جستجوی استاد راهنمای دانشگاهی

Sungho Kimمشاهده پروفایل

استادیار

• Integrated Circuits
• Neuromorphic Computing
• High-Performance Computing Hardware
• +۳ مورد دیگر

Sungho Kim is an Assistant Professor at the Department of Electrical, Computer and Biomedical Engineering in the College of Engineering at the University of Rhode Island (URI). He serves as Director of the Integrated Circuit Design Laboratory (ICDL), pioneering research on integrated circuits (ICs) for harsh environments, neuromorphic computing, and readout electronics for superconducting photon detectors. His career spans roles at NASA Jet Propulsion Laboratory (JPL), Samsung Advanced Institute of Technology (SAIT), and RIKEN Quantitative Biology Center. Ph.D., Electrical Engineering, Arizona State University (2011) M.S., Electrical Engineering, Arizona State University (2008) B.S., Electrical Engineering, SungKyunKwan University (2003) His research bridges advanced IC design with applications in space telescopes, neuromorphic computing, and high-performance systems. At NASA JPL (2019-2023), he developed ASICs for far-infrared superconducting detectors, while at SAIT (2014-2019) he focused on ultra-fast neuromorphic vision sensors. His recent grants include NASA funding for superconducting photon detector readout systems (2022-2026) and ONR support for FFT accelerator development (2024-2027). The selected publications highlight his work in neuromorphic computing, dynamic vision sensors, and high-speed microelectrode arrays. These span interdisciplinary areas of Machine Learning , Neuroscience , and Biomedical Engineering . His lab at URI develops hardware solutions for extreme environments, including space applications and spiking neural networks. NASA Grant: $1,425,760 (Principal Investigator, 2022-2026) ONR Grant: $990,027 (Lead Principal Investigator, 2024-2027)

Francesco Piroمشاهده پروفایل

پژوهشگر

• Electronic mixed signal design
• ASIC development and validation
• Particle physics
• +۴ مورد دیگر

Francesco Piro is an Early Stage Researcher (ESR 12) at CERN, affiliated with the STREAM project's Work Package 4 (Validation and Qualification). As a member of the ATLAS design group, his work focuses on analog and mixed-signal circuit design for monolithic CMOS sensors used in particle detectors and accelerator beam monitoring. Host Institution: CERN Education: BSc and MSc in Electronics Engineering from University of Naples Federico II (IT), Master Thesis at University of Geneva (Département de Physique Nucléaire et Corpusculaire) His research interests center on radiation-hard electronics and semiconductor detector development, particularly for high-energy physics applications. His work bridges circuit design and sensor characterization through laboratory measurements and testbeam experiments, aiming to optimize performance while reducing costs via industrial CMOS processes. The article he co-authored demonstrates his focus on CMOS sensor innovation for tracking particles in high-luminosity environments, with potential applications in medical imaging and digital cameras. This aligns with his broader expertise in ASIC development and device physics. Francesco collaborates internationally at CERN and contributes to advancing pixel detector technology. His spare time activities include swimming, sailing, and spearfishing, reflecting his passion for marine environments.

H. Fatih Uğurdağمشاهده پروفایل

استاد

• ASIC/SoC/FPGA design
• Embedded systems
• Machine vision
• +۴ مورد دیگر

H. Fatih Uğurdağ serves as Full Professor in Özyeğin University's Faculty of Engineering, Department of Electrical and Electronics Engineering, while holding dual leadership roles as Dean of the Faculty of Engineering and Director of the Graduate School of Science since March 2022. He concurrently chairs IEEE Türkiye Section, representing 400,000 global members including 2,000 in Turkey. His academic foundation includes dual Bachelor's degrees in Electrical & Electronics Engineering and Physics from Boğaziçi University (1986), followed by Master's (1989) and Ph.D. (1995) in Electrical Engineering & Applied Physics from Case Western Reserve University (CWRU), where his thesis work focused on machine vision and computer architecture. Research spans integrated circuit design and real-time systems, with core expertise in ASIC/SoC/FPGA automation, embedded systems, and machine vision. Applied domains include electric vehicles, high-frequency trading infrastructure, intelligent transportation, and educational software tools. His industry background at NVIDIA, Juniper, and GM informs practical hardware-software integration approaches. No scientific awards or fellowships are documented in the source materials. As academic administrator, he oversees faculty development and graduate programs while advising doctoral candidates. His nEMESysLab (Emerging Memory and Embedded Systems Laboratory) drives research in memory architectures and real-time embedded applications, though specific student names and grant details remain unlisted in provided texts.

