جست‌وجوی استاد و پژوهشگر

Yingjie Zhangمشاهده پروفایل

استادیار

• Molecular Imaging
• Electrochemistry
• Renewable Energy
• +۵ مورد دیگر

Yingjie Zhang is an Assistant Professor in the Department of Materials Science and Engineering at the University of Illinois at Urbana-Champaign. He holds a Ph.D. in Applied Science and Technology from UC Berkeley (2015). His research focuses on molecular imaging, electrochemistry, and renewable energy systems, with interdisciplinary collaborations across materials science, physics, and engineering. Education: B.S. in Physics (Summa Cum Laude), Nankai University, 2010 Ph.D. in Applied Science and Technology, UC Berkeley, 2015 Research Interests: Molecular imaging and spectroscopy Electrochemical energy conversion and catalysis Interfacial solvation dynamics Nanomaterials for renewable energy Awards: National Science Foundation CAREER Award (2024) Sloan Research Fellowship (2025) Beckman Young Investigator Award (2021) Grants and Labs: NSF STC Center for Quantitative Cell Biology (2023) Beckman Institute affiliation (2023–present) Zhang Research Group (focusing on interfaces, molecular systems, and energy/health applications)

Jaijeet Roychowdhuryمشاهده پروفایل

استاد

• Machine Learning
• Cyber-Physical Systems
• Novel Computational Paradigms
• +۴ مورد دیگر

Jaijeet Roychowdhury is a Professor of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He specializes in machine learning, novel computational paradigms, and the analysis/simulation of cyber-physical, electronic, and biological systems. His research group pioneered self-sustaining oscillator-based Ising machines and contributed to oscillator phase macromodeling, nonlinear system reduction, and open-source prototyping platforms like MAPP. Education: B.Tech., Electrical Engineering, Indian Institute of Technology (IIT) Kanpur, 1987 M.S., Electrical Engineering & Computer Science, UC Berkeley, 1989 Ph.D., Electrical Engineering & Computer Science, UC Berkeley, 1993 Research Interests: Machine learning integration with physical systems Innovative computational hardware (e.g., oscillator-based Ising machines) Oscillator networks for unconventional computing Nonlinear dynamical systems analysis Analog circuit simulation and verification Awards & Recognition: 2019 Bell Labs Prize (with Tianshi Wang) 2009 IEEE Fellow 2019-2023 Bakar Foundation Awards Bell Labs' Extraordinary Achievement Award (1996) Advising & Industry: Notable advisee: Tianshi Wang (Bell Labs Prize co-winner) Cofounder of Berkeley Design Automation (acquired by Mentor Graphics) Leadership roles at AT&T Bell Labs, Bell Labs, and CeLight Inc. Lab & Tools: Leads the Roychowdhury Research Group, developing MAPP (Model and Algorithm Prototyping Platform) and PHLOGON phase-based logic frameworks.

