جستجوی استاد راهنمای دانشگاهی

Hanna Veselovskaمشاهده پروفایل

پژوهشگر

• Phase Retrieval
• Super-Resolution
• Sigma-Delta Modulation
• +۴ مورد دیگر

Hanna Veselovska is a researcher in the Data Science Group at the Technical University of Munich (TUM), part of the Faculty of Mathematics and the TUM School of Computation, Information and Technology. Her research focuses on Quantization Theory, Mathematical Perspectives of Machine Learning, Image Processing, and Graph Signal Processing. She holds a PhD from the Institute of Mathematics of the National Academy of Sciences of Ukraine (NASU) under Anatoly Holub and has held postdoctoral positions at TU Braunschweig (Germany) and the University of Lübeck (Germany as a DAAD fellow). Current Position: Researcher at TUM Data Science Group PhD: Institute of Mathematics of NASU (2017) Postdoc: TU Braunschweig (2018–2020), University of Lübeck (DAAD fellowship) Her research interests span Phase Retrieval, Super-Resolution, and Sigma-Delta Modulation, with contributions to numerical analysis and signal processing. She has published extensively on topics such as regularized sampling formulas, graph signal quantization, and non-intrusive surrogate modeling. Her work bridges theoretical mathematics with applied data science, with applications in image processing and crashworthiness analysis. Teaching includes courses on Modelling and Simulation with Differential Equations, Random Matrix Theory, and Foundations in Data Analysis at TUM, as well as engineering mathematics courses at TU Braunschweig. Key contributions include advancements in digital halftoning via sigma-delta modulation and recovery of atomic measures on spheres. Her research emphasizes interdisciplinary approaches to solving complex signal processing challenges.

• VLSI Design
• Integrated Circuits
• Computer Architecture
• +۶ مورد دیگر

Xiaoyang Zeng is a Professor at Tsinghua University's School of Information Science and Technology, Institute of Microelectronics, with an extensive research portfolio in VLSI design, integrated circuits, and hardware acceleration systems. With over 429 publications spanning from 2005 to 2025, Professor Zeng maintains an exceptionally active research program, particularly evident in the high publication volume in recent years (45 papers in 2024 and 28 projected for 2025). His collaborative network includes prominent researchers such as Yibo Fan, Jun Han, Xu Cheng, and Xiaoyong Xue. Professor Zeng's research focuses on cutting-edge areas including Compute-in-Memory architectures, neuromorphic computing, low-power circuit design, and hardware acceleration for AI applications. His work bridges theoretical innovation with practical implementation, as evidenced by numerous publications in top-tier IEEE journals including the Journal of Solid-State Circuits, Transactions on Circuits and Systems, and Transactions on VLSI Systems. Recent work demonstrates particular strength in RRAM-based CIM accelerators, energy-efficient converters, and advanced signal processing techniques. The publication trends show a strategic evolution from traditional circuit design toward emerging computing paradigms, with increasing focus on AI hardware acceleration, neuromorphic systems, and energy-efficient computing solutions. His research group has developed innovative approaches to address challenges in memory-centric computing, analog circuit design, and hardware implementation of machine learning algorithms, with applications spanning consumer electronics, medical devices, and edge computing systems. Selected Scientific Awards: IEEE Journal of Solid-State Circuits Best Paper Award (2022) National Natural Science Award of China (Second Class, 2020) IEEE Asian Solid-State Circuits Conference Best Paper Award (2019) Professor Zeng has successfully advised numerous graduate students who have become active contributors in the field, with several now leading their own research projects. His research has been supported by multiple national-level grants from the National Natural Science Foundation of China and the Ministry of Science and Technology, focusing on next-generation computing architectures and advanced circuit design methodologies. The research group maintains strong industry connections with leading semiconductor companies for technology transfer and practical implementation of research outcomes.

• Analog Circuit Design
• CMOS Technology
• Delta-Sigma Modulators
• +۳ مورد دیگر

Dr. Matthias Keller is a Senior Lecturer at the Department of Microelectronics, Faculty of Engineering, Albert-Ludwigs-Universität Freiburg. He holds a Dr.-Ing. (summa cum laude, 2010) from the same institution for his work on ΔΣ modulators. His research focuses on analog circuit design using CMOS technology, particularly ΔΣ analog/digital converters. He has served as Acting Chair of the Microelectronics Professorship (2020–2022) and received the 2014 Teaching Award from the Faculty of Engineering, the first non-professorial academic staff member to do so. He is actively involved in university governance, including roles in the Senate (since 2023), Faculty Council, and Examination Committee. Education: Diploma in General Electrical Engineering (Saarland University, 2003) Roles: Academic Councillor (since 2015), Acting Chair (2020–2022), Senate Member (2023–) His research emphasizes systematic approaches to noise-shaping architectures and mixed-signal integrated systems. Collaborative projects include work within the Institute for Microsystems Technology (IMTEK).

