جستجوی استاد راهنمای دانشگاهی

Sergey Vakhrushevمشاهده پروفایل

دانشیار

• Glycomics
• Proteomics
• Glycoproteomics
• +۷ مورد دیگر

Sergey Vakhrushev serves as Associate Professor in the Department of Cellular and Molecular Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. He leads the Vakhrushev Group, which focuses on proteome-wide characterization of O-glycan structures at specific sites in O-glycoproteins. His research addresses fundamental challenges in glycoproteomics through innovative methodological approaches. Dr. Vakhrushev's primary research centers on post-translational modifications, particularly protein glycosylation. His group has made significant breakthroughs using genetically engineered 'SimpleCells' to overcome limitations in O-glycoproteome analysis, reporting over 15,000 O-glycosites and 5,000 O-glycoproteins. His work spans next-generation glycoproteomics, tyrosine O-GalNAc glycosylation, clinical glycoproteomics, and computational glycoinformatics. The research addresses critical challenges in simultaneous identification and quantification of native glycan structures on single glycosites, as well as glycosite occupancy and stoichiometry determination. His recent publications demonstrate a strong focus on advancing glycoproteomics through methodological innovation with applications spanning basic science to clinical diagnostics. His work on aberrant glycosylation in cancer development shows particular promise for biomarker discovery. The research has significant implications for understanding biological functions in health and disease across multiple organ systems including liver, kidney, and brain. Dr. Vakhrushev maintains an extensive international collaboration network spanning institutions in Zaragoza, Porto, Singapore, Muenster, Copenhagen, Split, Rome, Wien, and Athens. His research has garnered substantial attention, with publications being picked up by 72 news outlets, blogged by 3 sources, and widely shared across social media platforms including 39 X posts and numerous Bluesky references. His work has attracted significant academic interest with over 100 Mendeley readers across recent publications.

Miron Kłosowskiمشاهده پروفایل

استادیار

• CMOS Image Sensor Design
• Analog-to-Digital Converters
• Field-Programmable Gate Arrays
• +۵ مورد دیگر

Dr. Miron Kłosowski serves as an Assistant Professor at the Department of Microelectronic Systems within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. His primary workplace is located in Building A of the Faculty, room 309, where he conducts research and teaching activities in microelectronic systems and image sensor technologies. Dr. Kłosowski obtained his "dr inż." (Doctor of Engineering) degree on January 23, 2001, in the field of Electronics (Technology) from the Faculty of Electronics Telecommunications and Informatics. His academic journey has focused on the intersection of analog circuit design and digital image processing. His research program centers on advanced microelectronic systems with particular emphasis on image sensors and analog-to-digital conversion architectures. Dr. Kłosowski's work bridges theoretical circuit design with practical applications in imaging technology through: CMOS image sensor architecture and optimization for reduced noise Innovative analog-to-digital converters with embedded processing capabilities Low-power circuit design techniques for sensor interfaces Digital correction methods for image sensor non-uniformities Field-programmable gate array implementations for real-time signal processing Massively parallel imaging array architectures Analysis of Dr. Kłosowski's publication record (2017-2024) reveals a consistent research trajectory toward more integrated, efficient solutions for digital pixel sensors. His most recent work demonstrates significant advancements in on-the-ramp processing techniques that enable simultaneous image acquisition and filtering. The research spans both theoretical circuit innovations and practical implementations with applications in biomedical imaging and general-purpose camera technology. His educational contributions include adapting hardware teaching methodologies to remote environments during the pandemic, as documented in his IEEE Transactions on Education publication. Dr. Kłosowski maintains an extensive teaching portfolio across multiple engineering disciplines, regularly instructing courses in programmable circuits, FPGA applications, and digital signal processing. His teaching responsibilities span undergraduate and graduate programs in Electronics and Telecommunications, Informatics, and Biomedical Engineering, with consistent course offerings through the 2024/25 academic year. He participates in research initiatives including the HAPADS project (Highly Accurate and Autonomous Programmable Platform for Providing Air Pollution Data Services to Drivers and Public), which is funded through Norwegian and EEA funds under the Applied Research Program. This project is realized through the Department of Microelectronic Systems under agreement NOR/POLNOR/HAPADS/0049/2019-00.