Andrew Nereمشاهده پروفایل

استادیار

• Machine Learning
• Computer Architecture
• Embedded Systems
• +۳ مورد دیگر

Andrew Nere serves as Assistant Professor of Computer Science in the Math & Computer Science Department at Western Colorado University, teaching courses including Introduction to Web Design, Computer Science I, and Software Entrepreneurship since joining the faculty in Fall 2022. His industry background includes co-founding Thalchemy (2013), a startup specializing in embedded machine learning for wearable and environmental sensor applications, alongside prior internships at IBM and Qualcomm. His educational credentials feature: PhD in Electrical Engineering from University of Wisconsin-Madison (2013) MS in Electrical Engineering from University of Wisconsin-Madison (2010) B.S. in Computer Engineering from St. Cloud State University (2007) Nere's research centers on hardware-software co-design for efficient AI deployment, with dual focus on neuromorphic computing architectures and practical embedded systems implementation. He bridges theoretical neuroscience with engineering solutions, particularly for resource-constrained environments like fitness trackers and environmental sensors where computational efficiency is paramount. His work emphasizes translating academic research into real-world applications rather than pure theoretical exploration. Analysis of his 2010-2013 publications reveals consistent innovation in brain-inspired computing hardware, with recurring themes of GPU-accelerated neural simulations, specialized cache architectures for AI workloads, and energy-efficient neuromorphic designs. The research demonstrates strong interdisciplinary collaboration across computer architecture, neuroscience, and machine learning communities, frequently targeting hardware acceleration for cognitive computing tasks. Scientific recognition includes: Best Paper Nomination at IEEE International Symposium on Workload Characterization (2012) Best Paper in Track at International Parallel and Distributed Processing Symposium (2011) Nere brings substantial industry experience to academia, having served as university collaborator on the DARPA/IBM SyNAPSE project modeling brain functionality in computing systems. His startup Thalchemy exemplifies his commitment to applied research translation, while his current Software Entrepreneurship course provides students with practical business development frameworks for technology ventures. He actively leverages Gunnison Valley's natural environment for both recreation and potential research applications, noting particular interest in environmental sensing opportunities afforded by the region's wilderness proximity and diverse ecosystems.

• Artificial Intelligence
• Machine Learning
• Human-Computer Interaction
• +۱۶ مورد دیگر

Professor Damien Coyle is the Director of the Bath Institute for the Augmented Human at the University of Bath, where he leads cutting-edge research in artificial intelligence, machine learning, and human-computer interaction. His work is centered on brain-computer interfaces (BCI), neurotechnology, and cognitive computing, with applications in healthcare, rehabilitation, and intelligent systems. His research interests include Brain-Computer Interfaces , Spiking Neural Networks , Deep Learning , Emotion Recognition , Virtual and Extended Reality , and Neurofeedback Systems . He applies advanced AI techniques to decode neural signals, enabling real-time interaction between the brain and external devices. His interdisciplinary approach integrates neuroscience, computer science, and engineering. His recent publications from 2023–2024 reveal a strong focus on anomaly detection in industrial systems , EEG-fMRI data fusion for inner speech decoding , multi-level IT incident prediction using AI , and enhancing neurofeedback with immersive VR . These works demonstrate a trend toward multimodal data integration, real-time BCI applications, and AI-driven decision support in both clinical and technological domains. He has supervised numerous students and collaborators, many of whom are co-authors on his publications. His research is frequently published in top-tier IEEE and Springer conferences. He actively contributes to the advancement of neuroadaptive technologies and is involved in high-performance computing for BCI calibration. His leadership in organizing major conferences further underscores his influence in the field.

Ramon Canal Corretgerمشاهده پروفایل

استاد

• Microarchitecture
• Processor Design
• Memory Design
• +۱۵ مورد دیگر

Ramon Canal Corretger is a Full Professor in the Department of Computer Architecture at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC). He previously served as Vice Dean of Postgraduate Studies at FIB and leads the VirtuOS (Virtualization and Operating Systems) research group. His work bridges computer architecture, hardware security, and system-level reliability. Doctorate from UPC, co-supervised at the University of Wisconsin-Madison Sabbaticals at Harvard University (2006–2007) and the University of Cyprus (2019–2020) Active leadership in EU-funded projects such as Vitamin-V (Horizon Europe) His research focuses on microarchitecture, processor and memory design, reliability under variability, and security at the hardware-software interface. He explores low-power multicore architectures, virtualization optimizations, and secure RISC-V-based systems. His recent work integrates AI for intrusion detection and privacy-preserving federated learning in fog computing environments. The most recent publications demonstrate a strong trend toward security, reliability, and trustworthy computing , particularly in RISC-V ecosystems and cloud/edge infrastructures. There is increasing emphasis on hardware-software co-design , attack detection via performance monitoring , and energy-efficient secure accelerators using emerging technologies like neuromorphic and photonic computing. Scientific Awards: HiPEAC Paper Awards (2017, 2010) IEEE Senior Member (2016) Fulbright Award (2006) IBM Faculty Award (2000) Best Student Paper at HPCA-6 (2000) Multiple teaching excellence recognitions from UPC and AQU Catalunya First Prize in Epson Foundation Rosina Ribalta Award (2001) He has advised several PhD students including Manish Rana, Zoran Jaksic, and Shrikanth Ganapathy, many of whom received honors such as the Intel Doctoral Student Programme recognition. His research is supported by competitive grants from the Spanish government, EU Horizon programs, and industry collaborations. He is actively involved in the design of secure, reliable, and efficient computing systems for future cloud and embedded applications. He leads the VirtuOS research group, which focuses on virtualization, operating systems, and hardware-software interface optimization. The group contributes to open-source RISC-V initiatives and participates in large-scale European R&D projects targeting trustworthy computing infrastructures.

