جست‌وجوی استاد و پژوهشگر

• Mobile Wireless Networking
• Information and Communication Technologies for Development (ICTD)
• Network Measurement
• +۵ مورد دیگر

Elizabeth M. Belding is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB). She holds leadership roles as an Associate Dean and Faculty Equity Advisor in the UCSB College of Engineering, and serves as Associate Director of the Center for Information Technology and Society (CITS). Her research focuses on mobile/wireless networking, network measurement, and ICTD, with a focus on improving Internet accessibility in underserved regions globally. She has authored over 180 technical papers and led the development of the AODV routing protocol, foundational to standards like 802.11s and Zigbee. Education: Ph.D./M.S. in Electrical and Computer Engineering from UCSB (2000/1997). Awards include ACM and IEEE Fellowships, the 2018 ACM SIGMOBILE Test-of-Time Award, and mentoring accolades. She directs the MOMENT Lab, exploring broadband measurement, rural connectivity, and satellite networks. Recent projects include the NSF-funded PuebloConnect initiative and analysis of US broadband inequities via the Connect America Fund. Research emphasizes socially impactful solutions, including tribal community internet access, disaster communication (e.g., refugee camps), and combating gender-based violence via social media analysis. She has held leadership roles in the UCSB CS department and campus-wide initiatives, including the Chancellor's Advisory Committee on the Status of Women. Key grants include NSF, Bill & Melinda Gates Foundation, and industry partnerships (e.g., ViaSat). Notable students include Udit Paul (2024 SIGCOMM Dissertation Award) and Jiamo Liu. The MOMENT Lab's work spans technical innovations in mesh networks, cellular coverage, and policy-driven broadband analysis.

• Telecommunication Networks
• Beyond 5G/6G Mobile Networks
• Edge/Cloud Computing
• +۷ مورد دیگر

Cicek Cavdar is an Associate Professor at the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Sweden. She leads the Intelligent Network Systems research group and specializes in Telecommunication Networks , with a focus on Beyond 5G/6G Mobile Networks , Energy Efficiency , and AI-Assisted Network Management . PhD in Computer Science (2009) from University of California, Davis and Istanbul Technical University Her research spans Cell-Free Massive MIMO , Reconfigurable Intelligent Surfaces (RIS) , UAV Communication Systems , and Green Network Technologies . She actively contributes to 6G Network Architecture and Non-Terrestrial Networks , including satellite and aerial systems. Recent publications highlight AI-driven network optimization for handover management, energy-aware resource allocation , and multi-agent reinforcement learning in complex communication environments. She teaches advanced courses in Communication Systems , Machine Learning , and Software Engineering at KTH.

Richard M. Murrayمشاهده پروفایل

استاد

• Control Theory
• Autonomous Vehicles
• Biological Circuit Design
• +۳ مورد دیگر

Richard M. Murray is the Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering at the California Institute of Technology (Caltech). He holds a B.S. from Caltech (1985), M.S. from UC Berkeley (1988), and Ph.D. from UC Berkeley (1990). He has served in academic roles from Assistant Professor (1991–1997) to his current endowed professorship. He chaired the Engineering and Applied Science division (2000–2005) and Biology and Biological Engineering (2020–2024). His research focuses on feedback control in biological and autonomous systems, synthetic cells, and networked control systems. Collaborators include experts in robotics, synthetic biology, and systems biology. Key awards include the IEEE Control Systems Award and election to the National Academy of Engineering. His educational contributions span courses on control systems, robotics, and bioengineering. Current research projects include the Developer Cell initiative (Sloan Foundation), layered testing for autonomous systems (AFOSR), and microbiome-based environmental solutions (CHARMME, ARO). He advises numerous graduate students and postdocs, with notable alumni in academia and industry. Labs include facilities in Keck and Steele laboratories at Caltech. His work bridges control theory, synthetic biology, and autonomous systems to address societal challenges like environmental monitoring and safe autonomy.

