جستجوی استاد راهنمای دانشگاهی

• Materials Engineering
• Electrical and Electronic Engineering
• Nanotechnology
• +۷ مورد دیگر

Yongxiang Li is a Professor in the School of Engineering at RMIT University, Australia, specializing in advanced materials and nanotechnology. His research focuses on piezoelectric materials, 2D functional materials, and energy harvesting systems. He is actively involved in supervision of PhD and Master’s projects, including topics like flexible piezoelectric nanogenerators, 2D heterostructures, and low-temperature co-fired ceramic (LTCC) sensors. Research Interests: Materials Engineering, Electrical Engineering, Nanotechnology, Condensed Matter Physics, and Functional Ceramic Design. Key projects include developing lead-free piezoelectric materials, integrating sensors for lithium-ion batteries, and exploring gas sensors using liquid metal-derived oxides. Teaching Interests: Dielectric materials, ferroelectric systems, sensor technologies, and LTCC applications. His interdisciplinary work bridges materials science with optoelectronics and energy storage. Publications span over 400 outputs, emphasizing machine learning-driven materials discovery, defect engineering in 2D materials, and sensor innovation. He leads projects in collaboration with industry, focusing on practical applications of advanced ceramics and nanomaterials.

Rabi N. Mahapatraمشاهده پروفایل

استاد

• Embedded systems
• System-on-chip
• Reconfigurable architectures
• +۸ مورد دیگر

Rabi N. Mahapatra is a Professor in the Department of Computer Science & Engineering at Texas A&M University, within the College of Engineering. His research focuses on embedded systems, reconfigurable architectures, real-time systems, and semantic networks. He holds a Ph.D. in Computer Engineering from the Indian Institute of Technology (1992), an M.S. in Electrical Engineering (Sambalpur University, 1984), and a B.S. in Electronics & Communication (Sambalpur University, 1979). His research interests include Network-on-Chip (NoC), data analytic co-design, IoT protocols, and temperature-aware energy management. His work emphasizes hardware-software co-design for complex systems, with applications in many-core processors, semantic search engines, and real-time embedded systems. Key publications highlight contributions to collaborative filtering on many-core architectures, low-jitter clock distribution circuits, and energy-efficient scheduling. He has been recognized as an IEEE Computer Society Distinguished Visitor (2005–2007) and received the BOYS-CAST Indo-US Young Scientist Award. He leads the Codesign Embedded Systems group at Texas A&M, exploring cutting-edge topics such as photonics NoC, reservoir computing, and IoT security. His research bridges theory and practice, addressing challenges in scalable systems and embedded applications.

Abdullah Muzahidمشاهده پروفایل

دانشیار

• Computer Architecture
• Systems
• Artificial Intelligence
• +۵ مورد دیگر

Abdullah Muzahid is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University (since August 2024), previously serving as an Assistant Professor there since August 2018. Prior, he held an Assistant Professor role at the University of Texas at San Antonio (2012-2018). He earned his Ph.D. from the University of Illinois at Urbana-Champaign (2012), focusing on architectural support for debugging concurrency bugs under Prof. Josep Torrellas. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign (2012) M.S., Computer Science, University of Illinois at Urbana-Champaign (2009) B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology (2005) Research Interests: His work spans Computer Architecture , Systems , and Artificial Intelligence , with focus on multiprocessor architecture, parallel programming, debugging, and applying machine learning to system optimization. Recent projects include cache indexing via entropy estimation, DNN training acceleration, and hardware-software co-design for security. Awards: NSF CAREER Award (2017) Excellence in Research Award (UTSA, 2015 & 2017) W. J. Poppelbaum Award (UIUC, 2012) Intel Ph.D. Fellowship (2011) Grants & Advising: He leads NSF-funded projects on robust deep learning and stream processing systems. Advised 5 PhD graduates and currently mentors 4 PhD students. Served on program committees for ISCA, HPCA, MICRO, and as NSF panelist. Labs/Teams: Active in Texas A&M’s Computer Architecture group, collaborating on machine programming, hardware security, and AI-driven systems optimization.

• Artificial Intelligence
• Battery Technology
• Digitalization
• +۷ مورد دیگر

Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.

