جست‌وجوی استاد و پژوهشگر

• Signal Processing
• Wireless Communications
• Underwater Acoustic Communications
• +۷ مورد دیگر

Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.

Jason D. Bakosمشاهده پروفایل

استاد

• Computer Architecture
• Reconfigurable Computing
• High-Performance Computing
• +۴ مورد دیگر

Dr. Jason D. Bakos is a Professor in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research focuses on high-performance domain-specific architectures, including reconfigurable computing, embedded systems, and machine learning acceleration. He has held academic positions since 2005, progressing from Assistant to Associate Professor before becoming a full Professor in 2017. Education : Ph.D., Computer Science, University of Pittsburgh (2005) B.S., Computer Science, Youngstown State University (1999) Research Interests : Dr. Bakos specializes in computer architecture at multiple levels (circuit, micro-architectural, and system) with a focus on VLSI design, reconfigurable computing, high-performance computing, and applications in embedded systems. His recent work includes FPGA acceleration of machine learning algorithms, structural health monitoring systems, and real-time signal processing. Awards : 2018 Teaching Award in Computer Science and Engineering 2009 NSF CAREER Award Multiple design competition awards for innovative chip and circuit designs Grants & Funding : He leads and co-leads projects funded by NSF, Savannah River National Laboratory, and industry partners like Texas Instruments. Recent grants focus on edge computing for real-time machine learning, FPGA-based accelerators, and corrosion analysis of nuclear materials. Labs & Teams : His research group collaborates on projects involving embedded systems, FPGA design, and interdisciplinary applications in structural engineering and bioinformatics. He advises a dynamic team of graduate students and post-doctoral researchers.

Sujan Kumar Royمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Sujan Kumar Roy is an Assistant Teaching Professor in the Department of Computer Science at Michigan Technological University. He holds a Ph.D. in Machine Learning with Computer Engineering and Signal Processing from Griffith University, Australia, and has earned multiple academic distinctions, including the 'Award of Excellence in the Research Thesis' and consideration for the 'Chancellor's Medal for Excellence in Ph.D. Thesis 2021.' Dr. Roy's teaching focuses on Computational Intelligence, Foundations of Data Science, Machine Learning, Data Mining, and Introduction to Data Science. His research explores applications of AI, ML, and Data Science in Cybersecurity, Medical Image Analysis, Healthcare Systems, and Speech Enhancement. He has contributed extensively to speech enhancement techniques, integrating Kalman filters with machine learning and deep learning approaches. Recent research trends in his publications emphasize the development of robust algorithms for speech enhancement in noisy environments, fusion datasets for hate speech detection, and adaptive filtering methods. His work bridges signal processing and AI, aiming to improve real-time system performance and noise robustness. Awards: Award of Excellence in the Research Thesis Consideration for Chancellor's Medal for Excellence in Ph.D. Thesis 2021 In teaching, Dr. Roy emphasizes foundational concepts and their practical applications. His grants and collaborations focus on advancing AI-driven solutions for healthcare and cybersecurity challenges. He is affiliated with the Department of Computer Science at Michigan Tech, contributing to both academic and research missions.

Jason Trelewiczمشاهده پروفایل

استاد

• Materials Science
• Nuclear Engineering
• Advanced Materials for Extreme Environments
• +۴ مورد دیگر

Jason Trelewicz is a Professor at Stony Brook University’s Department of Chemical & Molecular Engineering and holds joint faculty status at Oak Ridge National Laboratory. His research focuses on interface-engineered materials for extreme environments, leveraging advanced processing, characterization tools, and multiscale modeling. He received his Ph.D. in Materials Science from MIT (2008) and previously served as Research Director at MesoScribe Technologies. His work emphasizes fusion materials, nanocrystalline alloys, additive manufacturing, and radiation effects. Awards include the DOE Early Career Award (2017), NSF CAREER Award (2016), and multiple best paper awards (2022). His lab, the Engineered Microstructures and Radiation Effects Laboratory, explores topics like ceramic composite moderators and plasma-facing materials. Education: Ph.D., Materials Science & Engineering, MIT (2008) Affiliations: Oak Ridge National Laboratory (Joint Faculty) Key research areas include thermal-mechanical evaluation of fusion reactor components, alloy design for additive manufacturing, and radiation tolerance of nanocrystalline materials. He has pioneered studies on helium bubble dynamics in tungsten and stability of doped nanocrystalline alloys. Awards: DOE Early Career Award, NSF CAREER Award, 2022 Best Paper Awards in Nuclear Materials and Asian Ceramics. Grants/Projects: Supported by DOE, NSF, and collaborative initiatives with Japan (FRONTIER). His group investigates corrosion behavior in 3D-printed steels and develops novel composite moderators for high-temperature reactors. Ongoing work includes multiscale modeling for fusion materials and in-situ TEM studies of irradiation effects.