Jordi Sortمشاهده پروفایل

استاد

• Materials Science
• Magnetism
• Magneto-ionics
• +۵ مورد دیگر

Professor Jordi Sort is a leading academic at the Universitat Autònoma de Barcelona (UAB), Department of Physics, and an ICREA researcher. His primary roles include leading the Group of Smart Nanoengineered Materials, Nanomechanics, and Nanomagnetism (Gnm³), focusing on functional materials for advanced technological applications. He holds an ERC Advanced Grant (2022) for the REMINDS project and recently secured an ERC Proof of Concept Grant (2025) for SECURE-FLEXIMAG, which develops data security devices using magnetic materials. His research spans magneto-ionics, neuromorphic computing, and energy-efficient materials, leveraging interdisciplinary approaches. Education: PhD in Materials Science from UAB (2002, Extraordinary Award), postdoctoral training at SPINTEC (Grenoble), Argonne National Laboratory (USA), and Los Alamos National Laboratory. His academic journey includes long-term collaborations at high-magnetic-field facilities in Grenoble and beyond. Research interests include voltage-driven magnetism control, magnetic data security, biodegradable alloys for biomedical applications, and machine learning in material science. Notable achievements include over 380 publications (h-index 57), 7 patents, and coordination of the BeMAGIC network with 24 European partners. Awards include the FEMS Prize (2015), Duran Farell Award (2020), and ERC grants. SECURE-FLEXIMAG aims to revolutionize hardware security using flexible magneto-ionic devices, addressing energy efficiency and scalability challenges. His articles highlight breakthroughs in magneto-ionics, neuromorphic systems, lunar material analysis, and biodegradable metallic alloys. Grants & Awards: ERC Advanced Grant (2022), ERC Consolidator Grant (2014), FEMS Prize, 20+ patents. Labs/Teams: Gnm³ lab at UAB, collaborations with global institutions like Argonne and Los Alamos.

• Semiconductor Devices
• Nanoelectronics
• Quantum Transport
• +۳ مورد دیگر

Jesus A del Alamo is the Donner Professor and Mac Vicar Faculty Fellow in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), a position he has held since joining the faculty. His primary affiliation is with the School of Engineering. As part of his roles, he leads the Xtreme Transistors Group, a research team focused on advancing semiconductor and nanoelectronics technologies. His research interests span semiconductor devices, nanoelectronics, quantum transport phenomena, and ferroelectric materials. He has pioneered work in ultra-scaled transistors, III-V semiconductor integration, and memristive systems. Key areas include vertical nanowire tunneling transistors, ferroelectric field-effect transistors (FeFETs), and neuromorphic hardware leveraging ionic synapses. Dr. del Alamo has been recognized for his contributions with prestigious titles such as the Donner Professorship and Mac Vicar Fellowship, as well as the 2019 MRS Fellow distinction. His work intersects device physics with practical applications in high-frequency electronics, low-power computing, and energy-efficient memory systems. His research outputs reflect a strong focus on semiconductor scaling, with recent studies addressing challenges in nanoscale device fabrication and reliability. He has collaborated extensively on initiatives to reassert U.S. leadership in microelectronics through academic-industry partnerships, as highlighted in papers like "Reasserting U.S. Leadership in Microelectronics" (2022). As an educator and mentor, he has advised numerous graduate students and postdoctoral researchers in semiconductor device engineering. His contributions to the field are further reflected in his editorial roles, including serving as Editor-in-Chief of IEEE Electron Device Letters (EDL).