• Photonic Interconnects
• Distributed Machine Learning
• Cloud Computing
• +۳ مورد دیگر

Rachee Singh is an Assistant Professor of Computer Science at Cornell University, leading the sysphotonics research group. She concurrently serves as an Amazon Scholar within the SageMaker Hyperpod teams, specializing in large-scale machine learning infrastructure development for cloud environments. Her research focuses on photonic interconnect systems for server-scale, rack-scale, and long-haul communication networks, targeting performance optimization for distributed machine learning and planet-scale cloud workloads. Key specialties include optical network design, fault-tolerant WAN architectures, and energy-efficient datacenter interconnects, with strong emphasis on practical deployment in real-world systems. Her group bridges theoretical networking principles with applied AI infrastructure challenges. Recent publications demonstrate concentrated innovation in photonic network optimization for ML workloads, particularly in wavelength management, collective communication algorithms, and chip-to-chip photonic fabrics. This work spans optical physics, distributed systems, and machine learning, revealing a trajectory toward sustainable, high-performance AI infrastructure. Scientific recognition includes: Amazon Research Award (2023) Cisco Research Award Dr. Singh actively mentors graduate researchers including Jonathan Aimuyo, Byungsoo Oh, and Arjun Devraj, whose co-authored publications form the core of her group's output. Research funding is secured through competitive grants from the NSF (including a $1M award for chip-to-chip photonic fabrics), SRC/DARPA JUMP 2.0 program, Cisco, and Cornell's Atkinson Center for Sustainability. The sysphotonics group operates as Cornell's hub for photonic network systems research, developing programmable integrated photonics solutions and collaborating with Amazon on SageMaker Hyperpod for next-generation ML infrastructure.

• Power System Analysis
• Distribution System Optimization
• Electrical Load Management
• +۷ مورد دیگر

Gianfranco Chicco is a Full Professor at the Politecnico di Torino , Italy, within the Department of Energy (DENERG). He serves as Scientific Director of the Electrical Power Systems research group and the Turin unit of the ENSIEL Consortium. A Fellow of IEEE (since 2018), he has held editorial leadership roles as Editor-in-Chief of Sustainable Energy, Grids and Networks and Subject Editor of Energy , while chairing major conferences like IEEE ISGT Europe 2017 and UPEC 2020. Education : Laurea (cum laude) in Electrical Engineering (1987), Ph.D. in Electrical Engineering (1992), Doctor Honoris Causa (2017, Polytechnic University of Bucharest; 2018, Technical University 'Gheorghe Asachi' of Iasi). Research Interests : Focus on power transmission and distribution systems , distributed energy resources , and multi-energy smart grids , with applications in artificial intelligence , load management , and power quality . His work addresses technical, economic, and environmental aspects of distributed generation and smart grid sustainability . Publications Trends : Recent articles emphasize photovoltaic power optimization , dynamic grid modeling , and multi-energy system coordination , reflecting expertise in renewable integration , clustering algorithms , and adaptive control . Key subfields include voltage stability , load forecasting , and blockchain for energy trading . Awards : IEEE Fellow (2018-) Best Paper Awards at SEST (2018, 2020) Doctor Honoris Causa (2017, 2018) 'Giancarlo Vallauri' Degree Prize (1988) Advising and Grants : Supervises PhD students in power converters , renewable integration , and high-voltage measurement methodologies . Leads European projects like H2020 MIGRATE and OSMOSE, focusing on grid resilience , clustering-based network planning , and multi-energy sustainability .

Marios C. Angelidesمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Creative Computing
• +۵ مورد دیگر

Professor Marios C. Angelides is a full-time faculty member at Brunel University London , serving as Professor of Computing and Divisional Lead within the College of Engineering, Design and Physical Sciences . He leads the Creative Computing Research Group under the Institute of Digital Futures and contributes to the Digital Media department at Brunel Design School. BSc (First Class Honours) and PhD in Computing from the London School of Economics (LSE) Chartered Engineer (CEng) and Chartered Fellow of the British Computer Society (FBCS CITP) His research focuses on Creative Computing , specifically applying Machine Learning , Serious Gaming , and Cognitive Modeling to develop Smart IoT Applications . His work spans autonomous drone fleets for environmental monitoring, cybersecurity middleware for Android systems, wearable technology for lifestyle recommendations, and historical analysis of Alan Turing’s legacy in modern AI. Recent publications highlight trends in deploying Machine Learning for: IoT systems optimization Autonomous aerial/underwater vehicle coordination Deepfake detection using Turing’s Imitation Game Energy allocation in CubeSats via gaming mechanics Scientific recognition includes being Deputy Editor of The Computer Journal and runner-up for the 2016 Oxford University Press Wilkes Award . He has supervised PhD students in topics like Smart Android Middleware for Cybersecurity and Wearable Recommendation Systems , with active involvement in editorial boards and international conferences.