Salah H. Abouzaidمشاهده پروفایل

پژوهشگر

• Radar Technology
• Deep Learning
• Material Characterization
• +۳ مورد دیگر

Salah H. Abouzaid is a Researcher at the Faculty of Electrical Engineering and Information Technology , Ruhr University Bochum, affiliated with the Integrated Systems department. His work focuses on radar technology and sensor systems. Specializes in FMCW radar systems and deep learning applications Research interests include material characterization and vital signs monitoring Active in microwave theory, embedded systems, and neural network modeling His recent publications demonstrate expertise in radar-based material analysis, machine learning integration, and biomedical sensing. No students or awards are listed in available records.

Friedel Gerfersمشاهده پروفایل

استاد

• High-Speed Integrated Circuits
• Energy-Efficient RF Transceiver Design
• Silicon Photonics
• +۷ مورد دیگر

Prof. Dr.-Ing. Friedel Gerfers serves as the Einstein-Professor for Mixed Signal Circuit Design at the Technical University of Berlin since 2019, and has led the Mixed Signal Circuit Design (MSC) group since 2015. Prior to academia, he held industry roles as Design Manager at Apple Inc. (2014-2015) and Technical Director at Integrated Device Technology (IDT) (2012-2014). High-Speed Integrated Circuits (GS/s range) Energy-Efficient RF/Transceiver Architectures Silicon Photonics Applications Ultra-Low-Power Sensor Readout Systems His research focuses on mixed-signal calibration algorithms , semiconductor design flows , and FinFET technology down to 14nm. Recent work emphasizes 22nm FD-SOI CMOS for high-performance applications. Key publication trends include: High-Speed ADC/DAC designs (12-18.5 GS/s) Advanced RF sampling techniques Error correction in current-steering DACs Optical interconnects (VCSEL-based systems) Current affiliations: Technical University of Berlin IEEE Conference Publications German Microwave Conference (GeMiC) Collaborations

• Analog Integrated Circuits
• Mixed-Signal VLSI Design
• High-Speed Data Converters
• +۷ مورد دیگر

Yan Zhu is a faculty member at the University of Macau , affiliated with the Analog and Mixed Signal VLSI Laboratory within the Faculty of Science and Technology. She has a strong research focus on high-performance analog and mixed-signal integrated circuits, particularly in data conversion and low-power design. Her research interests include: Analog and Mixed-Signal VLSI Design High-Speed Data Converters (ADCs) Noise-Shaping and Time-Domain Circuits PVT-Robust and Low-Power Circuit Techniques Compute-in-Memory and AI Hardware Acceleration The recent publications of Yan Zhu demonstrate a clear trend toward advanced ADC architectures such as time-interleaved, pipelined-SAR, and time-domain converters, with a strong emphasis on calibration, linearity, and energy efficiency. Her work frequently appears in top-tier journals like IEEE JSSC and conferences like ISSCC and CICC, indicating leadership in the field of analog circuit design. There is also a growing focus on machine learning hardware, particularly analog compute-in-memory systems for edge AI applications. No scientific awards or honors are mentioned in the provided text. Yan Zhu has made significant contributions through collaborative research, particularly with Chi-Hang Chan and Rui Paulo Martins , and has been involved in numerous projects related to ADC calibration, metastability, and high-speed sampling. While specific grant details are not listed, the volume and quality of publications suggest active funding support. She has not listed any advisees in the provided data. She is a core contributor to the Analog and Mixed Signal VLSI Laboratory at the University of Macau, where her team focuses on cutting-edge IC design for communication, sensing, and artificial intelligence applications.

• Communication Systems
• Digital Signal Processing
• Digital Circuit Technology
• +۴ مورد دیگر

Prof. Georg Schmidt is a Professor at Esslingen University of Applied Sciences since 2011, specializing in communication systems, digital technology, and coding theory. He holds a PhD in algebraic decoding of Reed-Solomon codes and has extensive industry experience, including roles at Ubidyne GmbH and the University of Ulm's Institute of Telecommunications Technology. His research interests span digital signal processing, embedded systems security, and error-correcting codes. He lectures on advanced channel coding and serves on the DV and Foreign Affairs Committees. Education: 1994–2000: Studied Electrical Engineering at the University of Ulm, focusing on systems engineering, communications, and network technology. Doctorate: Algebraic decoding of Reed-Solomon codes over half the minimum distance (University of Ulm). Research Focus: Communication systems and digital signal processing. Coding theory (e.g., Reed-Solomon codes, expander codes). Data security and embedded systems. Motor control and delta-sigma modulation techniques. Recent Publications Trends: Recent work emphasizes practical applications like Bluetooth Low Energy systems, energy harvesting, and advanced motor control algorithms, complementing foundational research in coding theory and error correction. Awards & Grants: No specific awards or grants listed. Active in patenting (e.g., antenna arrays, calibration methods, and energy systems). Advising & Labs: No student advisees listed. Engaged in collaborative projects on coding and industrial communication at Esslingen’s engineering faculty.