Tim Sherwoodمشاهده پروفایل

استاد

• Computer Architecture
• Computer Security
• Hardware Security
• +۷ مورد دیگر

Tim Sherwood is a Professor of Computer Science and Dean of the College of Creative Studies at UC Santa Barbara. He leads the UCSB Computer Architecture Lab (ArchLab) and co-founded Cycuity (formerly Tortuga Logic). His research focuses on secure and energy-efficient computing, superconducting architectures, and interdisciplinary projects like SEEDS. He holds a B.S. from UC Davis (1998) and M.S./Ph.D. from UC San Diego (2003) under Brad Calder. Awards include ACM Fellow (2023), IEEE Fellow (2022), and numerous best paper awards. Research interests span neuro-inspired temporal logic, hardware security, 3D integration, and accelerating machine learning. He emphasizes mentoring, having mentored over 20 students highlighted in awards. Teaching includes courses on computer organization, compiler design, and advanced architectures. Collaborations with industry and academia address challenges in trustworthy computing and future hardware paradigms. Notable achievements include the ASPLOS Most Influential Paper Award (2017) for SimPoint and leadership in securing hardware architectures. Current work explores superconducting computing, low-energy neural networks, and privacy-preserving systems.

Gerhard Jakob Kläuiمشاهده پروفایل

استاد

• Spintronics
• Magnetism
• Condensed Matter Physics
• +۷ مورد دیگر

Gerhard Jakob Kläui is an active faculty member at the Institute of Physics, University of Mainz, where he holds the academic rank of Außerplanmäßiger Professor (Extraordinary Professor). He is deeply involved in research and teaching activities, focusing on advanced topics in spintronics, magnetism, and quantum materials. His work is conducted within the broader framework of the Faculty of Physics, Mathematics and Computer Science. His research interests span Spintronics , Magnetism , Heusler compounds , Skyrmion dynamics , Spin-orbit torques , and Topological materials . These areas reflect a strong emphasis on next-generation magnetic technologies, including energy-efficient memory, neuromorphic computing, and quantum sensing. His group investigates both fundamental phenomena and device-level applications, particularly in antiferromagnetic and topological systems. The most recent publications (2024–2025) highlight a strong trend in ultrafast spin dynamics , magneto-ionic control , altermagnetism , and nonreciprocal transport . These works appear in high-impact journals such as Science Advances , Nature Communications , and Physical Review Applied , indicating significant contributions to the field. The research combines experimental techniques with theoretical insights, often involving collaborations across institutions. Email: jakob@uni-mainz.de Dr. Kläui has co-authored numerous papers with Prof. Mathias Kläui, suggesting a close collaborative relationship, possibly within the same research group. While no formal students or grants are listed, his extensive publication record implies advisory and leadership roles. His involvement in teaching is confirmed by the university's course listings. The research environment includes access to advanced facilities such as UHV deposition systems, scanning probe microscopy, and high-frequency magnetotransport setups, supporting a wide range of experimental investigations in nanomagnetism and spintronics.

Ismail Serdar Ozoguzمشاهده پروفایل

استاد

• Oscillator Engineering
• Current Mode Circuits
• Chaotic Oscillators
• +۷ مورد دیگر

Ismail Serdar Ozoguz is a Professor at Istanbul Technical University, Department of Electronics and Communication Engineering. With over 163 publications and 3020 citations, his work spans oscillator engineering, neural networks, and RF/wireless systems. Institution : Istanbul Technical University Department : Electronics and Communication Engineering Rank : Professor Research interests focus on oscillator engineering , current mode circuits , and chaotic oscillators . Recent work emphasizes neural network applications in filter optimization, antenna modeling, and stochastic computing. Scientific awards include: GEBIP Award (2002) Mustafa Parlar Foundation Research Incentive Award (2003) Research Incentive Award (2004) Projects highlight nonlinear optimization in GaN amplifiers, fractional-order neural networks, and spintronics for communication/memory systems. Collaborations span biomedical engineering, wireless networks, and AI-driven optimization.