Gabriel Wainerمشاهده پروفایل

استاد

• Modelling and Simulation Methodologies
• Discrete Event Systems
• Real-Time Modelling
• +۷ مورد دیگر

Dr. Gabriel Wainer is a Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He leads the Advanced Real-Time Simulation Lab and specializes in modeling and simulation methodologies, particularly focusing on discrete event systems, real-time modeling, cellular automata, and DEVS formalism. Research Interests: Discrete event systems, DEVS formalism, cellular automata, real-time simulation, IoT applications, and parallel/distributed simulation Affiliation: Carleton University Recent publications highlight his work in advanced simulation frameworks, energy-efficient 5G systems using deep reinforcement learning, and pandemic modeling with cellular automata. His lab develops tools like PROMETHEUS and Devsmap for standardized DEVS model representation, while also exploring applications in wireless communication, building energy systems, and behavioral epidemiology.

Ronita Bardhanمشاهده پروفایل

دانشیار

• Heat-Health and Built Environment
• Decarbonisation of Built Environment
• Urban Microscale
• +۱۲ مورد دیگر

Dr. Ronita Bardhan is Associate Professor of Sustainable Built Environment at the University of Cambridge , where she leads the Cambridge Sustainable Design Group and serves as Director of Research & Deputy Head of the Department of Architecture . She holds courtesy roles at Cambridge Public Health and the Department of Computer Science and Technology , and is a Fellow at Selwyn College . Education: BArch, MCP, MA, PhD (Urban Engineering) Her research intersects built environment , climate change , and public health , focusing on data-driven strategies for precision prevention of health and energy burdens. She pioneers algorithmic approaches to identify decarbonisation potential in buildings and urban areas, with a particular emphasis on gender-inclusive climate adaptation in the Global South. The 15 most recent articles span topics such as urban cooling with tree canopies , heatwave impacts on social systems , and machine learning applications for building energy efficiency . Her work addresses climate justice , hybrid workspace design , and thermal comfort in low-income housing . Awards: Top 50 Finalist Women in Engineering, UK 2024 Exceptional Woman of Excellence, Women Economic Forum Felicitated by Ministry of Health, Maharashtra, India She advises World Bank and ADB on affordable housing and climate resilience, and chairs the Research Ethics Committee at the Department of Architecture. Her lab, the Sustainable Design Group , develops solutions for health and low-carbon potential in built environments.

Wolfgang Nejdlمشاهده پروفایل

استاد

• Web Science
• Information Retrieval
• Artificial Intelligence
• +۴ مورد دیگر

Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .

Janick Edingerمشاهده پروفایل

استاد

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +۷ مورد دیگر

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

Moritz Rossnerمشاهده پروفایل

استاد

• Molecular Neurobiology
• Behavioral Neurobiology
• Mouse Genetics
• +۷ مورد دیگر

Professor Moritz Rossner serves as Head of the Department of Molecular and Behavioral Neurobiology at the Department of Psychiatry and Psychotherapy, Faculty of Medicine, Ludwig-Maximilians-Universität München (LMU). His research integrates molecular and behavioral approaches to understand the neurobiological underpinnings of psychiatric disorders, particularly schizophrenia and bipolar disorder. Rossner's research interests focus on molecular neurobiology and behavioral analysis using mouse models. His laboratory employs advanced techniques including mouse genetics , behavioral phenotyping , biosensors , next-generation sequencing , and transcriptomics to investigate psychiatric risk genes and pathways. His work bridges cellular and molecular mechanisms with behavioral outcomes, particularly in schizophrenia and bipolar disorder research. Analysis of Rossner's 15 most recent publications (2025) reveals a strong focus on precision psychiatry , neuroimaging biomarkers , and genetic mechanisms underlying psychiatric disorders. His research increasingly incorporates multimodal approaches combining neuroimaging, genomics, and clinical phenotyping to develop biologically informed diagnostic and treatment frameworks. Key themes include blood-brain barrier dysfunction in schizophrenia, inflammatory contributions to symptom severity, and pathway-specific polygenic scores for treatment prediction. Rossner leads the Molecular & Behavioural Neurobiology working group at LMU's Department of Psychiatry and Psychotherapy, which includes specialized units like the Mouse Behavioral Unit. His research program appears well-funded through multiple collaborative projects focused on understanding the molecular basis of psychiatric disorders and developing novel therapeutic approaches.