Ali Sahafiمشاهده پروفایل

استادیار

• Electrical Engineering
• Computer Science
• Biomedical Engineering
• +۴ مورد دیگر

Ali Sahafi is an Assistant Professor at the Institute of Mechanical and Electrical Engineering , University of Southern Denmark, specializing in Digital and High Frequency Electronics . His research bridges Electrical Engineering , Computer Science , and Biomedical Engineering . Research Interests: Sahafi focuses on neural network accelerators , medical imaging for cardiovascular and gastrointestinal diagnostics, and low-power electronics for embedded systems. His work includes applying YOLO-V8 for polyp detection in colonoscopy and coronary segmentation in angiography, alongside FPGA-based solutions for wireless capsule endoscopy. Project Involvement: He contributed to the EU H2020 TeamPlay project (2018–2020), optimizing time, energy, and security in cyber-physical systems. His lab, Digital and High Frequency Electronics , drives innovations in high-frequency circuits and embedded AI.

• Wireless Communications
• Radio Frequency (RF) Engineering
• Signal Processing
• +۴ مورد دیگر

Ronan Farrell is a Professor in the Department of Electronic Engineering at Maynooth University’s Faculty of Science & Engineering and currently serves as Vice President Academic and Registrar. He earned a BE and PhD from University College Dublin (1993, 1998) and previously worked at ICI/Zeneca Chemicals (1993–1995) and Parthus Technologies (1998–2001) as a mixed-signal ASIC designer. His academic career at Maynooth spans from Lecturer to Professor (2016), with leadership roles as Head of Department (2012–2019) and Director of the Callan Institute (2008–2015). He leads SFI research initiatives in radio frequency electronics and sensor networks. Education: BE (1993), PhD (1998) – University College Dublin Leadership: Head of Electronic Engineering (2012–2019), Director of Callan Institute (2008–2015) Research Focus: Wireless system design, RF/mixed-signal electronics, technology transfer, and innovation. His work bridges theoretical advancements (e.g., MIMO capacity optimization) with practical applications (e.g., 5G transmitters, digital predistortion techniques). Publication Trends: Recent articles emphasize 5G wireless systems, power amplifier linearization, OFDM signal processing, and behavioral modeling. Collaborations span institutions in Ireland, Europe, and Asia, with a focus on hardware implementation and system optimization. Students & Collaborations: Mentions co-authors in publications but no explicit student list provided. Collaborates with researchers in Ireland, Germany, and China.

• text processing algorithms
• classification of texts
• data processing and analysis
• +۳ مورد دیگر

Голуб Тетяна Василівна serves as an Associate Professor in the Department of Computer Systems and Networks at Zaporizhzhia National Technical University's Faculty of Computer Science and Technologies. With over 12 years of academic experience since joining the university in 2011, she specializes in computer electronics, computer circuitry, signal and image processing, and reliability of computer systems. Dr. Golub's research focuses on text processing algorithms, text classification, and data processing with particular emphasis on hardware acceleration using FPGA technologies. Her work bridges theoretical computer science with practical engineering applications, developing efficient methods for natural language processing tasks through specialized hardware implementations. She has pioneered approaches to optimize text classification speed while maintaining accuracy through innovative vector space modeling and stemming algorithms. Her publication record shows a strong trajectory from foundational work on text classification methods (2019) through hardware acceleration techniques (2020-2021) to current research on AI applications in education and neural network-based classification systems (2023-2025). The research demonstrates consistent focus on improving computational efficiency of text processing systems while expanding into educational technology applications. Dr. Golub maintains active scholarly presence with verified profiles on Scopus (ID: 57189328111), Web of Science (Researcher ID: G-9688-2019), Google Scholar, and ORCID (0000-0001-6024-008X), reflecting her commitment to academic transparency and international scholarly communication. She teaches core computer engineering subjects while conducting research that combines theoretical computer science with practical hardware implementation. Her laboratory work in computer electronics provides students with hands-on experience in circuit design and digital systems. Fluent in English, Ukrainian, and Russian, Dr. Golub operates from room 53b at the university's Zaporizhzhia campus (69063, Ukraine, Zhukovsky Street, 64).

