic Engineering from the University of Northumbria and a PhD in Electronic Engineering from the University of Wales, Swansea. His research focuses on radio-over-fiber systems, distributed fiber sensing, high-speed optical communications, and adaptive signal processing. Ng has held leadership roles in IEEE chapters and conferences, including chairing the IEEE UK&RI Communications Chapter (2011–2015) and serving as publicity chair for IEEE ICC 2015 and 2016. His research interests include innovative fiber optic sensor designs, acoustic wave devices for biomedical applications, and hybrid communication systems combining radio-over-fiber and free-space optics. Recent work emphasizes ultra-sensitive pressure/temperature sensors using microstructured fibers and acoustofluidic platforms for lab-on-a-chip applications. Ng has supervised seven PhD/MSc projects and actively contributes to standards development in optical communication systems. Ng’s publications span advanced sensor technologies, nonlinear compensation in optical systems, and turbulence-resistant free-space optical links. His work bridges academic research with practical applications in telecommunications, environmental monitoring, and healthcare diagnostics. Professional affiliations include IEEE technical committees (SPCE, TCGCC, ONTC) and guest editorships for IET Communications.

Matteo Magnaniمشاهده پروفایل

استاد

• Network Science
• Social Network Analysis
• Computational Social Science
• +۱۰ مورد دیگر

Matteo Magnani is a Professor in the Division of Computing Science at the Department of Information Technology, Uppsala University. He leads the Uppsala University Information Laboratory and is a founding member of the Uppsala University Computational Social Science Lab. His research spans network science, artificial intelligence, data science, and computational social science, with a focus on social data mining and multilayer networks. PhD in Computer Science, University of Bologna, 2006 Graduated with honours in Information Sciences, University of Bologna, 2002 Studies in Computer Science at University of Marne la Vallée and Imperial College London Matteo Magnani's research interests include social network analysis, multilayer and probabilistic networks, community detection, visual analytics, and the application of AI to digital media and climate communication. His work bridges computer science and social sciences, particularly in analyzing online discourse and digital intermediaries. He has contributed significantly to the understanding of network structures, uncertainty in networks, and the ethical dimensions of algorithmic analysis. His recent publications highlight trends in fairness in community detection, visual saliency in network layouts, emotional reactions to climate visuals online, and deep learning applications in social media. Topics frequently involve YouTube, Twitter, and online public debates, using advanced network and machine learning methods. Rotary Prize for best student of the Science Faculty Best Paper Award Funniest Presentation Award Best Poster Award Pedagogical Prize from UTN Distinguished University Teacher (Sweden) Docent title (Sweden) Magnani has supervised numerous students and collaborated widely, particularly with Luca Rossi, Alexandra Segerberg, and Davide Vega. He has secured funding from major sources including VR, H2020, STINT, and MIUR. He leads active research labs focused on information systems and computational social science, fostering interdisciplinary collaboration and innovation in network-based research.

Carey E. Priebeمشاهده پروفایل

استاد

• computational statistics
• statistical pattern recognition
• statistical image analysis
• +۵ مورد دیگر

Carey E. Priebe is a Professor in the Department of Applied Mathematics and Statistics at the Whiting School of Engineering, Johns Hopkins University. He maintains strong affiliations with multiple research centers including the Johns Hopkins University Center for Imaging Science, the Mathematical Institute for Data Science, and the Human Language Technology Center of Excellence. His academic career spans several decades with significant contributions to statistical methodology and theory. Dr. Priebe's research focuses on computational statistics, statistical pattern recognition, and statistical inference for high-dimensional and graph data. His work bridges theoretical statistics with practical applications in areas such as brain connectome mapping, network analysis, and image processing. He has made significant contributions to spectral graph theory, graph matching, and vertex nomination, with applications ranging from neuroscience to national security. His publication record demonstrates consistent contributions to statistical methodology, with a notable emphasis on graph-based statistical methods. His research trajectory shows increasing focus on network data analysis, particularly in the last decade, with applications to brain mapping and connectome analysis as evidenced by his NSF BRAIN Initiative grant and Nature publication. 2013 Erskine Fellow (University of Canterbury) 2011 McDonald Award for Excellence in Mentoring and Advising 2010 ASA SDNS Distinguished Achievement Award 2009 Erskine Fellow (University of Canterbury) 2008 National Security Science and Engineering Faculty Fellow 2008 Pond Award for Excellence in Teaching NSF BRAIN EAGER grant recipient (2014) Professor Priebe has supervised an extensive number of doctoral students whose work spans statistical methodology, network analysis, and machine learning. His students have secured positions at prestigious institutions including academia (University of Wisconsin, Boston University), government research labs, and major technology companies (Microsoft, Facebook, Amazon). His research has been supported by significant grants from NSF, DARPA, and other agencies focused on national security applications and fundamental statistical methodology development. He maintains active collaborations across multiple disciplines and institutions, as evidenced by his numerous conference presentations and visiting appointments including at The Alan Turing Institute and The Isaac Newton Institute. His work bridges theoretical statistics with practical applications in neuroscience, security, and data science.