Srdjan Capkunمشاهده پروفایل

استاد

• Computer Security
• Network Security
• Wireless Security
• +۴ مورد دیگر

Prof. Srdjan Capkun is a Full Professor in the Department of Computer Science at ETH Zurich and Director of the Zurich Information Security and Privacy Center (ZISC). He holds a Dipl.Ing. from the University of Split (1998) and a Ph.D. from EPFL (2004). His research focuses on system and network security, including wireless security (e.g., secure positioning), trusted computing, blockchain technologies, and privacy-preserving systems. He co-founded 3db Access (acquired by Infineon) and Sound-Proof, addressing secure distance measurement and authentication. Notable achievements include an ERC Consolidator Grant (2016), ACM Fellowship, and IEEE Fellowship. Education: Dipl.Ing., Electrical Engineering / Computer Science, University of Split, 1998 Ph.D., Communication Systems, EPFL, 2004 Research Interests: Wireless security (e.g., UWB, GNSS, cellular) Trusted execution environments (TEEs) Blockchain and cryptocurrency systems Privacy-preserving technologies Awards & Grants: ERC Consolidator Grant (2016) ACM Fellow and IEEE Fellow Leadership of ZISC Advising & Labs: Leads the System Security Group at ETH Zurich Guided postdoctoral researchers and graduate students in security and privacy Companies: 3db Access (secure distance measurement) Futurae (online authentication)

• Data Science
• Machine Learning
• Computational Harmonic Analysis
• +۶ مورد دیگر

Pierre Vandergheynst is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) in the Department of Electrical Engineering, with a courtesy appointment in Computer and Communication Sciences. He serves as EPFL’s Vice-Provost for Education since 2015 and leads the Signal Processing Laboratory 2 (LTS2). His research spans harmonic analysis, sparse approximations, mathematical data processing, and applications in signal/image processing, computer vision, machine learning, and graph-based data analysis. PhD in Mathematical Physics (1998), Université catholique de Louvain Postdoctoral Researcher at EPFL (1998-2001) Assistant Professor at EPFL (2002-2007) His research explores geometry/symmetry in high-dimensional data, redundant dictionaries for dimensionality reduction, and computational harmonic analysis on manifolds. Recent work focuses on protein structure modeling, geometric deep learning, and graph-based signal processing. Key article trends include graph neural networks for protein analysis, geometric deep learning in neuroscience, and structured knowledge priors in neural models. His 2023-2025 publications emphasize interpretable AI, long-range dependencies in graphs, and molecular representation learning. Scientific Awards: IEEE Signal Processing Magazine Best Paper Award (2023) Signal Processing Society Best Paper Award (2022) Apple ARTS Award (2007) De Boelpaepe Prize, Royal Academy of Sciences of Belgium (2009-2010) He has supervised over 30 PhD theses and contributed to foundational work in graph signal processing, compressive sensing, and geometric deep learning. His lab develops tools for data science on non-Euclidean structures, with applications in medicine, astronomy, and wireless systems.

Yaojun Zhangمشاهده پروفایل

استادیار

• Biological Physics
• Biophysics
• Theoretical Physics
• +۳ مورد دیگر

Yaojun Zhang is an Assistant Professor in the Department of Physics & Astronomy and the Department of Biophysics at Johns Hopkins University. She earned her PhD in Physics from the University of California, San Diego (2015), followed by postdoctoral fellowships at the Princeton Center for Theoretical Science (2015-2018) and the Princeton Center for the Physics of Biological Function (2018-2021). Her research focuses on biological physics, particularly the complex behaviors of biomolecules and their assemblies across scales—from single-molecule folding to intracellular transport and biomolecular phase separation. She employs theoretical, mathematical, and computational tools to bridge biological questions with physical principles. Education PhD in Physics, University of California, San Diego (2015) Postdoctoral Fellowships: Princeton University (2015-2021) Research Interests Her group studies biomolecular condensates and liquid-liquid phase separation, exploring how microscopic interactions determine macroscopic properties of cellular compartments. Key areas include: Biomolecular condensate formation and dynamics Phase separation in cellular environments Interactions between biomolecules and cellular components Biophysics of intracellular transport Collaborations & Tools Zhang collaborates with experimentalists to validate theoretical models and develops frameworks for understanding condensate functions, such as surface tension, stoichiometry, and phase diagrams. Her work addresses challenges like condensate stability, molecular exclusion, and biological function regulation. Labs & Resources She leads the Zhang Lab , which integrates experimental and computational approaches. Her team’s research is supported by resources at the Bloomberg Center for Physics and Astronomy.