• Defects in semiconductors
• Carrier transport in semiconductors
• Semiconductor junctions
• +۵ مورد دیگر

Francis Chi Chung Ling serves as an Associate Professor in the Department of Physics within the Faculty of Science at The University of Hong Kong (HKU). His academic journey began at HKU where he earned his B.Sc., M.Phil., and Ph.D. degrees. He maintains professional affiliations as C.Phys., M.IEEE, and F.Inst.P., and conducts research at Room 417, Chong Yuet Ming Physics Building. Office: CYP 417 Contact: 3917 5248 / 2559 9152 Email: ccling@hku.hk ORCID: https://orcid.org/0000-0003-4757-1065 Professor Ling's research spans multiple critical areas in semiconductor physics and materials science. His primary focus centers on defect characterization and engineering in semiconductors, particularly examining how defects influence electrical, optical, and magnetic properties. His work with positron annihilation spectroscopy provides atomic-scale insights into vacancy defects, while his investigations into deep level transient spectroscopy and carrier transport mechanisms advance fundamental understanding of semiconductor behavior. His laboratory maintains international collaboration with the positron beam line at Helmoltz Zentrum Dresden Rossendorf in Germany. Analysis of his 207 publications reveals a strong concentration on zinc oxide (ZnO) systems, silicon carbide (SiC), and other wide bandgap semiconductors. His recent work shows increasing focus on energy applications including photovoltaics, neuromorphic computing elements, and battery materials. The publications demonstrate consistent methodology combining experimental characterization with theoretical analysis, particularly emphasizing defect engineering approaches to modify material properties. Faculty Excellent Service Award: Faculty of Science, HKU (2008) Best Poster Award: ICMAT 2007, Singapore Faculty Knowledge Exchange Award 2024 for SiC Power Devices collaboration Professor Ling has supervised over 35 research postgraduate students across MPhil and PhD programs, with recent graduates focusing on SiC devices, ZnO-based materials, and 2D semiconductor structures. His grant portfolio includes significant funding as Principal Investigator on 17 projects totaling over HK$8 million, with recent major awards including HK$1.26 million for 'Bipolar Degradation in SiC Devices Suppressed by Proton Implantation' (2023) and HK$804,000 for 'Optimising the Performance of SiC Devices Through the Control of Atomic Scale Deep Level Defect' (2021). He leads the Material Physics Laboratory within HKU's Experimental Condensed Matter and Material Science Group, specializing in defect characterization and engineering of functional materials. The laboratory maintains specialized equipment for deep level transient spectroscopy, temperature-dependent Hall measurements, and luminescence spectroscopy, with international access to positron beam facilities in Germany.

Yiyang Liمشاهده پروفایل

استادیار

• Energy Storage
• Neuromorphic Computing
• Electrochemical Materials
• +۳ مورد دیگر

Yiyang Li is an Assistant Professor in the Department of Materials Science and Engineering at the University of Michigan, College of Engineering, specializing in electrochemical materials for energy storage and brain-inspired computing systems. Education: BS in Electrical and Computer Engineering from Olin College of Engineering (2011) PhD in Materials Science and Engineering from Stanford University (2016) His research centers on leveraging high-density point defects (>10 22 cm -3 ) in ionic materials for dynamic electrochemical doping. The first thrust examines individual Li-ion battery particles to uncover fundamental electrochemical properties, while the second develops analogue non-volatile memory elements for neuromorphic computing—potentially reducing machine learning energy consumption by two orders of magnitude through parallelized matrix operations. His work demonstrates significant trends in utilizing lithium, proton, and oxygen ions within host materials to enable high-density energy and information storage via redox processes. Awards: Truman Fellow at Sandia National Labs (2017-2020) Dr. Li actively recruits graduate students and postdocs for his newly formed research group starting September 2020, with current teaching responsibilities including MSE550: Fundamentals of Materials Science and Engineering. Prospective students must apply through UM departments before contacting him. The Li Group (http://ligroup.engin.umich.edu) operates from 2118 H.H. Dow and focuses on electrochemical redox systems for next-generation energy and computing applications.