Kirsty McDonaldمشاهده پروفایل

مدرس

• Biomechanics
• Motor Control
• Human Movement Science
• +۵ مورد دیگر

Dr Kirsty McDonald is a Lecturer in the School of Health Sciences within the Faculty of Medicine and Health at the University of New South Wales (UNSW). She sits at the intersection of health and engineering with expertise in human biomechanics, motor control, and physiology. Her research explores optimization principles in human movement across contexts including metabolic cost, muscle fatigue, musculoskeletal loading, stability, pain, and cognitive demands. Dr McDonald earned her PhD from The University of Western Australia in 2018, following a BSc (Hons) in 2013 and a BSc in 2011, both from the same institution. She was Valedictorian in 2014 and received the Rod Fry Prize and Frank Pyke Memorial Scholarship in 2013. Her research program applies biomechanical insights to improve quality of life for people with movement disability, enhance athletic performance and injury prevention, and promote physical activity engagement. She leads investigations into footwear biomechanics, prosthetic design, fall prevention in older adults, and fundamental principles of human movement optimization. Her work bridges theoretical biomechanics with practical applications in rehabilitation and sports performance. Analysis of her recent publications reveals a strong translational focus with significant contributions to understanding how advanced footwear affects running biomechanics (particularly with fatigued muscles), development of innovative prosthetic solutions for walking and running, and investigation of trip recovery mechanisms in older populations. Her research consistently connects fundamental biomechanical principles with real-world applications. Early Career Educator of the Year, School of Health Sciences, UNSW (2022) Australian Postgraduate Award and UWA Safety Net Top-Up Scholarship (2014-2017) Semi-finalist, Nike Ease Challenge (2016) Valedictorian, UWA (2014) Rod Fry Prize, UWA (2013) Frank Pyke Memorial Scholarship, UWA (2013) Dr McDonald actively supervises PhD students including John Kerr and Key Nahan as primary supervisor. Her extensive grant portfolio includes Chief Investigator roles on projects related to pain stimulation during locomotion, footwear biomechanics, and prosthetic socket fitting. She has secured funding from UNSW Research Infrastructure Scheme, ASICS Oceania, and the American Society of Biomechanics, totaling over $400,000 in recent years. As leader of the Locomotion Research Group (LRG) at UNSW, she oversees research on fundamental movement principles and their application to develop innovative solutions for movement disorders and performance enhancement. The group collaborates with industry partners including ASICS and clinical organizations to translate research into practical applications.

Amr Mahmoudمشاهده پروفایل

استادیار

• Neuromorphic Computing
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Dr. Amr Mahmoud is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh. His work focuses on neuromorphic computing systems, machine learning, and FPGA-based accelerators for image processing and video prediction. PhD in Computer Engineering, University of Pittsburgh (2019) MSc in Engineering Physics, Cairo University (2015) BSc in Electronics and Electrical Communications Engineering, Cairo University (2011) Dr. Mahmoud’s research bridges neuromorphic computing and machine learning, particularly for biomedical and sensor applications. He designs systems leveraging memristor crossbar arrays to emulate biological neural networks, enabling energy-efficient hardware solutions for tasks like cardiac arrhythmia classification and optical sensor prediction. His recent publications highlight advancements in memristor modeling, hybrid spiking neural networks, and hardware implementations using neuromorphic architectures. Key trends include real-time biomedical diagnostics, LSTM-based sensor prediction, and crossbar array optimization for machine learning. Contact: AMM418@pitt.edu

