جست‌وجوی استاد و پژوهشگر

• Wireless Communications
• Cognitive Radio
• Massive MIMO
• +۷ مورد دیگر

Professor Wei Zhang is a Full Professor at the School of Electrical Engineering & Telecommunications, University of New South Wales (UNSW), where he has been serving since May 2008, progressing from Senior Lecturer (2008-2012) to Associate Professor (2013-2017) and finally to Full Professor in November 2017. He received his PhD degree in Electronic Engineering from the Chinese University of Hong Kong in 2005 and was a Research Fellow at the Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology from 2006 to 2007. Professor Zhang's research spans cognitive radio, massive MIMO, 5G/6G networks, UAV communications, orbital angular momentum, and reconfigurable intelligent surfaces. His publications demonstrate a strong theoretical foundation combined with practical implementations, addressing critical challenges in modern wireless systems including spectrum efficiency, secure communications, and network intelligence. With over 200 papers in IEEE journals and conferences along with three authored books, his work has significantly impacted the field of wireless communications. Analysis of his recent publications (2023-2025) reveals a clear trajectory toward next-generation wireless technologies with emphasis on reconfigurable intelligent surfaces (RIS), orbital angular momentum (OAM), non-orthogonal multiple access (NOMA), and the integration of machine learning with traditional communication techniques. A substantial portion of his current work focuses on satellite-terrestrial integrated networks, UAV communications, and secure wireless transmission techniques, showing increasing sophistication in addressing complex communication challenges through innovative approaches. Professor Zhang's scientific achievements have been recognized with prestigious honors including: Fellow of the IEEE Fellow of the IET Distinguished Lecturer of IEEE Communications Society (2016-2017) His leadership in the academic community is evident through his editorial roles as Editor-in-Chief of IEEE Wireless Communications Letters (2016-2019) and currently as Editor-in-Chief of Journal of Communications and Information Networks (JCIN). As Area Editor of IEEE Transactions on Wireless Communications and former editor for multiple IEEE Transactions journals, he has significantly influenced the direction of wireless communications research. His active participation in major IEEE conferences as TPC Chair and Co-Chair demonstrates his commitment to advancing the field through scholarly exchange. Currently serving as Chair of IEEE Wireless Communications Technical Committee and Vice Director of IEEE Communications Society Asia Pacific Board, Professor Zhang continues to shape the future of wireless communications research globally, bridging the gap between academic innovation and industry implementation in next-generation wireless networks.

Joseph Glazمشاهده پروفایل

استاد

• Applied Probability
• Geometrical Probability
• Probability Approximations
• +۷ مورد دیگر

Joseph Glaz is a Professor in the Department of Statistics at the University of Connecticut. His work focuses on applied probability and statistical methodology, particularly in scan statistics and related inference techniques. Contact: joseph.glaz@uconn.edu Phone: (860) 486-4193 (Storrs Campus) Research highlights: Develops scan statistics for discrete , continuous , and conditional data frameworks Specializes in change-point detection for normal data mean/variance Innovates robust methods for outlier-prone datasets Extends scan statistics to network and graph structures Contributed to foundational texts like the Handbook of Scan Statistics Publication trends include: Scan statistics for genomic data (Hi-C translocation detection) Nonparametric and Bayesian extensions of scan methods Approximations and inequalities for sequential testing Applications in quality control , medical imaging , and sensor networks