Eleanor Powerمشاهده پروفایل

دانشیار

• Social Network Analysis
• Ethnography
• Religion and Society
• +۵ مورد دیگر

Dr. Eleanor Power is an Associate Professor in the Department of Methodology at the London School of Economics and Political Science (LSE). Her research focuses on the interplay between belief, practice, identity, and social relationships, with a particular emphasis on how reputational dynamics shape social inequality and cooperation. She combines ethnographic methods with social network analysis to study these phenomena in South India and cross-culturally. Education: Eleanor holds a PhD in Anthropology from Stanford University (2015). Prior to joining LSE in 2017, she was an Omidyar Postdoctoral Fellow at the Santa Fe Institute. She is fluent in English and Tamil. Research Interests: Eleanor examines signaling theory, religious practice, and the micro-dynamics of social inequality, including the 'reputational poverty trap.' Her current projects include co-directing the ENDOW project on social and economic inequality and leading the Rep2SI project on reputational dynamics. Her work bridges anthropology, sociology, and computational social science. Publications: Her recent work explores latent network models, cooperative behavior in South Indian communities, and the role of reputation in human social networks. She also collaborates on interdisciplinary projects, such as analyzing reproductive inequality across species and the impact of art workshops on prisoners' well-being. Awards: While no specific awards are listed, her research has been highlighted in LSE's 30th Anniversary celebrations for its interdisciplinary innovation and collaborative nature. Grants and Labs: Eleanor leads the Rep2SI project and co-directs the ENDOW project, indicating active grant-funded research. She is affiliated with LSE's Department of Methodology and has collaborated with institutions like the Santa Fe Institute.

• Photonics
• Materials Science
• Energy Technology
• +۳ مورد دیگر

Dr. Pier-John Sazio is a Principal Research Fellow at the University of Southampton. He is affiliated with the Smart Lasers and Special Fibres research group and has been involved in multiple research projects funded by the Engineering and Physical Sciences Research Council (EPSRC) and the United States Air Force. His work focuses on advanced materials engineering, photonics, and energy technologies, including photonic fibre technologies for solar fuels, solid-state batteries, and infrared sources. Research projects include: Roll-2-Roll (R2R) Manufacture of multilayer solid-state batteries Composite material hollow core fibres for active photonics Photonic Fibre Technologies for Solar Fuels Catalysis Zinc Selenide Fiber Infrared Sources & Isolators His research interests span photonics, materials engineering, and nanotechnology applications in energy storage and optoelectronics. He collaborates with international teams through initiatives like the Materials World Network. While no specific publications are listed here, his projects reflect contributions to cutting-edge materials and photonics research. Dr. Sazio has secured funding for over a dozen projects, demonstrating expertise in translating fundamental research into applied technologies. He is part of interdisciplinary teams addressing challenges in renewable energy, defense, and advanced manufacturing.

• Materials Science
• Condensed Matter Physics
• Nanotechnology
• +۳ مورد دیگر

Dr. Qingbo Sun is a researcher at the Department of Materials Physics, Australian National University, specializing in advanced materials for energy and electronic applications. His work focuses on defect engineering, dielectric materials, and photovoltaic effects in nanocrystalline systems. Research interests include: Defect-driven local symmetry breaking Colossal dielectric permittivity Photocatalytic heterojunctions High-pressure material transformations Doping strategies in semiconductors Nonlinear electric polarization Research trends from his publications highlight innovations in TiO2-based photocatalysts, SnO2 dielectrics, and ferroelectric heterostructures. Collaborations span materials synthesis, computational modeling, and international experimental studies. His work is cited extensively in Scopus with 294 citations.

Jane Guمشاهده پروفایل

استاد

• High Efficiency Interconnect
• Low Power Interconnect
• Millimeter-Wave Systems
• +۶ مورد دیگر

Q. Jane Gu is a Professor at the School of Electrical and Computer Engineering at Georgia Tech since September 2024, holding the Ed and Pat Joy Professorship. Previously, she was at the University of California, Davis (2012–2024) and the University of Florida (2010–2012). She earned her Ph.D. in Electrical Engineering from UCLA in 2007. Her research focuses on high-efficiency, low-power interconnects, millimeter-wave, sub-mm-wave, and terahertz integrated circuits and systems for applications in communication, radar, and imaging. Notable contributions include sub-THz resonator-based sensors, dielectric waveguide interconnect channels, and energy-efficient transmitters. Recipient of NSF CAREER Award (2013) 2015 UC Davis Outstanding Junior Faculty Award 2017 and 2018 Qualcomm Faculty Awards 2019 UC Davis Chancellor’s Fellow 2022–2023 IEEE SSCS Distinguished Lecturer Her group has garnered nine best paper awards, including top honors at the 2016, 2017, and 2020 IEEE MTT-S International Microwave Symposia. Research interests span terahertz interconnects, millimeter-wave radar systems, and integrated circuits for high-speed communication. Publications reflect advancements in sensor design, high-frequency transceivers, and phased-array systems, emphasizing energy efficiency and signal integrity.