Ralf Beckمشاهده پروفایل

استاد

• Control Engineering
• Automation Technology
• Regulation Systems
• +۵ مورد دیگر

Prof. Dr.-Ing. Ralf Beck serves as Professor for Control and Regulation Technology and Automation Technology at Hochschule Düsseldorf University of Applied Sciences within the Faculty of Electrical Engineering & Information Technology. His academic responsibilities span multiple degree programs including BEng Electrical Engineering, BEng Industrial Engineering, and MSc Electrical Engineering and Information Technology. His educational background includes Mechanical Engineering studies at TU Braunschweig (1998-2004), followed by doctoral research at RWTH Aachen's Institute of Control Engineering where he earned his Dr.-Ing. in 2010 with a dissertation on predictive energy management for hybrid vehicles. Prior to his current professorship, he held progressive roles at FEV Europe GmbH from 2009-2018, culminating as Senior Project Manager for Vehicle and Powertrain Electronics. Beck's research focuses on control engineering systems with particular emphasis on automation technology, regulation systems, and model-based development approaches. His work bridges theoretical control methodologies with practical automotive applications, especially in hybrid vehicle energy management, multi-robot systems, and intelligent air path control. The Modellfabrik Fab21 serves as his primary experimental platform for model-based development applications. His publication record since 2005 demonstrates consistent contributions to control engineering, particularly in hybrid vehicle systems, emission control optimization, and calibration methodologies. Recent work shows increasing focus on distributed robotics and intelligent transportation systems, reflecting evolving research directions while maintaining core expertise in control theory applications. As an educator, Beck teaches foundational and advanced courses including Electrical Engineering III, Control and Regulation Technology, Model-Based Development, Technical Mechanics, and Advanced Control Engineering at the Master's level. His teaching integrates theoretical concepts with practical laboratory applications through the university's Moodle platform, emphasizing hands-on implementation of control algorithms and system modeling techniques.

Muhannad S. Bakirمشاهده پروفایل

استاد

• Heterogeneous Integration
• Electrical and Photonic Interconnects
• Thermal Modeling for Electronics
• +۳ مورد دیگر

Muhannad S. Bakir is the Dan Fielder Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, and Director of the 3D Systems Packaging Research Center . His research focuses on heterogeneous integration , electrical/photonic interconnects , thermal modeling , and electronics for healthcare , with over 180 publications and 12 U.S. patents. Research areas include: Advanced cooling and power delivery for emerging systems Biosensor-CMOS integration 2.5D/3D IC packaging Polylithic integration technology Nanofabrication for microsystems Scientific accolades include: 2018 IEEE EPS Exceptional Technical Achievement Award 2013 Intel Early Career Faculty Honor Award 2012 DARPA Young Faculty Award 2011 IEEE CPMT Outstanding Young Engineer Award Best paper awards at IEEE ECTC, IITC, and CICC 2020 Georgia Tech Doctoral Thesis Advisor Award His lab explores integrated 3D systems with emphasis on co-design of thermal, power, and electrical networks for machine learning and healthcare applications.

• RF and Microwave Engineering
• Power Amplifiers
• Digital Transmitters
• +۴ مورد دیگر

Leonardus Cornelis Nicolaas de Vreede is a Professor at Delft University of Technology in the Faculty of Electrical Engineering, Mathematics and Computer Science. With over 237 research publications and extensive conference activities, he is a leading researcher in RF and microwave engineering with specialization in power amplifiers, digital transmitters, and mm-wave circuits for wireless communications applications. Dr. de Vreede's research focuses on the intersection of circuit design and signal processing for next-generation wireless systems: Advanced Power Amplifier Architectures including Doherty and Out-phasing techniques Energy-Efficient Digital Transmitters with high linearity and power efficiency mm-Wave Circuit Design for 5G/6G applications Machine Learning Applications for Digital Predistortion CMOS RF Integrated Circuit Implementation Wideband Signal Processing Techniques His recent publications demonstrate a clear research trajectory toward integrating machine learning with traditional RF circuit design to solve the efficiency-linearity tradeoff in wireless transmitters. This work is particularly relevant for current and future wireless infrastructure requiring high spectral efficiency across wide bandwidths while maintaining energy efficiency. Dr. de Vreede has received significant recognition for his contributions to the field: EuMC Microwave Prize (2024) for groundbreaking work on wideband Doherty amplifiers Recognition for innovative characterization techniques for high-power RF transistors (2015) As an active researcher and educator, Dr. de Vreede has supervised 16 students and regularly participates in major international conferences including serving on program committees for the IEEE MTT-S International Microwave Symposium. His work bridges theoretical advances with practical implementations for wireless infrastructure applications, with numerous patents and industry collaborations evident from his research portfolio.