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Sani NassifView profile

Research Fellow

• Machine Learning
• Energy Analysis
• Integrated Circuits
• +4 more

Sani Nassif is a Research Fellow at the Technical University of Munich (TUM) under the Rudolf Diesel Industry Fellowship, hosted by Professor Ulf Schlichtmann. With 28 years of experience at Bell Labs and IBM Research, he has led teams in integrated circuit modeling, simulation, statistical analysis, and optimization. Research Interests: His work bridges integrated circuit technology with cross-disciplinary applications in medicine. Key areas include variability analysis in semiconductor manufacturing, low-power circuit design, and reliability engineering for nano-scale systems. He focuses on applying machine learning and statistical methods to solve challenges in energy-efficient computing and biomedical systems. Selected Publications: His research spans circuit variability trends, leakage current modeling, and reliability frameworks for nano-era systems. Work includes foundational studies on SRAM failure analysis and CMOS scaling limitations. Scientific Awards: He is recognized as an IEEE Fellow IBM Master Inventor (75 patents) Rudolf Diesel Industry Fellow

Marc ReichenbachView profile

Professor

• Integrated Circuits
• Embedded Systems
• VLSI Design
• +7 more

Prof. Dr.-Ing. Marc Reichenbach serves as the Chair of Integrated Systems at the Institute for Applied Microelectronics and Data Technology at the University of Rostock. His office is located at Albert-Einstein-Straße 26, 18059 Rostock, Room 102 (1st floor), with contact information including telephone (0381) 498 7270 and email marc.reichenbach@uni-rostock.de. Professor Reichenbach's research focuses on the intersection of hardware design and artificial intelligence, with particular expertise in memory technologies and computing architectures. His work spans several key areas: Development of specialized computer architectures for deep learning applications Advanced VLSI design and CPU architecture Emerging memory technologies, particularly RRAM (Resistive Random-Access Memory) FPGA-based acceleration systems Hardware implementations for neural networks and AI applications Analysis of Professor Reichenbach's recent publications (2023-2025) reveals a strong focus on memory computing technologies, particularly RRAM-based systems. His work demonstrates expertise across multiple dimensions of computer architecture including ASIC design, FPGA acceleration, and novel memory systems. The publications show a clear trajectory toward implementing AI and machine learning capabilities directly in hardware, with applications ranging from edge computing to satellite systems. A significant portion of his recent work addresses the challenges of implementing neural networks using emerging memory technologies, focusing on efficiency, reliability, and performance optimization. Professor Reichenbach teaches several advanced courses including: Computer architectures for deep learning applications Project seminar Embedded Systems Advanced VLSI Design (Advanced CPU Design) His research group appears to be actively engaged in several cutting-edge projects related to hardware acceleration for AI applications, memory computing, and embedded systems design. The group collaborates on projects involving digital twins for hardware systems, real-time operating systems for heterogeneous architectures, and specialized computing systems for various applications from medical devices to drone technology.

Joan Daniel Prades GarciaView profile

Professor

• Nanotechnology
• Quantum Systems
• Sensors
• +4 more

Joan Daniel Prades Garcia is a Full Professor (W3) at the Institute of Semiconductor Technology, Faculty of Electrical Engineering, Information Technology, Physics, Technische Universität Braunschweig, Germany. He previously held a Full Professorship (2019–2024) and an Associate Professorship (2014–2019) at Universitat de Barcelona, Spain, and founded two start-ups, including ColorSensing SL (since 2018). His research bridges semiconductor technology and quantum metrology, focusing on ubiquitous sensor systems using nanowires and quantum effects for environmental monitoring. Education: PhD in Electronic Engineering (2009, Universitat de Barcelona); Master in University Teaching (2011); Master in Nanoscience and Nanotechnology (2007) His research exploits quantum-scale changes in nanoscale materials under environmental stimuli to develop scalable, transportable sensors. Key projects include ultra-low-power gas sensors, self-heated nanowires, and GaN micro-LED integration for distributed sensing networks. His work has been recognized with prestigious awards, including the Alexander von Humboldt Professorship (2024), ERC Starting Grant ('BetterSense', 2014), ERC Proof-of-Concept grants ('GasApp', 2016; 'Stick-n-Sense', 2020), ICREA Academia Award (2018), and Eurosensors Fellow (2017). He has coordinated over 47 projects and acquired €11.1 million in funding, including €4.8 million internationally. He leads a team at TU Braunschweig, collaborating on semiconductor quantum systems and nanoscale metrology to address air pollution, a critical global health challenge. His scientific record includes over 115 refereed journal articles, 9 patents (2 licensed), and an h-index of 42.