• Electric Machines
• Permanent Magnet Motors
• Reluctance Motors
• +۷ مورد دیگر

Lale Ergene is a Professor in the Department of Electrical Engineering at Istanbul Technical University (ITU), College of Engineering. Her research focuses on advanced electric machine design and control systems for industrial and automotive applications. She is actively involved in motor drive innovation, particularly in permanent magnet and reluctance motor technologies. Research Interests: Dr. Ergene specializes in electric machines, with emphasis on Permanent Magnet Synchronous Motors (PMSM), Interior Permanent Magnet (IPM) motors, and Permanent Magnet Assisted Synchronous Reluctance Motors (PMaSynRM). Her work spans sensorless control, field weakening techniques, finite element analysis, and motor optimization for electric vehicles and home appliances. She applies intelligent control methods such as neuro-fuzzy systems and real-time diagnostics. Recent Research Trends: Her recent publications (2023–2024) show a strong focus on improving motor efficiency and control robustness, especially in EV traction systems and white goods. Key themes include voltage distortion reduction, flux weakening enhancement, real-time parameter estimation using FFT, and lean sensorless control at zero/low speeds. Her work bridges theoretical modeling with industrial applications. Scientific Awards: Best Poster Paper AWARD (2016) Graduation Design and Project Competition 2nd Prize (2015) ITU 2014 Best Doctoral Thesis Award (2015) Advising and Grants: Dr. Ergene has supervised or is currently supervising 25 theses, indicating a strong mentoring role. She has led multiple funded projects, including TÜBİTAK and ITU BAP grants, focusing on FPGA-based neural network control, three-level inverter design, real-time model diagnostics, and sensorless control for washing machines and EVs. Her projects demonstrate sustained research funding and applied engineering impact. Labs and Research Teams: While specific lab names are not mentioned, her projects imply leadership in a motor control and electric machines research group at ITU, likely involving FPGA, real-time simulation, and embedded control systems. Her collaborations with researchers like A.F. Ergenc, M. Yilmaz, and A. Tap suggest an active, multidisciplinary team focused on next-generation motor drives.

Shunqiao Sunمشاهده پروفایل

استادیار

• Statistical Signal Processing
• Sparse Signal Processing
• Mathematical Optimization
• +۷ مورد دیگر

Dr. Shunqiao Sun is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Alabama, College of Engineering. He joined the faculty in August 2019 as a tenure-track professor after working at Aptiv’s radar core team in Malibu, California. His research focuses on advanced signal processing, machine learning, and optimization for automotive and MIMO radar systems in autonomous vehicles. Ph.D. : Electrical and Computer Engineering, Rutgers University, 2016 M.S. : Electrical Engineering, Fudan University, 2011 B.S. : Electrical Engineering, Southern Yangtze University, 2004 Dr. Sun's research lies at the intersection of statistical and sparse signal processing , mathematical optimization , and machine learning , with applications in automotive radar , MIMO radar , and autonomous driving . His work emphasizes sparsity-oriented frameworks, AI-powered radar perception, and high-resolution 4D sensing. He leads a dynamic research group focused on next-generation radar technologies for intelligent transportation systems. His recent publications demonstrate a strong trend in deep learning for radar signal recovery , collaborative radar imaging , direction-of-arrival estimation with sparse arrays , and integrated sensing and communication . Several of his papers are among the most downloaded and cited in IEEE journals, including top articles in IEEE Signal Processing Magazine and IEEE Journal of Selected Topics in Signal Processing. Scientific Awards and Honors: NSF CAREER Award (2024) NSF CRII Award (2022) IEEE AESS Robert T. Hill Best Dissertation Award (2016) Best Student Paper Award at IEEE SAM Workshop (2020) Rutgers ECE Academic Achievement Award (2015–2016) University of Alabama Hewson Engineering Faculty Fellow (2025) Dr. Sun is actively involved in academic service and leadership. He is an Associate Editor for IEEE Signal Processing Letters and IEEE Open Journal of Signal Processing . He serves as Vice Chair of the IEEE Signal Processing Society’s Autonomous Systems Initiative and is an elected member of the IEEE Sensor Array and Multichannel (SAM) Technical Committee and the Integrated Sensing and Communication (ISAC) Technical Working Group. He has co-organized numerous workshops and special sessions at ICASSP, EUSIPCO, and IEEE Radar Conference. His lab has secured significant research funding from the National Science Foundation , NXP Semiconductors , MathWorks , and NOAA . He mentors multiple Ph.D. students, several of whom have interned at leading industry labs such as NXP and GM Cruise. He has co-organized the Workshop on Signal Processing for Autonomous Systems (SPAS) at ICASSP and EUSIPCO and delivered invited seminars at institutions including TU Delft, UC Davis, and Lehigh University.