Ulrich Rückertمشاهده پروفایل

استاد

• Neuromorphic Computing
• Embedded Systems
• Machine Learning
• +۹ مورد دیگر

Prof. Dr.-Ing. Ulrich Rückert is a Professor at the Faculty of Engineering of the University of Bielefeld , where he leads the Cognitronics & Sensor Technology Group and participates in CITEC (Center for Cognitive Interaction Technology). He serves as Vice Rector for Digitalization and Data Infrastructure , driving university-level digital transformation initiatives. Research Focus : Neuromorphic computing, spiking neural networks (SNNs), embedded systems, robotics, UWB localization, and reconfigurable hardware. Projects : Leading federal and EU-funded initiatives like eProcessor (RISC-V multi-core systems), VEDLIoT (efficient deep learning in IoT), and Al4DG (AI in distribution grid control). Teaching & Leadership : Academic advisor for the Master in Biomechatronics , chairs examination boards, and leads the Library Commission . His work integrates neuromorphic hardware with edge computing and real-time systems , supported by grants from the European Union and German Federal Government . Recent publications analyze FPGA-based SNNs , UWB localization , and resource-efficient embedded architectures . Scientific Contributions : Over 200 publications in robotics, neural networks, and hardware-software co-design. Notable collaborations with institutions in Germany, Switzerland, and Italy.

İsmail AKTÜRKمشاهده پروفایل

استادیار

• Computer Architecture
• Brain-Inspired Computing
• Energy-Efficiency
• +۳ مورد دیگر

Dr. İsmail AKTÜRK serves as an Assistant Professor in the Computer Science Department within Ozyegin University's Faculty of Engineering. Previously, he held an Assistant Professor position at the University of Missouri - Columbia's Department of Electrical Engineering and Computer Science for four years. His academic foundation includes a Ph.D. in Electrical and Computer Engineering from the University of Minnesota, Twin Cities. Education: Ph.D. in Electrical and Computer Engineering, University of Minnesota, Twin Cities, 2017 M.S. in Computer Engineering, Bilkent University, 2013 M.S. in Electrical Engineering, Louisiana State University, 2009 B.S. in Computer Engineering, Doğuş University, 2007 Dr. AKTÜRK's research centers on Computer Architecture with specialized expertise in brain-inspired computing and neuromorphic systems . He pioneers unconventional computing paradigms that integrate memory and processing units to eliminate energy-intensive data transfers inherent in traditional von Neumann architectures. His work employs hardware/software co-design methodologies to enhance energy efficiency for data-intensive applications like deep learning through spatial and temporal approximations. He directs the Computer Architecture and System Technologies Lab, where his research group develops application-specific systems exploiting novel devices and algorithmic advancements. Dr. AKTÜRK actively mentors graduate students in creating energy-efficient computing solutions for emerging computational challenges.

• Approximate computing
• Bayesian networks
• Cybersecurity
• +۷ مورد دیگر

Alessandro Savino is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di TORINO. He serves as an academic advisor for Bachelor’s and Master’s degree programs in Computer Engineering (Ingegneria Informatica) and contributes to PhD programs in Artificial Intelligence and Computer Engineering. Research Interests: Approximate computing, Cybersecurity (including automotive systems), Dependability, Parallel computing, Reliability analysis, and Neuromorphic architectures. Key Projects: Leads RESCHIP4EU (2024-2028), NEUROPULS (2023-2027), and commercial contracts focused on real-time OS validation and avionics design. Publications: Recent work spans hardware security (e.g., VeriSide for leakage assessment), spiking neural networks (SpikeExplorer, SpikingJET), and automotive cybersecurity (CARACAS, CAN-MM). Teaching: Instructs courses on Parallel and Distributed Computing, Hardware & Wireless Security, and System Programming across Politecnico di TORINO and Scuola IMT Alti Studi - LUCCA. Research Group: Leads the SMILIES group, focusing on resilient computer architectures and life sciences.