Ning Zhangمشاهده پروفایل

استادیار

• Plant Defense Mechanisms
• Genome Editing Technologies
• Crop Improvement
• +۳ مورد دیگر

Ning Zhang is an Assistant Professor in the Biology Department at James Madison University (JMU), joining in 2024. Her research focuses on enhancing crop resilience through molecular and biochemical studies of plant defense mechanisms against bacterial pathogens, alongside developing genome editing technologies for trait improvement. She holds a PhD in Horticulture and Crop Science from The Ohio State University (2016), an MS in Silviculture from Zhejiang Agriculture and Forestry University (2011), and a BS in Landscape Architecture from Shandong Agricultural University (2008). Research Interests: Dr. Zhang's lab investigates plant immunity pathways, CRISPR/Cas9 genome editing applications, and engineering crops for disease resistance. Her work integrates molecular biology, genetics, and biochemistry to tackle challenges posed by climate change and biotic/abiotic stresses. Recent Trends in Publications: Her articles concentrate on MAPK signaling pathways, NLR protein interactions, PP2C phosphatase regulation, and bacterial effector mechanisms in tomato and other crops. Key themes include immune system activation, pathogen recognition diversity, and transgenic plant development. Lab Information: The Zhang Lab at JMU is part of the Department of Biology, focusing on plant biotechnology solutions for agricultural sustainability. They collaborate on projects involving CRISPR-based gene editing and stress tolerance research.

• Synthetic Biology
• Systems Biology
• Quantitative Biology
• +۵ مورد دیگر

Ting Lu is an Associate Professor at the University of Illinois at Urbana-Champaign in the School of Biomedical and Translational Sciences, focusing on microbial synthetic biology and systems biology. Their research bridges biology, engineering, and physics to reprogram cellular functionalities through gene regulatory networks. Ph.D. in Biophysics, University of California at San Diego (2007) B.S. in Physics, Zhejiang University (2002) Ting Lu's work explores microbial ecosystems, synthetic gene circuits, and their applications in biotechnology and medicine. By combining experimental approaches with mathematical modeling, they investigate bacterial communication networks, metabolic pathways, and spatial dynamics in microbial communities. Selected research trends include microbial consortia engineering for bioremediation and bioproduction, complexity reduction in microbiomes, and predictive modeling of synthetic gene networks. Their publications span high-impact journals such as Nature Communications , Nature Chemical Biology , and eLife . Fellow, American Institute for Medical and Biological Engineering (2022) Future Insight Prize (2021) Donald Biggar Willett Faculty Scholar (UIUC) (2020) NIH Maximizing Investigators' Research Award (2019) NSF CAREER Award (2015) AHA National Scientist Development Grant (2012) Ting Lu's lab has received grants from NIH, NSF, ONR, and industry partners. They offer undergraduate research opportunities in synthetic and systems biology, and teach advanced courses such as BIOE 430 - Intro Synthetic Biology and BIOE 432 - Systems Biology .

Wei Xiangمشاهده پروفایل

استادیار

• Economics
• International Economics
• Macroeconomics
• +۳ مورد دیگر

Wei Xiang is an Assistant Professor of Economics at the University of Michigan's Department of Economics, housed within the College of Literature, Science, and the Arts. He earned his Ph.D. in Economics from Yale University in 2024, focusing on international trade, macroeconomics, and environmental economics. His research bridges economic theory with applied analyses, addressing global trade dynamics, macroeconomic policies, and environmental sustainability. Education: Ph.D. in Economics, Yale University (2024). Research Interests: His work explores the intersection of international trade policies, macroeconomic stability, and environmental regulations. He examines how trade agreements influence economic growth and environmental outcomes, with a focus on empirical methodologies to assess policy impacts. Additionally, he investigates macroeconomic models to understand global economic fluctuations and their implications for sustainable development. Publications: His recent articles highlight contributions to vehicle communication systems, signal processing, and wireless technologies, reflecting interdisciplinary engagement with engineering applications. These include real-time prediction models for GPS errors and beamforming optimization in vehicular networks. Labs/Teams: Not explicitly stated, but his research collaborations likely involve interdisciplinary teams in economics, engineering, and environmental science.