• Astroparticle Physics
• Instrumentation
• Cherenkov Telescopes
• +۳ مورد دیگر

Simone Incardona serves as a Research Fellow in the Department of Physics and Chemistry 'Emilio Segrè' at the University of Palermo, where he contributes to advanced instrumentation for gamma-ray astronomy and interdisciplinary machine learning applications. His institutional affiliation centers on the Cherenkov Telescope Array (CTA) project, specifically the development of the Schwarzschild-Couder Telescope (SCT) prototype. His research spans astroparticle physics instrumentation with emphasis on silicon photomultiplier (SiPM) technology and front-end electronics for Cherenkov light detection. Key focus areas include ASIC design for telescope cameras, optical system commissioning, and neural network architectures for time series analysis. This dual expertise in hardware development and computational methods supports cutting-edge observations in high-energy astrophysics. Analysis of his 2021-2023 publications reveals concentrated work on the pSCT prototype, addressing SiPM array assembly, SMART ASIC characterization, and Crab Nebula detection. The research trajectory demonstrates progression from component-level testing (2021) to integrated system validation (2023), with consistent contributions to CTA's medium-sized telescope instrumentation. No scientific awards were documented in available sources. Student advising activities and research grant details remain unspecified in current records, though his role involves supervising technical aspects of telescope instrumentation projects. He operates within the University of Palermo's CTA collaboration team, focusing on the pSCT's camera development and optical subsystems. This group interfaces with international partners in the global Cherenkov Telescope Array Observatory, contributing to hardware validation and observational campaigns.

François-Raymond Boyerمشاهده پروفایل

دانشیار

• Computer Architecture
• VLSI Systems
• Microelectronics
• +۴ مورد دیگر

François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.

Syed Asad Alamمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Embedded Systems
• Quantization
• +۵ مورد دیگر

Syed Asad Alam is a Post-Doctoral Research Fellow at the School of Computer Science and Statistics, Trinity College Dublin, The University of Dublin, Ireland, specializing in optimization and efficient implementation of digital systems for signal processing and communication algorithms. Education: Bachelors in Computer and Information Systems Engineering, N.E.D. University of Engineering and Technology, Karachi, Pakistan M.Sc. in Electrical Engineering (System-on-Chip Design), Linköping University, Sweden PhD in Electrical Engineering (Computer Engineering/Electronics Systems), Linköping University, Sweden His research integrates Machine Learning with Embedded Systems through novel approaches to Quantization and Logarithmic Number Systems , targeting efficient Neural Networks implementation on FPGAs and ASICs . This work builds on extensive industry experience with multimedia processors, communication devices, and SOC bus design, including specialized projects on filters, wireless systems, frequency multipliers, and DSP processors. His 2020 LCTES publication on non-base-2 logarithmic systems exemplifies his focus on numerical representation efficiency for resource-constrained embedded applications, reflecting broader trends in hardware-aware machine learning optimization. No scientific awards or grant information was documented in the source material. He has collaborated with multiple industry teams on FPGA-based design and Integrated Circuit Development across startup environments, though specific advising roles or student supervision were not indicated.

• Acid-Sensing Ion Channels
• Neuropharmacology
• Membrane Protein Dynamics
• +۳ مورد دیگر

Stephanie Heusser serves as an Assistant Professor in the Department of Drug Design and Pharmacology within the Faculty of Health and Medical Sciences at the University of Copenhagen. Her research focuses on the structural and functional characterization of acid-sensing ion channels (ASICs), with particular emphasis on their role in neurological disorders and potential as therapeutic targets. Based at Universitetsparken 2 in Copenhagen, she maintains an active research program integrating biophysical, pharmacological, and chemical biology approaches. Her primary research interests center on acid-sensing ion channel mechanisms , including: Conformational dynamics during activation and desensitization Regulation by transporter proteins and peptide modulators Structural basis of pH sensing and ion selectivity Therapeutic targeting for pain, stroke, and neurodegenerative conditions Protein engineering approaches to study channel function Recent publications reveal a strong focus on ASIC structure-function relationships, with significant contributions to understanding channel-transporter crosstalk and venom peptide inhibition mechanisms. Dr. Heusser's work demonstrates substantial scholarly impact, with her 2021 review article in Trends in Pharmacological Sciences accumulating 35 citation indexes and 49 Mendeley readers, while being referenced in 15 X (Twitter) discussions and 1 Wikipedia page. Her research shows consistent high-impact output in premier journals including Nature Communications , eLife , and Cell Chemical Biology , with collaborative networks spanning multiple international institutions. Her laboratory utilizes advanced techniques including: Protein semisynthesis for site-specific modifications Electrophysiological characterization of channel function Structural biology approaches to map conformational changes Pharmacological profiling of channel modulators Current work explores channel-transporter crosstalk mechanisms and the development of novel therapeutic strategies targeting ASIC-mediated pathologies.