Justin Gottschlichمشاهده پروفایل

عضو هیئت علمی

• Machine Programming
• Artificial Intelligence
• Software Engineering
• +۳ مورد دیگر

Justin Gottschlich is an Adjunct Lecturer in the Computer Science Department at Stanford University, where he teaches the graduate course Machine Programming (CS 329M) . He also serves as Founder, CEO, and Chief Scientist of Merly Inc., a startup focused on machine programming systems to improve software development efficiency and quality. Previously, he led the Machine Programming Research group at Intel Labs, pioneering advancements in automating software development through a fusion of machine learning, programming languages, and systems research. His academic roles include prior positions as Adjunct Professor at University of Colorado-Boulder and Adjunct Assistant Professor at University of Pennsylvania. He has advised numerous graduate students across institutions, contributing to their research in machine programming and related fields. Gottschlich has authored dozens of research papers and holds multiple patents, with his work highlighted by prominent outlets like the Wall Street Journal and Communications of the ACM. He actively contributes to academic committees, including serving as Steering Committee Chair for the ACM SIGPLAN Machine Programming Symposium (MAPS). His research interests span machine programming, autonomous software development, formal methods, and the integration of AI into software engineering practices. Education: PhD in Computer Science from University of Colorado-Boulder Keynote Engagements: LADSIOS (2021), MIT DSAIL (2021), Penn PRECISE (2019) Labs/Teams: Intel Labs Machine Programming Research Group, Merly's R&D Team Grants & Funding: Extensive industry and academic research funding through Intel Labs and Merly

• Optical Networking
• High-Speed Networks
• Data Center Technologies
• +۶ مورد دیگر

Emmanouel (Manos) Varvarigos is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), where he leads the High Speed Communication Networks Laboratory. He holds a Diploma from NTUA (1988) and an M.S./Ph.D. from MIT (1990/1992). Prior roles include Professorships at UC Santa Barbara (1992-1998) and Delft University (1998-1999), and leadership at the University of Patras (1999-2015). He has coordinated over 30 EU research projects, including H2020 initiatives like ORCHESTRA and FLEXGRID. His research focuses on optical networking, cloud computing, smart energy grids, and high-speed network protocols. He has published over 450 papers and serves on numerous conference committees. Awards include the NSF Research Initiation Award. His lab employs 5 postdocs and 10+ PhD students, addressing challenges in networking, data centers, and grid computing. Education: Ph.D., Electrical Engineering and Computer Science, MIT, 1992 M.S., Electrical Engineering and Computer Science, MIT, 1990 Diploma in Electrical and Computer Engineering, NTUA, 1988 Research Interests: Optical networking, high-speed network protocols, data center architectures, cloud computing, smart energy grids, wireless networks, and distributed systems. Grants & Projects: Coordinated 7 EU projects (e.g., FLEXGRID, ORCHESTRA) and participated in 35+ others. National projects include roles as Scientific Director of the Greek School Network and CTI’s Network Technologies Division. Labs & Teams: Directs the High Speed Communication Networks Lab (HSCNL), collaborating with global institutions on optical networks, edge cloud, and smart grids. The lab’s work includes EU-funded projects on 5G, data centers, and renewable energy integration.