Nikolaos Sidiropoulosمشاهده پروفایل

استاد

• Signal Processing
• Machine Learning
• Wireless Communications
• +۵ مورد دیگر

Nikolaos Sidiropoulos is the Louis T. Rader Professor in the Department of Electrical and Computer Engineering at the University of Virginia, School of Engineering and Applied Science. He has previously held faculty positions at the University of Minnesota and the Technical University of Crete, Greece. His research bridges signal processing, machine learning, and communications, with a strong emphasis on tensor decomposition and optimization. His research interests include: Signal Processing Machine Learning Wireless Communications Optimization Tensor Decomposition Cyber-Physical Systems Data Science His educational background includes a Diploma in Electrical Engineering from Aristotle University of Thessaloniki (1988), and M.S. and Ph.D. degrees from the University of Maryland, College Park (1990, 1992). His recent publications focus on tensor methods, deep learning integration with clustering, and physical layer multicasting, reflecting a trend toward interdisciplinary methodologies that combine classical signal processing with modern machine learning. Notable scientific awards include: NSF/CAREER Award (1998) IEEE SPS Best Paper Awards (2001, 2007, 2011, 2022) IEEE SPS Donald G. Fink Overview Paper Award (2022) IEEE SPS Claude Shannon–Harry Nyquist Technical Achievement Award (2022) EURASIP Technical Achievement Award (2022) Distinguished Research Award, University of Virginia (2023) Fellow of IEEE (2009) and EURASIP (2014) Distinguished Lecturer, IEEE SPS (2008–2009) ADC Endowed Chair, University of Minnesota (2015) Students have won five best student paper awards at IEEE conferences (SPAWC 2012, ICASSP 2014, CAMSAP 2015, DSW 2019, CAMSAP 2023) He has advised numerous students and postdoctoral researchers, many of whom have gone on to publish influential work. His research has been supported by the National Science Foundation and other major funding agencies. He leads an active research lab at Thornton A012, University of Virginia, focusing on next-generation signal processing and machine learning algorithms.

Carlo Dallapiccolaمشاهده پروفایل

استاد

• Experimental Particle Physics
• High-Energy Physics
• Beyond the Standard Model Physics
• +۷ مورد دیگر

Carlo Dallapiccola is a Professor and Graduate Program Director in the Department of Physics at the University of Massachusetts Amherst, actively contributing to the ATLAS experiment at CERN's Large Hadron Collider. His research is central to advancing experimental particle physics through searches for new phenomena and precision measurements of Standard Model processes. University: University of Massachusetts Amherst School: College of Natural Sciences Department: Department of Physics Academic Rank: Professor Emails: carlod@physics.umass.edu, carlo.dallapiccola@cern.ch Location: Lederle Graduate Research Tower, Amherst, MA His research interests lie at the forefront of high-energy physics, focusing on experimental searches for physics beyond the Standard Model , particularly long-lived new particles that decay with displaced vertices, a signature of models like gauge-mediated supersymmetry breaking and dark sectors. He is deeply involved in the performance and upgrade of the ATLAS detector , including the muon spectrometer and the new inner tracker (ITk) for the High-Luminosity LHC. His work also encompasses Higgs boson physics , top quark studies , and precision electroweak measurements , all requiring advanced data analysis and detector calibration techniques. The recent articles highlight a strong trend toward precision Higgs physics , including searches for rare decays (H→μμ, H→ZZγ), Higgs self-coupling via pair production, and CP properties in tau decays. There is also a significant focus on exotic and beyond-Standard-Model signatures , such as leptoquarks and vector-like quarks, alongside the development of advanced data analysis methods using machine learning and neural simulation-based inference for parameter estimation and jet flavor tagging. His leadership is evident in collaborative efforts, with no individual scientific awards listed in the provided text. He advises graduate students as Graduate Program Director, fostering the next generation of physicists. His work is supported by major international collaborations and grants from agencies funding high-energy physics research, though specific grants are not detailed here. He is a key member of the ATLAS collaboration and has contributed to major detector upgrade projects like the New Small Wheel and the ITk. His research integrates data from the LHC with sophisticated computing frameworks, placing him at the heart of one of the largest scientific endeavors in history.