• Signal Processing
• Wireless Communications
• Radar Systems
• +۵ مورد دیگر

Mario Huemer is a Professor at the Institute of Signal Processing, Johannes Kepler University Linz (JKU), serving as Principal Investigator for 41 research projects including the Christian Doppler Pilot-Laboratory for Steel Industry Signal Processing and Machine Learning and the JKU LIT - SAL Intelligent Wireless Systems Lab. His expertise spans signal processing applications in wireless communications, radar systems, and machine learning. His primary research interests include: Signal Processing Wireless Communications Radar Systems Machine Learning Joint Communications and Sensing Calibration Techniques Automotive Systems 5G/6G Networks Recent publications reveal strong trends in deep learning for signal processing, robust 5G/6G waveform design, and advanced automotive radar techniques. His work consistently bridges theoretical innovation with industrial implementation, particularly in ADC calibration, I/Q imbalance correction, and joint sensing-communication systems. No scientific awards are listed in the provided information. Huemer has supervised 29 students and leads diverse research initiatives including industry collaborations (e.g., automotive radar systems) and publicly funded projects like the Christian Doppler Laboratory. Current projects focus on radar synchronization (2025-2028), steel industry signal processing (2025-2032), and intelligent wireless systems development (2024-2026). He directs the Intelligent Wireless Systems Lab (IWS Lab), a JKU LIT-SAL collaboration advancing interdisciplinary research in wireless communications, sensing, and machine learning with strong industry partnerships.

David Sanchezمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Numerical Analysis
• Mathematical Physics
• +۵ مورد دیگر

David Sanchez is an Associate Professor at the Institut National des Sciences Appliquées (INSA) of Toulouse in the Department of Mathematical Engineering and Modeling. He holds multiple affiliations including membership in the Toulouse Institute of Mathematics (IMT) PDE Team and an associate researcher position at the Center for Integrative Biology (CBI) in the Molecular Cellular and Developmental Biology Laboratory (MCD) DEMO team. His research spans several interconnected fields of mathematical analysis and modeling. Professor Sanchez specializes in the analysis of partial differential equations, with focus on nonlinear and asymptotic analysis of parabolic and elliptic systems. His work in ferromagnetism involves developing asymptotic models for spintronics and studying magnetization configurations in nanowires. He also conducts significant research on biological fluids, particularly mathematical models of mucus flow in lungs and mucociliary clearance processes. The trends in his publications show consistent work in mathematical physics, with increasing interdisciplinary applications in biology and computer science over time. His recent publications (2019-2025) demonstrate strong activity in both theoretical mathematics and applied biological modeling, with research spanning from ferromagnetic nanowires to zebrafish embryonic development. Professor Sanchez has received recognition through his extensive publication record in high-quality journals including ESAIM: Mathematical Modeling and Numerical Analysis, Journal of Computational Physics, and Journal of Differential Equations. His interdisciplinary approach connects mathematical theory with practical applications across physics, biology, and computer science. His advising and research activities involve collaborations across multiple institutions including Université Toulouse III - Paul Sabatier, Université Bordeaux, and international partners. His work bridges theoretical mathematics with applications in physics, biology, and computer science through interdisciplinary research teams. Professor Sanchez maintains an active research laboratory focused on mathematical modeling, with particular emphasis on partial differential equations and their applications to physical and biological systems. His team works on both theoretical analysis and numerical implementation of mathematical models across multiple application domains.

• Collective Animal Behavior
• Statistical Physics
• Biological Physics
• +۵ مورد دیگر

James G. Puckett is a Professor in the Department of Physics and Astronomy at Gettysburg College, where he conducts research at the intersection of physics and biology. His work primarily focuses on collective behavior in biological systems, particularly insect swarms and fish schools, as well as granular materials and statistical physics. His research interests include collective animal behavior, statistical physics, biological physics, granular materials, and network analysis. Dr. Puckett employs advanced experimental techniques including multicamera imaging and tracking systems to study the motion of individual organisms within groups, developing mathematical models to explain emergent collective phenomena. His work has revealed important insights into pairwise interactions in insect swarms, adaptive long-range interactions, and thermodynamic analogies in collective animal behavior. Analysis of his publications shows a consistent focus on understanding how local interactions between individuals give rise to complex collective behavior. His research spans both biological systems (insect swarms, fish schools) and physical systems (granular materials), demonstrating the power of physics approaches to understand diverse phenomena. The interdisciplinary nature of his work bridges physics, biology, and mathematics. Throughout his career, Dr. Puckett has published in prestigious journals including Physical Review Letters, with research that has been cited over 45 times according to metrics shown in the repository. His collaborations include researchers from Yale University, Penn State, and other institutions, reflecting the collaborative nature of modern interdisciplinary research. Dr. Puckett's laboratory work involves sophisticated experimental setups for tracking individual organisms in controlled environments, combined with advanced data analysis techniques including time-frequency analysis, network analysis, and statistical modeling. His research has implications for understanding not only natural biological systems but also for developing principles applicable to robotics and artificial collective systems.