• Semiconductor Device Modeling
• Boltzmann Transport Equation
• TCAD (Technology Computer-Aided Design)
• +11 more

Christoph Jungemann is a Professor at RWTH Aachen University in the Faculty of Electrical Engineering and Information Technology, where he serves as Vice Dean and heads the Institute for Theoretical Electrical Engineering. He obtained his diploma and doctorate in electrical engineering from RWTH Aachen and completed habilitations at the University of Bremen and TU Braunschweig. His career includes academic positions at Fujitsu in Japan, the University of Bremen, Stanford University, TU Braunschweig, and the University of the Federal Armed Forces in Munich. His research focuses on semiconductor device modeling, particularly using the Boltzmann transport equation, noise simulation, SiGe HBTs, THz devices, ReRAM, and cryogenic electronics. He employs deterministic and Monte Carlo methods for advanced TCAD applications. His recent work explores high-harmonic generation in doped silicon, plasma waves, and compact modeling of III-V devices. His publication trend shows sustained leadership in computational electronics, with emphasis on numerical stability, multi-scale modeling, and emerging device technologies for quantum and high-frequency applications. IEEE Paul Rappaport Award (2006) IEEE Fellow (2019) RWTH Teaching Award (2017) He has advised numerous researchers and co-authored extensively with colleagues in device physics and modeling. He has led major projects such as DOTSEVEN and edited special issues on next-generation TCAD. He has also served as co-editor of IEEE Transactions on Electron Devices and contributed to accreditation in engineering education through ASIIN. He leads a research group focused on theoretical electrical engineering, advancing simulation methodologies for next-generation semiconductor devices.

• Integrated Systems
• High-Frequency Sensors
• Medical Technology
• +3 more

Lasse Cordes is a Researcher at the Ruhr University Bochum within the Faculty of Electrical Engineering and Information Technology, Department of Integrated Systems. His work focuses on advanced sensor design and semiconductor technologies. Research interests include: High-frequency sensor systems BiCMOS integrated circuit applications Medical technology integration Semiconductor device optimization Recent publications demonstrate expertise in microwave engineering and power detection technologies. He is based at the Integrated Systems department, collaborating on projects like KI-ROJAL and PluTO+.

• Memristive Devices
• Printed Electronics
• Non-Volatile Memory
• +3 more

Dr. Hongrong Hu is a Research Fellow at the Institute of Nanotechnology, Karlsruhe Institute of Technology (KIT), Germany, affiliated with the Electronic Devices and Systems research unit. Her work focuses on advancing printed memristive technologies for next-generation memory applications. Her research expertise spans: Memristive Devices and Resistive Random-Access Memory (ReRAM) Printed Electronics Fabrication (Inkjet/Laser Printing) Non-Volatile Memory Systems Metal-Oxide Semiconductor Materials High-Entropy Compounds for Memory Neuromorphic Computing Hardware Analysis of her 2021-2025 publications reveals a strategic progression from fundamental device characterization (e.g., noise properties in printed transistors) toward sophisticated material engineering (high-entropy Prussian Blue analogs, metal-organic frameworks) and neuromorphic applications. Her work consistently bridges materials science, electrical engineering, and nanofabrication to solve scalability challenges in printed memory devices. Scientific recognition: No awards or fellowships documented in available sources Dr. Hu's academic mentoring and grant activities are not publicly detailed, though her collaborative publications suggest active participation in KIT's research ecosystem. She contributes to the Electronic Devices and Systems unit's mission of developing innovative electronic solutions through printed and flexible technologies for real-world applications.