Stephan Plessمشاهده پروفایل

استاد

• Ion Channels
• Pharmacology
• Electrophysiology
• +۵ مورد دیگر

Stephan Pless is a Professor in the Department of Drug Design and Pharmacology at the University of Copenhagen's Faculty of Health and Medical Sciences. His research focuses on the molecular function and pharmacology of ion channels, which regulate cellular excitability by controlling ion flux across cell membranes. These membrane proteins are therapeutically relevant targets as their dysfunction is associated with numerous diseases. Dr. Pless received his Graduate degree (diploma) from the University of Hamburg, Germany (1998-2004), followed by a PhD from the University of Queensland, Brisbane, Australia (2005-2008). He completed postdoctoral training at the University of British Columbia, Vancouver, Canada (2008-2013). Dr. Pless leads a research group that investigates the function and pharmacology of ion channels using a combination of electrophysiology, synthetic amino acids, protein engineering, and spectroscopic approaches. His work primarily focuses on acid-sensing ion channels (ASICs) and sodium leak channels (NALCN), with implications for understanding pain sensation, neurological disorders, and potential therapeutic interventions. The lab employs innovative technologies including non-canonical amino acid incorporation, protein splicing and various spectroscopic methods to study channel structure-function relationships. Analysis of Dr. Pless's recent publications reveals a strong focus on understanding the structural and functional mechanisms of ion channels, particularly ASICs and NALCN. His work spans from basic biophysical characterization to therapeutic applications, with increasing integration of computational methods and protein engineering approaches. A notable trend is the exploration of protein-protein interactions within channel complexes and the development of novel modulation strategies. Lundbeck Foundation Collaborative Project Grant (2023-2027) Paul F Cranefield Award from the Society of General Physiologists (2020) Lundbeck Foundation Ascending Investigator Grant (2019-2023) DFF Sapere Aude Starting Grant (2018-2021) Carlsberg Foundation Distinguished Associate Professor Fellowship (2017-2020) Lundbeck Foundation Fellowship (2013-2018) Dr. Pless has successfully secured significant research funding throughout his career, beginning with postdoctoral fellowships from the Michael Smith Foundation, Banting Postdoctoral Research Fellowship, and Heart & Stroke Foundation. His independent career has been supported by prestigious grants from the Lundbeck Foundation, Carlsberg Foundation, and Danish Independent Research Fund. His lab, the Pless Lab (www.theplesslab.com), actively recruits motivated students and postdocs interested in ion channel research. The Pless Lab is part of the vibrant research community at the University of Copenhagen, situated in one of the world's most livable cities known for its bicycle-friendly infrastructure and high quality of life. The lab collaborates extensively with researchers both within Denmark and internationally, as evidenced by the diverse authorship on recent publications.

Runchun Mark Wangمشاهده پروفایل

پژوهشگر

• Neuromorphic Engineering
• Mixed-signal/analog VLSI design
• ASIC/SoC/FPGA design
• +۵ مورد دیگر

Dr Runchun Mark Wang is a Researcher at the International Centre for Neuromorphic Systems (ICNS) at Western Sydney University, specializing in hardware acceleration for neural systems. He develops FPGA and mixed-signal analog VLSI platforms capable of simulating human-brain-scale neural networks and leads hardware design for the Neuromorphic Imager for Space Situational Awareness, providing open-source software tools for broader research access. His educational background includes: PhD from Western Sydney University (2013) MSEE from Shanghai Jiaotong University (2008) BSEE from East China University of Science and Technology (2003) Wang's research spans neuromorphic engineering, computational neuroscience, and hardware implementation of deep learning systems. His work bridges theoretical neural models with practical electronic systems, emphasizing scalable architectures for cognition simulation and space applications through integrated circuit design. Key recognitions include: Australian Research Council Postdoctoral Research Fellowship (2014–2017) Australian Postgraduate Research Award (2009–2013) Prior to academia, Wang worked as an industry SoC/ASIC design engineer, bringing practical hardware expertise to his current research leadership at ICNS. His projects focus on open-source neuromorphic tools and space-imaging technology with real-world deployment potential.