Mohammad Khaleqi Qaleh Jooqمشاهده پروفایل

پژوهشگر ارشد

• Neuromorphic Computing
• ASIC Design
• Emerging Devices
• +۷ مورد دیگر

Dr. Mohammad Khaleqi Qaleh Jooq serves as a Postdoctoral Research Fellow at the International Centre for Neuromorphic Systems (ICNS), Western Sydney University. Previously, he held a Brain Pool Postdoctoral Research Fellowship at Inje University, South Korea from 2022 to 2024. His academic background includes: Ph.D. in Electrical Engineering, Lorestan University, Khorramabad, Iran (2019) His research focuses on neuromorphic hardware systems and next-generation electronics, with primary expertise in ASIC design for real-world applications, carbon nanotube-based devices, and fuzzy logic implementations. His work bridges theoretical device modeling with practical image processing solutions through emerging beyond-CMOS technologies and approximate computing paradigms. As an active member of the International Centre for Neuromorphic Systems, he contributes to advancing brain-inspired computing architectures while exploring nanoscale device physics for next-generation hardware implementations.

Lucas J. Koernerمشاهده پروفایل

دانشیار

• Image sensors
• Camera systems
• Optical time-of-flight
• +۹ مورد دیگر

Lucas J. Koerner is an Associate Professor in the Department of Electrical & Computer Engineering at the University of St. Thomas School of Engineering. He holds a PhD and MS in Physics from Cornell University and a BA in Physics and Mathematics from Northwestern University. Education: PhD in Physics, Cornell University MS in Physics, Cornell University BA in Physics and Mathematics (Integrated Science Program), Northwestern University Research Interests: Dr. Koerner specializes in electronics instrumentation for novel detection applications. His expertise spans image sensors , camera systems , optical time-of-flight , sensors , CMOS x-ray detectors , electrical instrumentation and data acquisition , and open source hardware . His work enables breakthroughs in medical diagnostics, scientific instrumentation, and industrial sensing through custom hardware solutions. Publication Trends: Recent publications (2018-2020) focus on embedded sensor networks, 3D-printed EMI shielding, and photodiode readout techniques. Earlier work (2006-2012) pioneered X-ray pixel array detectors for synchrotron and free-electron laser applications, enabling high-resolution protein crystallography and materials science breakthroughs through time-resolved measurements. Professional Experience: Prior to academia, Dr. Koerner developed radiation-hardened electronics for space missions at Johns Hopkins Applied Physics Lab and led camera electrical testing for mobile devices at a Fortune 500 company. His Cornell research created CMOS readout circuits for X-ray detectors used in single-particle diffraction studies. Teaching: He teaches Digital Design, Electricity & Magnetism, and Senior Design Clinic, emphasizing hands-on instrumentation development and open-source hardware principles.

Sara Achourمشاهده پروفایل

استادیار

• Programming Languages
• Compilers
• Runtime Systems
• +۲ مورد دیگر

Sara Achour is an Assistant Professor jointly appointed to the Computer Science and Electrical Engineering departments at Stanford University. She earned her PhD in Computer Science from MIT in 2021. Her research develops programming languages, compilers, and runtime systems for emerging analog computing platforms. Dr. Achour leads research in hardware-aware optimization frameworks and novel analog compute paradigms, with applications spanning quantum computing, IoT devices, and neuromorphic systems. Her research focuses on: Bridging software abstractions with unconventional hardware capabilities Energy-efficient computing paradigms for edge devices Cross-layer optimization of analog and hybrid computing systems Publication analysis reveals consistent themes in analog computing architectures, hardware-aware optimizations, and emerging computing platforms. Recent work explores quantum compilation techniques, hyperdimensional computing optimizations, and hardware security metrics. Dr. Achour advises multiple graduate students including: 16 doctoral candidates across computer architecture and quantum computing 10 master's students in software-hardware co-design She maintains active research collaborations through the Stanford SystemX Alliance.