Juan Alonsoمشاهده پروفایل

استاد

• Aerospace System Design
• Computational Fluid Dynamics
• Multi-Disciplinary Optimization
• +۷ مورد دیگر

Prof. Juan Alonso is the Vance D. and Arlene C. Coffman Professor and James & Anna Marie Spilker Chair in the Department of Aeronautics & Astronautics at Stanford University. He directs the Aerospace Design Laboratory (ADL), focusing on high-fidelity computational methods for aerospace system design. His expertise spans transonic/supersonic/hypersonic aircraft, rotorcraft, and launch vehicles. Alumni include record-holding teams for human-powered watercraft and lightweight unmanned aerial vehicles. Education: PhD (1997) from Princeton University in Mechanical & Aerospace Engineering; M.A. (1993) Princeton; B.S. (1991) MIT Aeronautics/Astronautics. Research emphasizes multi-disciplinary optimization, numerical methods, and parallel computing applied to advanced aircraft design, sustainable aviation, and UAS systems. Notable contributions include computational design frameworks like SU2 and SUAVE, and initiatives in curriculum development for engineering education. Recent work focuses on: GPU-accelerated CFD solvers, multi-fidelity surrogate models (e.g., VortexNet), contrail simulation frameworks, and battery degradation modeling for electric aircraft. Active in urban air mobility and high-fidelity trajectory optimization for hypersonic systems. Labs/Teams: Aerospace Design Laboratory (ADL) leading open-source computational tools development. Involved in NASA-funded projects and industry partnerships for advanced propulsion systems.

Gianluca Piazzaمشاهده پروفایل

استاد

• MEMS/NEMS
• Nanotechnology
• Piezoelectric Devices
• +۷ مورد دیگر

Gianluca Piazza is the STMicroelectronics Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Mechanical Engineering. He directs the John and Claire Bertucci Nanotechnology Laboratory (CMU Nanofab). Previously, he was the Wilf Family Term Assistant Professor at the University of Pennsylvania. His research focuses on piezoelectric micro/nano electromechanical systems (M/NEMS) for RF communication, optomechanics, chemical/biological sensing, and mechanical computing. Key projects include nanorelays for low-power computing, ultrasound-based wireless powering, and piezoelectric MEMS for energy harvesting. Education: PhD (2005) in Electrical Engineering from UC Berkeley; MS (2001) from University of Texas at Austin and Politecnico di Milano (Italy). Research Interests: M/NEMS design, micro/nano fabrication, piezoelectric materials, mechanical switches, and energy-efficient electronics. His work bridges fundamental science and applied engineering, with patents in micromechanical resonators and awards including the IBM Young Faculty Award (2006) and multiple IEEE Best Paper Awards. Grants & Collaborations: NSF LEAP-HI grant ($2M) for nanorelay development (2020); CMU Kavčić-Moura Endowment funding. Collaborates with Maarten de Boer (Mechanical Engineering) and institutions like the University of Pennsylvania and City University of Hong Kong. Labs & Teams: Leads the Piazza Micro and Nano Systems Laboratory, focusing on NEMS/MEMS innovation. Active in CMU’s Center for Silicon System Implementation and Engineering Research Accelerator.

Joanna Austinمشاهده پروفایل

استاد

• Hypervelocity Flight
• Planetary Entry
• Supersonic Combustion and Detonation
• +۵ مورد دیگر

Joanna Austin is a Professor of Aerospace and serves as the Graduate Option Representative for Aeronautics and Space Engineering, as well as the Undergraduate Option Representative for Aerospace at the California Institute of Technology (Caltech). She leads the Caltech Hypersonics Group, which operates facilities like the T5 Reflected Shock Tunnel and the Hypervelocity Expansion Tube (HET). Her research focuses on reactive, compressible flows in applications such as hypervelocity flight, planetary entry, supersonic combustion, bubble dynamics, and explosive geological events. Key projects include studying shock-boundary layer interactions, Martian atmospheric entry aerothermodynamics, and high-speed fluid-structure interactions. She advises four Ph.D. students and collaborates with a team including staff members like Liza Bradulina and research assistants such as Noel Esparza-Duran. Her work bridges experimental fluid dynamics with geophysical phenomena, leveraging advanced diagnostics like Focused Laser Differential Interferometry (FLDI) and laser spectroscopy. The group’s facilities enable studies of high-enthalpy flows and hypersonic aerodynamics critical for aerospace and planetary exploration. Research highlights include investigations into CO₂ Martian entry conditions, boundary layer transition mechanisms, and fluid-structure coupling in high-speed flows. The Hypersonics Group’s experimental setups replicate extreme environments to advance predictive models for aerospace systems. Her contributions span both fundamental fluid mechanics and applied engineering challenges, with a focus on real-gas effects and shock dynamics. Collaborations with institutions like NASA and academic partners further her interdisciplinary impact.

