جست‌وجوی استاد و پژوهشگر

Dan NICULAمشاهده پروفایل

استاد

• Digital Systems
• Hardware Description Languages
• Electronics Design
• +۴ مورد دیگر

Professor Dan NICULA is a faculty member at the University of Transilvania in Brașov, Romania. He holds a Doctorate in Engineering (2017) from the same institution and a Master's degree in Applied Electronics Engineering from the Polytechnic University of Bucharest (1990). His academic roles include teaching courses such as Digital Electronics, Hardware Description Languages, and Digital Media Communication across undergraduate and graduate programs in Electrical Engineering and Computer Science. His research focuses on digital systems, hardware description languages (Verilog/VHDL), and electronic circuit design. Key contributions include textbooks like 'Digital Electronics: Emergency Textbook' (2020) and 'Verilog Textbook' (2019), which are foundational resources for students and professionals. He has supervised over 150 student theses, with recent topics spanning FPGA-based AI accelerators, UVM verification methodologies, and embedded system implementations. Professional experience includes roles at Intel (1999-2015) and Fotonation (2015-present), alongside his academic career. He is affiliated with the Faculty of Electrical Engineering and Computer Science and contributes to research initiatives in VLSI design, digital signal processing, and hardware-software co-design.

Mihai IVANOVICIمشاهده پروفایل

استاد

• Image Processing
• Remote Sensing
• Fractal Analysis
• +۳ مورد دیگر

Professor Mihai IVANOVICI is affiliated with the University of Transilvania in Brasov, Romania, serving in the Department of Electronic and Computers within the Faculty of Electrical Engineering and Computer Science . His research focuses on image processing, remote sensing, fractal analysis, and texture characterization , with applications in agriculture, biomedical engineering, and space technology. He leads projects integrating artificial intelligence into FPGA-based systems for cosmic radiation sensing and agricultural monitoring. Notable contributions include the DACIA5 dataset for crop identification and studies on vegetation indices using hyperspectral data. His work bridges theoretical analysis with practical implementations in domains like precision agriculture and satellite technology. Research Highlights: Developed fractal analysis models for soil roughness estimation and image segmentation Designed hardware accelerators for AI applications in gaming and space systems Explored EEG-based brain signal complexity linked to visual stimuli Awards: No awards explicitly listed in the provided texts. Grants & Collaboration: Active in EU-funded educational initiatives like InnEO’Space PhD for training young Earth Observation researchers. Collaborates with institutions on projects like the ATLAS New Small Wheel read-out controller ASIC. Contact: Located at Str. Institutului 10 (Corp L3) and Str. Politehnicii 1 (Corp N) in Brașov.

Traian TULBUREمشاهده پروفایل

مدرس

• Very Large Scale Integrated Circuits
• Digital Electronics
• Microelectronics
• +۴ مورد دیگر

Traian TULBURE is a Lecturer at the Department of Electronics and Computers within the Faculty of Electrical Engineering and Computer Science at the Technical University of Brașov. His research focuses on Very Large Scale Integrated Circuits, Digital Electronics, and reconfigurable architectures for structured ASIC technology. He has contributed to significant projects including the ATLAS experiment at CERN, particularly in developing readout controllers for muon spectrometers. Key research interests include optimizing testability in dynamic reconfigurable CPLD architectures and advancing structured ASIC applications. His work bridges microelectronics innovation with high-energy physics instrumentation, demonstrated through collaborations on particle detector systems. Publications emphasize both theoretical advancements (e.g., dynamic reconfiguration methodologies) and applied contributions to large-scale physics experiments. No scientific awards are explicitly mentioned, though his involvement in international collaborations like ATLAS highlights his professional standing. Advising activities and grant details are not detailed in the provided text. He has contributed to detector hardware development for the ATLAS New Small Wheel upgrade, reflecting his role in experimental physics instrumentation.

• Control Engineering
• System Identification
• Bayesian Estimation
• +۵ مورد دیگر

Adrian Wills is an Associate Professor in the School of Engineering (Mechatronics) at the University of Newcastle, Australia. He leads the Mechatronics Engineering program and holds academic appointments since July 2015. His research focuses on Bayesian estimation, system identification, and control engineering, with applications in robotics and mechatronics. Wills has collaborated with institutions globally, including Linköping University, Uppsala University, and the University of British Columbia. He earned his B.E. (Elec.) and Ph.D. from the University of Newcastle in 1999 and 2003, respectively. Teaching expertise includes delivering advanced courses in estimation and optimization within the Mechatronics Engineering program. Administrative roles include program convenor for Mechatronics Engineering. Research highlights include contributions to state-space models, nonlinear system identification, and model predictive control. His work bridges theoretical advancements with practical applications in engineering systems and healthcare. Key collaborations involve Professors Lennart Ljung, Thomas Schön, and Bhushan Gopaluni, among others. His technical contributions span MATLAB toolboxes (e.g., UNIT), FPGA/ASIC implementations for control systems, and interdisciplinary projects in strain measurement using neutron diffraction.

Dustin Richmondمشاهده پروفایل

استادیار

• Computer Architecture
• FPGA
• RISC-V
• +۴ مورد دیگر

Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.

• 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).

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

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.

Ali Al Batainehمشاهده پروفایل

استادیار

• Artificial Intelligence
• Hardware Security
• Cybersecurity
• +۵ مورد دیگر

Ali Al Bataineh serves as Director of the Center for Artificial Intelligence and Assistant Professor in the Department of Engineering at Norwich University's David Crawford School of Engineering. He holds a Ph.D. in Electrical Engineering from the University of Toledo (2021), with doctoral research focused on computational models inspired by the adaptive immune system. His research spans artificial intelligence applications in hardware security (including FPGA/ASIC Trojan detection), cybersecurity, natural language processing, and humanitarian disaster response. Key projects involve AI-driven optimization techniques and military/health sector implementations, supported by international collaborations with École Spéciale Militaire de Saint-Cyr (France) and Helmut Schmidt University (Germany). Dr. Al Bataineh co-leads Norwich University's $5.3 million NSF-funded cybersecurity initiative and is establishing a Military AI Virtual Data Center with German partners. He advises students to embrace persistence and curiosity in research, emphasizing failure as part of the learning process. No scientific awards are documented in the provided information.

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.