Milad Zamaniمشاهده پروفایل

استادیار

• Integrated Circuits
• Biomedical Engineering
• Wireless Power Systems
• +۳ مورد دیگر

Milad Zamani is a Tenure Track Assistant Professor in the Department of Electrical and Computer Engineering at Aarhus University. His research focuses on integrated circuits, biomedical engineering, and wireless power systems with applications in neural engineering and sensor systems. He leads projects such as DONUT (European Doctoral Network for Neural Prostheses and Brain Research) and CorroSense (Self-powered corrosion monitoring). His work spans topics like bio-impedance sensing for wearables, ultrasonic energy transfer for implants, and high-precision analog circuits. Recent projects include thermally-powered leakage detection systems and optogenetic implantable devices. Zamani collaborates on advanced sensor technologies, neuromorphic hardware, and biomedical device miniaturization. His lab develops low-power circuits for medical applications, combining signal processing with cutting-edge microelectronic design.

• Analog Circuit Design
• RF/Microwave Engineering
• VLSI Design
• +۶ مورد دیگر

Dr. Ahmet Tekin is an Assistant Professor at the Department of Electrical and Electronics Engineering, Boğaziçi University. His research focuses on analog/mixed-signal/RF/microwave VLSI design, with emphasis on biomedical electronics, wireless communication systems, and integrated circuit innovation. He specializes in developing advanced sensor technologies, antenna arrays, and energy-efficient RF systems for healthcare, IoT, and aerospace applications. Key research areas include continuous glucose monitoring devices, optoelectronic blood pressure sensors, phased array transmitters for satellite communication, and resonance-based wireless charging systems. His work integrates cutting-edge semiconductor technologies like 22nm FDSOI and SOI CMOS with innovative circuit architectures. Dr. Tekin's recent publications highlight advancements in ultra-wideband antennas, adaptive sampling techniques, and biomedical IoT communication protocols. His research bridges electronics engineering with practical applications in healthcare, robotics, and renewable energy systems. Though no awards are explicitly mentioned, his prolific output in high-impact journals underscores his contributions to the field. He advises on interdisciplinary projects at the intersection of electronics and biomedical engineering, with a focus on wearable technologies and smart medical devices. His lab collaborates on energy harvesting systems and low-power biomedical sensors, reflecting a commitment to both foundational research and real-world solutions.

Sam Shichijoمشاهده پروفایل

استاد پژوهش

• Semiconductor Device Physics
• TCAD (Technology Computer Aided Design)
• Analog and RF Devices
• +۴ مورد دیگر

Sam Shichijo is a Research Professor in the Department of Electrical Engineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He has been actively contributing to research since 2010, particularly in analog and mixed-signal integrated circuit technologies through his affiliation with the Texas Analog Center of Excellence (TxACE). Prior to joining UT Dallas, he had a distinguished 29-year career at Texas Instruments, where he advanced semiconductor device and memory technologies. Ph.D. in Electrical Engineering, University of Illinois at Urbana-Champaign (1980) M.S. in Electrical Engineering, University of Illinois at Urbana-Champaign (1978) B.S. in Electronic Engineering, University of Tokyo (1974) His research focuses on semiconductor device physics , TCAD simulation , analog and RF devices , and IC process integration . His expertise spans from fundamental device modeling to advanced CMOS and mixed-signal technologies. He has made significant contributions to the development of DRAM and analog transistor technologies, especially in nanoscale CMOS processes. The recent publications highlight a strong trend in addressing challenges of analog design in scaled CMOS technologies , SRAM and analog transistor variation , and RF IC evolution . His work often intersects with TCAD, device optimization, and system-on-chip integration, emphasizing reliability and performance in deep-submicron processes. Sam Shichijo has received numerous honors, including: IEEE Fellow (1992) TI Fellow (1994) Outstanding Paper Award, ISSCC (1986) Guest Editor, IEEE Transactions on Electron Devices (2003) Conference Chair, Device Research Conference (1992) Organizer, IEDM Short Course (2000) He has advised various industry research directions through roles in ITRS, SRC, SEMATECH, and advisory boards. Although no formal students are listed, his leadership in technical programs and industry collaborations suggests significant mentorship and guidance in research teams and consortia. He has been instrumental in shaping technology roadmaps and advancing analog/mixed-signal integration through grants and industrial research programs. His work with TxACE and Organic Electronics at UT Dallas continues to drive innovation in analog electronics. He is associated with the Texas Analog Center of Excellence (TxACE) and the Organic Electronics program, where he contributes to cutting-edge research in analog components and next-generation electronic materials and devices.