H. Jane Baeمشاهده پروفایل

استادیار

• Turbulence Modeling
• Computational Fluid Dynamics
• Fluid Mechanics
• +۳ مورد دیگر

H. Jane Bae is an Assistant Professor of Aerospace at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. Her research focuses on turbulence modeling, particularly developing high-fidelity computational methods to simulate high-Reynolds-number flows for applications in aircraft design, wind farms, and atmospheric predictions. She integrates machine learning, information theory, and numerical techniques to enhance turbulence modeling efficiency. Education: B.S. in Aerospace Engineering from Caltech (2011), Ph.D. in Mechanical Engineering from Stanford University (2018). She joined Caltech in 2021. Research interests include near-wall turbulence dynamics, resolvent analysis, sparse identification of nonlinear dynamics, and reinforcement learning for wall models in LES. Her work addresses computational cost reduction and model accuracy in complex flow simulations. Awards: 2023 Outstanding Referee Award from Physical Review. Teaching includes courses on fluid mechanics (Ae/APh/CE/ME 101 abc) and turbulence (Ae 239 ab). Her lab combines turbulence theory, high-performance computing, and data-driven methods to study unsteady flows over complex surfaces. Notable contributions include machine learning-based wall models and resolvent analysis frameworks for non-stationary flows.

Andreas Peter Burgمشاهده پروفایل

دانشیار

• Circuits and systems for telecommunications
• Silicon implementation of communication technologies
• Communication algorithms optimization
• +۵ مورد دیگر

Andreas Peter Burg is a Tenured Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Telecommunications Circuits Laboratory (TCL) within the School of Engineering. He holds multiple academic and administrative roles at EPFL including Associate Professor in Teaching (SEL, EDMI, EDEE), Director of SEL Management, and Member of the Doctoral Program Committee for Electrical Engineering. Dr. Burg received his Dipl.-Ing. degree in 2000 and Dr. sc. techn. degree in 2006 from ETH Zurich. His academic career includes positions as SNF Assistant Professor at ETH Zurich (2009-2011) before joining EPFL in January 2011 as a Tenure Track Assistant Professor, where he was promoted to Tenured Associate Professor in June 2018. His research focuses on circuits and systems for telecommunications , with particular expertise in silicon implementation of communication technologies, communication algorithms optimization for hardware, low-power VLSI signal processing, and digital integrated circuits. His work bridges theoretical communication concepts with practical circuit implementations, addressing challenges in wireless and wired communication systems. His recent publications (2024-2025) demonstrate a strong focus on next-generation communication technologies including 6G systems, advanced error correction coding, wireless sensing applications, and ultra-low power circuit design. These works span multiple subfields from LDPC and polar code decoding to RF signal processing and machine learning applications in wireless systems. Willi Studer Award (2000) ETH Medal for diploma thesis (2000) ETH Medal for Ph.D. dissertation (2006) Swiss National Science Foundation Assistant Professorship grant (2008) Dr. Burg has been involved in the development of more than 25 ASICs throughout his career and co-founded Celestrius, an ETH spinoff in MIMO wireless communication. His laboratory work focuses on practical implementations of communication algorithms with emphasis on power efficiency and hardware optimization. Current research directions include 6G technologies, wireless sensing applications, and novel error correction techniques for next-generation communication systems.

Stefano Markidisمشاهده پروفایل

استاد

• High-Performance Computing
• Quantum Computing
• Computational Fluid Dynamics
• +۵ مورد دیگر