Gwen Marchandمشاهده پروفایل

استاد

• Educational Psychology
• Student Motivation and Engagement
• Mixed-Methods Research
• +۳ مورد دیگر

Gwen Marchand, Ph.D. is the Associate Vice President for Research and a Professor of Educational Psychology at the University of Nevada, Las Vegas (UNLV) . She formerly served as Associate Dean of Research and Sponsored Projects in the UNLV College of Education and as Director of the UNLV Center for Research, Evaluation, and Assessment . Education: Ph.D. in Systems Science: Psychology, Portland State University, 2008 – emphasis in human development, student motivation & engagement, and quantitative research methods Research Interests: Professor Marchand’s scholarship applies complexity theory and mixed-methods designs to study student motivation and engagement , classroom systems , student mobility , and collaborative team processes . Her interdisciplinary work emphasizes research-practice partnerships and systems-level understanding of educational phenomena. Current focal areas include: Motivational development of school-aged children Social and personal determinants of student engagement Teacher instructional supports for motivation in science classrooms Program evaluation and evidence-based educational innovation Publications & Scholarly Impact: Across 40+ peer-reviewed works since 2004, Marchand’s research spans complex dynamic systems , mixed-methods innovations , motivational theory , and science education reform . Recent outputs (2020-2024) converge on applying systems perspectives to classroom dynamics and translating motivational theory into scalable teacher professional-development programs. Professional Service & Leadership: Program Chair & Treasurer, Division 15 (Educational Psychology), American Psychological Association (APA) Secretary/Treasurer, Complexity Theories in Education SIG, American Educational Research Association (AERA) President, Scholarly Consortium for Innovative Psychology in Education (SCIPIE) Editorial Boards: Journal of Educational Psychology , Contemporary Educational Psychology Guest Co-Editor, special issues on complex systems ( Journal of Experimental Education ) and mixed-methods ( Contemporary Educational Psychology ) Teaching & Mentoring: Marchand regularly teaches graduate courses in advanced research methods , program evaluation , motivation theory , and quantitative analyses . Her interdisciplinary mentorship spans educational psychology, systems science, and STEM education research. Administrative Oversight: Office of Sponsored Programs Office of Clinical Trials Office of Research Integrity Interdisciplinary research development initiatives and strategic planning Funding: Her research has been supported by the National Science Foundation , the National Institute of General Medical Sciences , and numerous state and local agencies, evidencing broad recognition of her expertise and translational impact.

Elisha Kriegمشاهده پروفایل

استادیار

• DNA Nanotechnology
• Programmable Materials
• Biomaterials
• +۳ مورد دیگر

Dr. Elisha Krieg serves as Group Leader at the Leibniz Institute for Polymer Research Dresden and TUD Young Investigator at Dresden University of Technology, Germany. Her research pioneers programmable biomaterials using DNA nanotechnology for advanced biomedical applications, bridging synthetic polymer science with biological complexity. Her academic foundation includes: Ph.D. in Chemistry, Weizmann Institute of Science, Israel (2013) M.Sc. in Chemistry, Weizmann Institute of Science, Israel (2009) Vordiplom in Chemistry, University of Cologne, Germany (2006) Krieg's work centers on developing DNA-based nanomaterials that translate nanoscale programmability to macroscopic functional materials. Her group designs synthetic polymers functionalized with DNA modules to create reconfigurable platforms for diagnostics, tissue engineering, and nucleic acid purification. This approach leverages DNA's molecular precision to overcome limitations of conventional synthetic polymers, enabling dynamic biomaterials that respond to biological cues. Recent publications reveal a clear trajectory toward clinical translation, with 12 of 15 recent papers focusing on DNA-encoded hydrogels for cell culture matrices and nucleic acid diagnostics. The research spans fundamental supramolecular chemistry to applied biomedical engineering, emphasizing scalability and point-of-care compatibility. Key recognition includes: HFSP Postdoctoral Fellowship during Harvard tenure Krieg actively recruits MSc/PhD students through DIGS-BB and secures competitive funding including the TUD Young Investigator program. Her mentorship emphasizes interdisciplinary training in polymer chemistry, molecular biology, and nanomaterial characterization. Current grants support three core application areas: DNA/RNA purification for sequencing diagnostics, dynamic 3D cell culture matrices, and pathogen detection systems. The Krieg Group operates within the Max Bergmann Center of Biomaterials, utilizing advanced facilities for DNA nanotechnology, polymer synthesis, and nanomaterial characterization including cryo-EM and rheology.