Andre Levchenkoمشاهده پروفایل

استاد

• Systems Biology
• Signal Transduction
• Cell Communication
• +۵ مورد دیگر

Andre Levchenko is the John C. Malone Professor of Biomedical Engineering at Yale University, with secondary appointments in the Department of Neurosurgery and affiliations with the Cancer Signaling Networks, Immunology, and the Yale Program in Neurodevelopment and Regeneration. His research focuses on systems biology, signal transduction, and cell-cell communication, utilizing microfluidics and computational modeling to study cancer progression, stem cell behavior, and neurological disorders. PhD, Columbia University MEng, Moscow Institute of Physics and Technology Levchenko's work explores how cells process dynamic signals to make critical decisions, particularly in glioblastoma migration, organoid development, and cardiovascular tissue engineering. His lab develops innovative microfluidic platforms and mathematical models to dissect multicellular communication and signaling networks. Recent publications highlight his contributions to understanding YAP-driven cancer invasion , NOTCH signaling in angiogenesis , and metabolic regulation of hypoxia responses . He has pioneered methods for organoid modeling and single-cell analysis , advancing precision in biological signaling studies. Scientific Awards : Computational Molecular Biology Post-Doctoral Fellowship (Burroughs Wellcome Fund) National Academies Keck Futures Conference Invitee Distinguished Guest Lecturer, University of Virginia American Asthma Foundation Early Excellence Award Fellow, American Institute for Medical and Biological Engineering Levchenko leads the Levchenko Lab at the Yale Systems Biology Institute, collaborating with institutions like Mayo Clinic and Yale Cancer Center. His research has received recognition in Faculty of 1000 and multiple journal highlights.

James Briscoeمشاهده پروفایل

استاد

• Developmental Biology
• Molecular Signaling
• Transcriptional Networks
• +۴ مورد دیگر

James Briscoe is a Senior Group Leader at The Francis Crick Institute in London, where he leads a research group focused on developmental biology and morphogen signaling. He previously held positions at the Medical Research Council's National Institute for Medical Research, which later became part of the Francis Crick Institute. Education: BSc in Microbiology and Virology from the University of Warwick, UK PhD from Imperial Cancer Research Fund/King's College London Postdoctoral training at Columbia University with Thomas Jessell Dr. Briscoe's research focuses on the molecular and cellular mechanisms of graded signaling by morphogens and the role of transcriptional networks in cell fate specification. His laboratory employs a range of experimental and computational techniques using model systems including mouse and chick embryos and embryonic stem cells. His work has significant implications for understanding developmental processes and their relationship to disease. His recent publications demonstrate a continued focus on morphogen gradients, neural tube development, and computational approaches to understanding cell fate decisions. His research increasingly integrates single-cell technologies and computational modeling to unravel the complexities of developmental patterning. Scientific Awards and Honors: EMBO Young Investigator (2001) EMBO Gold Medal (2008) Elected to EMBO (2009) Fellow of the Academy of Medical Sciences (2019) Fellow of the Royal Society (2019) As Editor-in-Chief of the journal Development since 2018, Dr. Briscoe plays a significant role in shaping the field of developmental biology. His leadership extends to mentoring researchers and contributing to scientific policy discussions, as evidenced by his recent publication 'Science under siege: protecting scientific progress in turbulent times.' Dr. Briscoe's laboratory at the Crick Institute is well-equipped with access to advanced facilities including light microscopy, flow cytometry, genomics, and computational resources, enabling a multidisciplinary approach to developmental biology questions.

Raul Astudillo Marbanمشاهده پروفایل

پژوهشگر

• Machine Learning
• Bayesian Optimization
• Decision-Making Systems
• +۵ مورد دیگر

Raul Astudillo Marban is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at Caltech, hosted by Professor Yisong Yue. He will join MBZUAI as a tenure-track Assistant Professor in August 2025. His research focuses on adaptive learning and decision-making in complex, data-intensive environments, with applications in personalized healthcare, engineering design, and scientific discovery. He earned his Ph.D. in Operations Research and Information Engineering from Cornell University under Professor Peter Frazier and holds an undergraduate degree in Mathematics from the University of Guanajuato and the Center for Research in Mathematics. His work integrates Bayesian optimization and machine learning to address real-world challenges such as protein engineering, plant breeding, and computational biology. Key contributions include steering generative models with experimental data, preferential multi-objective optimization, and cost-aware Bayesian strategies. He has received recognition as a Rising Star in Management Science and Engineering (Stanford) and a Rising Star in Data Science (University of Chicago/UCSD). Recent research highlights include optimizing protein fitness through generative models, active learning in directed evolution, and Bayesian optimization for budget allocation in agriculture. His publications span top venues like NeurIPS, Nature Communications, and TMLR. He actively recruits students/researchers for projects in machine learning and optimization.

John Paisleyمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Statistics
• Data Science
• +۳ مورد دیگر

John Paisley is an Associate Professor of Electrical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science, and a member of Columbia's Data Science Institute (DSI). He holds a B.S., M.S., and Ph.D. in Electrical and Computer Engineering from Duke University (2004-2010), followed by postdoctoral research in Computer Science at Princeton University and UC Berkeley. His research focuses on Bayesian models, posterior inference techniques for Big Data, and applications in data analysis, recommendation systems, information retrieval, and compressed sensing. He has pioneered methods like Bayesian Gaussian Process ODEs and Double Normalizing Flows, with recent work emphasizing uncertainty quantification in environmental modeling and neuroimaging analysis. His collaborative workflows (e.g., bneR ) address air pollution exposure and PM2.5 concentration uncertainties, combining Bayesian nonparametric ensembles with geospatial data. He has also developed frameworks for neural network interpretability, image denoising, and compressed sensing MRI. Paisley's work bridges statistical theory and applied machine learning, with applications in healthcare, environmental science, and geophysics. His academic contributions include over 50 publications since 2016, spanning topics like deep metric learning, adversarial learning, and variational inference optimization. He maintains an active research group and serves on editorial boards for machine learning and signal processing journals.

Ismail Guvencمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Networks
• UAV Networks
• +۶ مورد دیگر

Dr. Ismail Guvenc is a Full Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He holds an IEEE Fellowship and is a Senior Member of the U.S. National Academy of Inventors. His research focuses on 5G/6G wireless systems, UAV communications, heterogeneous networks, and spectrum management. He leads the NSF AERPAW project and serves as the NC State Site Director for the NSF BWAC I/UCRC center. Dr. Guvenc has authored/co-edited four books and holds over 30 U.S. patents. Education: Ph.D. in Electrical Engineering, University of South Florida (2006) Master's in Electrical and Computer Engineering, University of New Mexico (2003) Bachelor's in Electrical Engineering, Bilkent University, Turkey (2001) Research Interests: Dr. Guvenc’s work spans UAV communication systems, 5G/6G networks, spectrum sensing, and machine learning for network optimization. He emphasizes experimental validation through platforms like AERPAW, focusing on drone-based networks, radio dynamic zones, and testbed-driven innovation. His contributions address challenges in UAV localization, interference management, and energy-efficient networks. Grants & Leadership: PI and Director of NSF AERPAW (2019–Present) NC State Site Director for NSF BWAC I/UCRC (2019–Present) Recipient of NSF CAREER Award (2015) and NC State Faculty Scholar Award (2021) Publications & Awards: He has authored over 130 peer-reviewed papers and contributed to standardization efforts. His awards include the R. Ray Bennett Faculty Fellow Award (2019) and the USF Outstanding Dissertation Award (2006). Labs & Teams: Dr. Guvenc directs research in the ECE’s wireless communications group, leveraging AERPAW’s experimental capabilities to advance UAV networks and 6G technologies. His team collaborates with industry and government on spectrum policy and autonomous systems.

Aline Eidمشاهده پروفایل

استادیار

• Applied Electromagnetics
• RF Circuits
• Wireless Sensing
• +۶ مورد دیگر

Aline Eid is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Michigan Ann Arbor, directing the Beam Dynamics research group. Her work bridges electromagnetics, wireless systems, and autonomous technologies, with a focus on mmWave/sub-THz sensing, backscatter communications, and wireless power transfer. PhD in Electrical and Computer Engineering (Georgia Tech, 2021) MS in Electrical and Computer Engineering (American University of Beirut, 2017) Postdoctoral Associate at MIT Media Lab (Signal Kinetics group) Research Interests: She pioneers systems that use electromagnetic waves to address societal challenges in Sustainable energy networks Smart cities/infrastructures Autonomous vehicles/robots Her group develops mmID tags for radar vision, batteryless sensors, and 5G-based wireless power grids. Scientific Impact: Recognized with awards including IEEE RFID Best Paper (2023) Proceedings of the IEEE Best Paper (2023) IEEE MTT-S Graduate Fellowship (2020) She leads commercialization efforts for warehouse robotics via MTRAC grant and startup Atheraxon. Advising: Mentors 8 students across PhD (Skanda Harisha, Sepideh Ghasemi, Yunfei Liu), Master's (Longyu Guo), and undergraduates (Mohamed Safawi, Katherine Shih, Andy Wang, Adrian Velazquez) in projects spanning robotics, IoT, and electromagnetic engineering. Labs: Beam Dynamics group at U-M Radiation Laboratory, collaborating with Atheraxon and MTRAC for technology translation.