Sebastian Sternمشاهده پروفایل

پژوهشگر

• Wireless Communications
• MIMO Systems
• Lattice Coding
• +۳ مورد دیگر

Dr.-Ing. Sebastian Stern serves as a Senior Researcher at the Institute of Communications Engineering, Ulm University, Germany. His research focuses on advanced communication systems with particular expertise in MIMO transmission, lattice-based coding, and optical communications. Stern maintains active collaborations with researchers including Robert F.H. Fischer and Johannes K. Fischer across multiple publications. His educational background includes a dissertation titled Advanced Equalization and Coded-Modulation Strategies for Multiple-Input/Multiple-Output Systems (2019) from Ulm University, building upon his Master's thesis Comparison of the peak value behavior of single- and multi-carrier methods (2012) which earned the VDE Award for Outstanding Master Thesis. Stern's research interests span wireless communications, optical transmission systems, and advanced signal processing techniques. His work demonstrates significant contributions to 4D constellation design using Hurwitz and Eisenstein integers, lattice reduction methods for MIMO systems, and non-binary coding schemes for high-throughput fiber-optic communication. Recent publications show expanding work into quaternionic lattices and AI applications for network security. His publication record shows consistent output since 2013 with 25+ journal and conference papers, including high-impact publications in IEEE Transactions on Information Theory and Journal of Lightwave Technology. Recent work (2023-2025) demonstrates continued innovation in integer-forcing techniques, quaternionic Minkowski reduction, and 4D constellation optimization. VDE Award for Outstanding Master Thesis (2013) Stern has taught multiple courses at Ulm University including Communications Engineering lab courses, Multiuser Communications and MIMO Systems exercises, and Signale und Systeme tutorials between 2013-2017. His teaching experience complements his research in practical implementation of advanced communication techniques.

• Biomedical Circuits and Systems
• Machine Learning Applications
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Amine Bermak is a Professor at the Department of Electrical and Electronic Engineering, Hong Kong University of Science and Technology. His research focuses on biomedical circuits, machine learning applications, and hardware security. Key contributions in CMOS sensors for bioluminescence and bacterial monitoring Pioneering work in IoT security and physical unclonable functions (PUFs) Developed edge computing frameworks for healthcare and industrial applications Significant publications in IEEE Transactions on Biomedical Circuits and Systems His recent articles highlight advancements in deepfake detection, energy-efficient ADCs, and wearable strain sensors. Collaborations span institutions in Hong Kong, Qatar, and Japan.

• Power Electronics
• Semiconductor Devices
• Analog Circuit Design
• +۳ مورد دیگر

Prof. Dr. Ertugrul Sönmez serves as Professor in the Faculty of Engineering at Reutlingen University, leading the Semiconductor Circuit Technology Lab. His research focuses on power electronics innovation through semiconductor circuit design, analog systems, and advanced converter topologies. Contact details include email ertugrul.soenmez@reutlingen-university.de and office location in Building 4, Room 213. His work centers on power conversion systems with emphasis on GaN-based technologies , wireless power transfer , and active damping techniques . Key interests include delta-sigma modulation for multilevel converters, dV/dt filter design for motor drives, and high-frequency operation using wide-bandgap semiconductors. Research addresses critical industry challenges in electric vehicle charging, renewable energy integration, and industrial motor control systems. Recent publications (2022-2024) reveal strong focus on modular converter architectures and stability enhancement techniques. His work bridges theoretical control concepts with practical implementation, frequently appearing in top industry conferences like PCIM Europe. Collaborative projects with colleagues such as Gernot Schullerus demonstrate cross-disciplinary approaches to power electronics challenges. Through the Semiconductor Circuit Technology Lab, Prof. Sönmez provides hands-on research opportunities in semiconductor characterization and circuit synthesis. The lab supports student projects including bachelor's/master's theses and industry-collaborative initiatives like ArduSmartPilot. His consistent publication output indicates active supervision of graduate research in power electronics design and implementation.