Su Varmaمشاهده پروفایل

استاد مهمان

• Synthetic Heterocyclic Chemistry
• Materials Science
• Polymer Chemistry
• +۷ مورد دیگر

Prof Su Varma is a Visiting Professor at the School of Engineering and Materials Science, Queen Mary University of London. He holds a BSc (Hons), MSc, and PhD from the University of Bombay, and his academic affiliations include fellowships with the Royal Society of Chemistry and the Institute of Materials, Minerals and Mining. Academic Director, NSG Group R&D Incubator Member, EPSRC Strategic Advisory Network Core Panel Member, EPSRC Future Leaders Fellowship scheme Advisory Board roles at Swansea University SUNRISE, EPSRC-Oxford PV Prosperity Partnership, and IIT Kanpur His research focuses on synthetic heterocyclic chemistry , molecular conductors , and functional materials development for applications in glazing technology, electrochromics, and sol-gel chemistry. Su promotes academic-industry collaboration to address emerging technologies in materials science. He has published over 70 peer-reviewed papers and 75 patents, with expertise spanning fire-resistant polymers, colloidal silicates, and synthetic ceramics. Su actively engages with global research funding bodies to advance NSG Group's strategic partnerships. Fellow of the Royal Society of Chemistry (CChem FRSC) Fellow of the Institute of Materials, Minerals and Mining (FIMMM) As Academic Director of the NSG Group R&D Incubator, Su facilitates collaborations with universities and startups to develop next-generation materials for glass hybridization and functionality. He emphasizes the interplay of 'market-pull' and 'laboratory-push' strategies in commercializing academic research.

Yixuan Zouمشاهده پروفایل

مدرس

• Artificial Intelligence
• Wireless Communications
• Machine Learning
• +۷ مورد دیگر

Dr. Yixuan Zou is a Lecturer in Digital Signal Processing at the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL). She co-teaches QMUL's Joint Programme with Beijing University of Posts and Telecommunications (BUPT). B.Sc. in Mathematics M.Sc. from Imperial College London Ph.D. in Computer Science, QMUL (2022) Her research focuses on applying artificial intelligence to wireless communications, specifically non-orthogonal multiple access (NOMA), IRSs/RISs-aided systems, and resource allocation for 6G networks. She integrates machine learning, deep reinforcement learning, and meta-learning techniques to optimize network performance. Recent publications highlight advancements in secure IoT node identification, UAV-assisted RIS-NOMA networks, STAR-RIS beamforming, and wideband near-field communication optimization. She contributes to IEEE conferences as a Technical Program Committee member and session chair. Academic Fellow at Digital Environment Research Institute (DERI) Dr. Zou supervises PhD students researching next-generation multiple access, AI-driven near-field communication, and human action recognition, while also serving as a reviewer for top-tier journals like IEEE TWC and IoT-J.

• Haptic Communication
• Teleoperation Systems
• Digital Twin Technology
• +۳ مورد دیگر

Siwen Liu is a Scientific Staff member and Ph.D. candidate at the Chair of Media Technology (Lehrstuhl für Medientechnik) within the Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM). She joined TUM in December 2021 after completing her Master's degree in China. Her research focuses on Digital Twin based MMT control schemes, multi-dimensional parameters-based performance optimization of human-in-the-loop haptic teleoperation systems, and resource scheduling in teleoperation networks. Her work intersects robotics, haptics, and computer vision with applications in teleoperation systems. Dr. Liu's recent publications demonstrate her expertise in developing advanced teleoperation frameworks that leverage Digital Twin technology to overcome time-delay challenges. Her research shows a clear progression from foundational teleoperation concepts to sophisticated hybrid control strategies that incorporate human perception metrics. She actively supervises student theses, including research on DT-based Human-robot Teleoperation with Haptic Codecs Standard, indicating her role in mentoring the next generation of robotics researchers. Her work aligns with major research initiatives at TUM including the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and DFG: Teleoperation over 5G projects.