Ignacio Bravo Muñozمشاهده پروفایل

استاد

• Electronics Engineering
• Signal Processing
• FPGA Applications
• +۳ مورد دیگر

Ignacio Bravo Muñoz is a Professor at the Department of Electronics, Universidad de Alcalá (Spain), affiliated with the GEINTRA research group focusing on Electronic Engineering applications in Intelligent Spaces and Transport. He holds a PhD from Universidad de Alcalá (2007) with a thesis on FPGA-based object detection using computational vision and PCA techniques. His research spans indoor positioning systems (using LED/PSD sensors), sustainable energy frameworks for smart communities, FPGA-based hardware design , and remote laboratory platforms . Key contributions include real-time metrology for ESA's PLATO mission, cooperative demand response algorithms, and innovative pedagogical approaches integrating sustainability into digital electronics education. Recent work emphasizes edge computing for video surveillance , machine learning in human action recognition , and non-cooperative target identification using radar signatures. His interdisciplinary projects bridge electronics engineering with energy systems, biomedical applications, and educational technology. He actively collaborates with industry and academic institutions on EU-funded projects, contributing to advancements in aerospace instrumentation (PLATO FPA qualification), smart grid technologies, and STEM education innovation.

Fabien Alibartمشاهده پروفایل

پژوهشگر

• Neuromorphic Computing
• Memristive Devices
• Bio-inspired Computing
• +۳ مورد دیگر

Fabien Alibart is a Research Officer and Permanent Researcher at the University of Sherbrooke (Canada), associated with the LN2-3IT/CNRS laboratory. His primary focus is on neuromorphic computing, memristive devices, and bio-inspired hardware solutions. He holds a PhD in Thin Film Physics from the University of Picardie Jules Verne (Amiens, France), specializing in optoelectronics and carbon-based devices. His research spans neuromorphic systems, organic electrochemical transistors, and memristive circuits. Key projects include developing iono-electronic materials for brain-inspired computing (IONOS project), cryogenic memristors, and 3D memory architectures. He has led multiple ANR and NSERC grants, focusing on neuromorphic interfaces and energy-efficient computing. Alibart's work intersects material science, electrical engineering, and biology. Notable contributions include memristor-based pattern classification, synaptic plasticity modeling, and neuromorphic hardware integration. His teams have pioneered organic/nanoparticle transistor synapses and developed CMOS-compatible memristive crossbars for analog AI acceleration. Collaborations span institutions like UdeM, IBM Zurich, and the European CHIST-ERA initiative. His lab focuses on advancing bio-interfacing technologies and neuromorphic engineering through multidisciplinary approaches.

Peter Lianمشاهده پروفایل

استاد

• Biomedical Circuits and Systems
• Low-Power Electronics
• Signal Processing
• +۴ مورد دیگر

Professor Peter Lian is a faculty member in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. He holds prestigious fellowships from IEEE, Canadian Academy of Engineering, and Singapore Academy of Engineering. His research focuses on biomedical circuits, low-power systems, and embedded AI for IoT sensors. He has served in numerous leadership roles within IEEE, including IEEE Board of Directors (2024-2025) and President of the IEEE Circuits and Systems Society (2018-2021). Education: B.Sc., College of Economics & Management, Shanghai JiaoTong University (1984) Ph.D., Electrical Engineering, National University of Singapore (1994) Research Interests: Specializes in wearable/implantable biomedical sensors, ultra-low-power circuits, event-driven sensor systems, and embedded AI. His work bridges biomedical engineering with low-power electronics design. Awards Summary: 2023 IEEE Mac Van Valkenburg Award for biomedical systems leadership 2023 Best Paper Award for cardiac arrhythmia classifier research 1996 IEEE Guillemin-Cauer Award for digital filter design Advising & Grants: Advised over 20 graduate students whose work received 30+ awards including IEEE grants. Active in mentoring student research teams in low-power biomedical systems and IoT sensor design. Labs & Collaborations: Leads research initiatives in biomedical circuits and energy-efficient systems, collaborating with industry on wearable health monitoring technologies.

• Microelectronics
• Nanotechnology
• VLSI Design
• +۷ مورد دیگر

Sumeet Gupta is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. His research focuses on device-circuit co-design in emerging nanotechnologies, spintronics, and low-power VLSI design. He leads interdisciplinary efforts in ferroelectric devices, neuromorphic computing, and energy-efficient hardware for AI applications. Education: B.Tech from IIT Delhi (2006), M.S. and Ph.D. from Purdue University (2008, 2012). Research Interests: Ferroelectric and spintronic materials for next-gen computing Non-Boolean computing architectures Compute-in-memory accelerators Low-power and variation-tolerant VLSI design Domain wall dynamics in thin films Neuromorphic engineering Key Contributions: Over 50+ peer-reviewed publications on ferroelectric transistors, crossbar array optimizations, and fault-tolerant neural network hardware. His work bridges material science, device physics, and circuit design to enable energy-efficient computing systems.