Stefano Markidis is a Professor of Computer Science at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Digital Futures Faculty. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and an MS from Politecnico di Torino. His research focuses on high-performance computing systems, including supercomputers and quantum computers, with expertise in plasma simulations, quantum algorithms, and scalable computational frameworks. Markidis leads the development of the Neko framework for high-fidelity computational fluid dynamics and the iPIC3D particle-in-cell code for plasma physics. He teaches courses such as Quantum Computing for Computer Scientists, High-Performance Computing, and Applied GPU Programming. His work addresses exascale computing challenges, including optimizing algorithms for GPUs, quantum systems, and distributed architectures. Key research interests include: Parallel Programming Models and HPC Frameworks Quantum Computing Applications in Scientific Simulations Physics-Informed Machine Learning Exascale System Optimization Turbulence Modeling and Plasma Dynamics His publications span over 100 articles in journals like Journal of Computational Physics and Scientific Reports , focusing on topics such as scalable CFD, quantum neural networks, and plasma simulation techniques. He has advised numerous students in these areas. Markidis collaborates with institutions like Los Alamos National Laboratory and RISE Research Institutes of Sweden through the Digital Futures initiative, aiming to solve societal challenges via digital technologies.

Ira Weissمشاهده پروفایل

استاد

• Global/International Management
• Corporate Strategy
• Higher Education Management
• +۳ مورد دیگر

Dr. Ira Weiss is a Professor of Strategic Management at North Carolina State University, affiliated with the Department of Management Innovation & Entrepreneurship. His expertise spans Global/International Management, Corporate Strategy, Higher Education Management, and Business Accreditation. He holds a Ph.D. in Management from UCLA (1976). His research focuses on strategic frameworks, organizational systems, and accreditation processes, as evidenced by his thought leadership in AACSB articles advising institutions on accreditation strategies. His academic contributions include over four decades of publications on IT management, risk mitigation, and professional certification. Notable works address end-user computing strategies, cost control in software development, and auditability of systems. Though no specific grants or advising roles are detailed, his influence extends through academic discourse and institutional best practices. He remains active in North Carolina State’s initiatives related to management innovation and entrepreneurship.

Mehmet Öztürkمشاهده پروفایل

استاد

• Energy Harvesting
• Thermoelectrics
• Nanoelectronics
• +۵ مورد دیگر

Dr. Mehmet Öztürk is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on nanoelectronics, energy harvesting, and advanced materials for flexible electronics, particularly thermoelectric devices for body heat energy conversion. He holds a Ph.D. in Electrical Engineering from NC State, a Master’s from Michigan Technological University, and a Bachelor’s from Bogazici University. Dr. Öztürk’s research interests span Physical Electronics, Photonics, and Magnetics, with emphasis on novel materials and processes for thermoelectric generators and wearable technologies. His work includes developing flexible, high-efficiency thermoelectric systems using liquid metal interconnects and graphene-doped elastomers. Recent projects involve aerosol spray deposition techniques for stretchable electronics and optimizing materials for body heat harvesting systems. Key scientific contributions include analytical models for thermoelectric energy extraction, high thermal conductivity composites, and microporous CNT nanocomposites. His work bridges fundamental material science with applied engineering solutions for energy-efficient wearable devices. Awards: 2020 William F. Lane Outstanding Teaching Award 2009 IEEE Fellow for contributions to Si/SiGe epitaxy 2006 IEEE Undergraduate Teaching Award Lab Affiliations: Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST)

Diego Donzisمشاهده پروفایل

استاد

• Fluid Dynamics
• Turbulence
• Turbulent Mixing
• +۳ مورد دیگر

Diego Donzis is a Professor in the Department of Aerospace Engineering at Texas A&M University, affiliated with the College of Engineering. He holds the Presidential Impact Fellow title. His work focuses on high-performance computing for fluid dynamics, particularly compressible turbulence, turbulent mixing, and shock-turbulence interactions. Donzis earned his Ph.D. and M.S. in Aerospace Engineering from the Georgia Institute of Technology. Research interests include large-scale simulations of turbulent flows, thermal boundary condition effects on turbulence, and the development of advanced numerical methods like Selected-Eddy Simulations (SES) for extreme-scale computing. His studies explore universality in turbulence scaling, energy spectra dynamics, and the interplay between compressibility and fluid mixing. Publications emphasize turbulence decay laws, shock-turbulence interactions, and the role of thermal non-equilibrium in turbulent flows. Notable contributions include advancing asynchronous algorithms for exascale CFD and analyzing density gradient statistics in compressible turbulence. Awards include the Presidential Impact Fellow distinction. Donzis collaborates on grants such as the Frontera Travel Grant for compressible turbulence research. His work bridges computational methods with fundamental fluid dynamics, addressing challenges in both numerical accuracy and physical modeling.