• Wireless Networks
• Reconfigurable Intelligent Surfaces (RIS)
• Resource Management
• +۳ مورد دیگر

Zhenyu Li is a doctoral student at the KTH Royal Institute of Technology in the Division of Communication Systems . He earned his bachelor's degree from Xidian University (2021) and a master's degree from KTH (2023). His research focuses on wireless network design assisted by reconfigurable intelligent surfaces (RISs) and resource management in RIS-enhanced networks to address requirements in diverse communication scenarios. B.Sc., Xidian University, Xi'an, China (2021) M.Sc., KTH Royal Institute of Technology, Stockholm, Sweden (2023) Research Interests : Advancing wireless communication through RIS technologies, optimizing mmWave network coverage in indoor dense spaces, and developing resource management strategies for next-generation networks. His work bridges theoretical modeling with practical applications in high-frequency communication systems. Publications : Recent contributions include theoretical and applied studies on mmWave channel modeling, self-sustainable metasurface-assisted systems, and mixed deployment strategies for RISs in indoor environments. These works emphasize performance optimization and energy efficiency. Contact : zhenyuli@kth.se

Monika Quinones Winderمشاهده پروفایل

استاد

• Marine Ecology
• Aquatic Food Webs
• Plankton Ecology
• +۳ مورد دیگر

Monika Quinones Winder is a Professor of Marine Ecology at the Department of Ecology, Environment and Plant Sciences, Stockholm University. She leads the Winder Lab, which focuses on understanding the drivers of food web interactions and how they respond to environmental change in aquatic ecosystems. Dr. Winder received her PhD in Natural Sciences from ETH Zurich, Switzerland, followed by postdoctoral research at the University of Washington, Seattle, and the University of California, Davis. Her academic journey has positioned her as a leading researcher in marine ecology and plankton dynamics. Her research program explores aquatic food web interactions and their responses to environmental changes, with particular emphasis on planktonic organisms in both freshwater and marine systems. She investigates how species composition and biotic interactions regulate populations, trophic energy transfer, and ecosystem function. Dr. Winder employs a multifaceted approach, combining descriptive field studies, long-term ecological monitoring, experimental research, and advanced molecular techniques such as selective metabarcoding to understand the impacts of external pressures on species and ecosystem dynamics. Analysis of Dr. Winder's recent publications reveals a strong focus on climate change impacts on plankton communities, particularly in the Baltic Sea ecosystem. Her work examines phenological shifts in plankton blooms, the effects of warming and acidification on plankton recruitment from sediments, and the role of microbial communities in zooplankton gut function. She also maintains active research programs on fish larvae ecology in coastal East Africa and invasive species impacts in the Bolivian Amazon. Dr. Winder has received recognition for her contributions to marine ecology, though specific awards are not detailed in the available information. Her research has been supported by various funding sources that enable her comprehensive investigations of aquatic ecosystems across different geographical regions. As a dedicated mentor, Dr. Winder supervises students and postdoctoral researchers in her lab, fostering the next generation of marine ecologists. Her collaborative approach is evident in the extensive list of co-authored publications spanning multiple international research teams. The Winder Lab maintains an active research agenda with several ongoing projects including studies on plankton species interaction networks, protist parasites in plankton food webs, larval fish production in coastal East Africa, sustainable management of water and soil resources in Bolivia, and plankton-fish interactions in Baltic Sea food webs.

• Power and Energy Systems
• Condition Monitoring
• Fault Diagnosis and Prognosis
• +۵ مورد دیگر

Dr Xiandong Ma is a Reader in Power and Energy Systems at Lancaster University's School of Engineering, where he has been a faculty member since December 2008. His research focuses on intelligent condition monitoring and fault diagnosis of power systems, with particular expertise in wind energy systems and smart grid technologies. His educational background includes: BEng in Electrical Engineering from Jiangsu University (1986) MSc in Power Systems and Automation from Nanjing Automation Research Institute (1989) PhD in Partial Discharge based High-voltage Plant Condition Monitoring from Glasgow Caledonian University (2002) Dr Ma's research spans intelligent condition monitoring and fault diagnosis/prognosis of wind power systems and electrical assets, condition-based operations and maintenance of power and energy systems, modeling, optimization, and control of smart/micro grids with renewable energy resources, power conversion and renewable energy integration, and associated machine learning and AI technologies and digital twin solutions. His work bridges theoretical advances with practical engineering applications in the renewable energy sector. His recent publications demonstrate a strong focus on quantum machine learning applications for wind turbine monitoring, electric vehicle-grid integration challenges, wave energy conversion systems, and nuclear fuel inspection technologies. The research shows a clear trajectory toward more sophisticated AI-driven solutions for energy systems, with increasing emphasis on multi-physics modeling and cross-domain applications. Dr Ma has received several prestigious recognitions: Chartered Engineer Fellow of the Institution of Engineering and Technology (FIET) Fellow of the Higher Education Academy (FHEA) Member of EPSRC Peer Review College KTP Fellowship awarded by University of Technology Sydney (2018) Ranked in the world's top 2% scientists by Stanford University He actively supervises numerous PhD students and postdoctoral researchers, with current projects including the Leverhulme Trust-funded "Self-Aware Power Networks: Autonomous Operation at Scale" and several EPSRC-funded initiatives. Dr Ma has secured significant research funding and collaborates extensively with industry partners to translate research into practical applications. Dr Ma leads research within Lancaster's Energy research group, focusing on the integration of advanced sensing, AI, and control techniques for next-generation power and energy systems. His team works closely with industrial partners including ALSTOM Power and various renewable energy companies to develop innovative solutions for real-world energy challenges.

Evangelos D. Karousisمشاهده پروفایل

مدرس

• mRNA translation
• Cell-free translation systems
• Viral RNA biology
• +۵ مورد دیگر

PD Dr. Evangelos D. Karousis is a Junior Group Leader and Lecturer at the Department of Chemistry, Biochemistry and Pharmacy at the University of Bern. He leads the Karousis Lab focused on mRNA translation mechanisms in health and disease, with particular emphasis on cell-free translation systems. His research is affiliated with the Multidisciplinary Center for Infectious Diseases (MCID) and the Swiss National Center of Competence in Research (NCCR) RNA & Disease. Dr. Karousis's research focuses on understanding the molecular mechanisms of mRNA translation, particularly how viruses like coronaviruses manipulate host translation machinery. His work combines biochemical approaches , cell-free translation systems , and structural biology to investigate viral pathogenesis and host defense mechanisms. Key areas include: Cell-free translation from diverse human cell types Coronavirus Nsp1 protein mechanisms mRNA degradation pathways Viral RNA structures and translation regulation Host-pathogen interactions at the molecular level His recent publications demonstrate a strong focus on developing innovative cell-free translation systems and understanding coronavirus mechanisms. The work shows a clear trajectory toward developing broad-spectrum antiviral strategies based on fundamental insights into viral manipulation of host translation. Scientific recognition includes: Lecturer of the Year award from the Biology department at University of Bern Dr. Karousis actively mentors the next generation of scientists through his research group and teaching responsibilities. His lab collaborates extensively with Prof. Dr. Oliver Mühlemann's group and participates in the NCCR RNA & Disease network, receiving support from Swiss National Science Foundation funding. The Karousis Lab maintains active engagement with the international RNA biology community through conferences, workshops (including the annual Kandersteg RNA meetings), and collaborative projects. The lab's "cell-free translation enthusiast" approach has positioned it at the forefront of developing innovative methods for studying translation mechanisms.