• Phase Change Memory
• Neuromorphic Computing
• Very Large Scale Integration
• +4 more

Houpeng Chen is a Research Professor at the Chinese Academy of Sciences, specifically affiliated with the School of Microsystem and Information Technology in the Department of Microelectronics. With over two decades of research experience since the early 2000s, Chen has established himself as a leading expert in memory systems and circuit design, particularly in the areas of Phase Change Memory and neuromorphic computing. Chen's research primarily focuses on advanced memory technologies, with particular emphasis on Phase Change Memory (PCM) systems, neuromorphic computing architectures, and analog circuit design for memory applications. His work spans from fundamental circuit design for memory systems to advanced computing architectures that leverage novel memory technologies. A significant portion of his recent work explores in-memory computing paradigms and brain-inspired computing systems, demonstrating a strategic shift toward next-generation computing architectures that address the limitations of traditional von Neumann systems. Analysis of Chen's publication record shows a clear evolution from traditional circuit design toward more innovative memory-based computing architectures. His recent work demonstrates strong expertise in 3D cross-point memory systems, in-memory computing, and neuromorphic hardware implementations. The research shows consistent quality with publications in top-tier IEEE journals and conferences, indicating strong recognition within the semiconductor and memory research community. As evidenced by the authorship patterns in his publications, Chen has successfully mentored numerous graduate students and junior researchers who have gone on to become first authors on significant publications. His collaborative network includes extensive work with Zhitang Song, Qian Wang, and Xi Li, suggesting a well-established research group with strong internal collaboration.

• Analog and Mixed-Signal Circuit Design
• RF Energy Harvesting
• Neuromorphic Hardware
• +5 more

Pengcheng Xu is a Researcher at the Technical University of Munich's Chair of Circuit Design under Prof. Ralf Brederlow, specializing in analog and mixed-signal circuit design. His work spans energy harvesting systems, neuromorphic hardware, and wireless sensor technologies, with strong industry connections including prior roles at Huawei and Fraunhofer EMFT. Education: Bachelor of Physics, Shanghai Normal University (2013) Master of Integrated Circuit Engineering, Tongji University (2016) Ph.D. in Electrical Engineering, Université catholique de Louvain (2021) Exchange Student, University of Erlangen-Nuremberg (2015) Xu's research focuses on practical applications of circuit design including RF energy harvesting for battery-less IoT sensors, neuromorphic accelerators for edge computing, and precision analog systems for electrochemical/ mechanical stress sensing. His work bridges theoretical circuit innovation with real-world implementation in semiconductor processes from 28nm FDSOI to emerging memory technologies. His publications demonstrate consistent high-impact contributions to IEEE journals and conferences including JSSC, ISSCC, and ESSCIRC, with particular expertise in impedance-aware rectifier design and low-power circuit architectures. Xu holds a pending European/US patent for RF energy harvesting systems. Awards and Recognition: Shanghai Outstanding Graduate Award (2013, 2016) Chinese Government Award for Outstanding Self-Funded Students Abroad (2020) Chinese National Scholarship (2012, 2014, 2015) Meritorious Winner, Mathematical Contest in Modeling (2013) Xu actively contributes to the academic community as IEEE Young Professionals Germany Chair (2023-2024), IEEE Design Automation Conference TPC member (2022-2024), and reviewer for multiple IEEE journals. He supervises student theses in analog circuit design and neuromorphic hardware through TUM's Chair of Circuit Design, which maintains strong industry partnerships with semiconductor companies.

Guillermo Payá VayáView profile

Professor

• Embedded Systems
• Processor Architecture
• FPGA Design
• +5 more

Prof. Dr.-Ing. Guillermo Payá Vayá leads the Chair for Chip Design for Embedded Computing at Technical University of Braunschweig's Faculty of Electrical Engineering, Information Technology, and Physics. His research focuses on processor architecture design, FPGA/ASIC implementations, and optimization techniques for embedded systems, particularly in high-performance, low-power, and radiation-hardened computing domains. Primary research interests include: Application-Specific Instruction Set Processors (ASIPs) and compiler co-design Radiation effects characterization and fault-tolerant hardware Ultra-low-power processor architectures for embedded AI Hardware acceleration of neural networks and computer vision algorithms Memory subsystem optimization and parallel computing techniques Recent publications demonstrate strong emphasis on radiation-hardened electronics (35% of recent works), AI accelerator design (27%), and ultra-low-power systems (20%), with growing interest in biomedical applications. Experimental validation through FPGA prototyping and semiconductor testing is a consistent methodology across research domains. Leads research team investigating: Radiation-tolerant FPGA architectures (Trumann, Weide-Zaage) Vector processor optimization (Gesper, Thieu) Nano-scale controller design (Weißbrich) AI-hardware co-design (Kautz, Beyer)

• Educational Technology
• Collaborative Learning
• Computer-Supported Learning
• +3 more

Markus Kuhn is a researcher at the University of Cambridge with a diverse academic career spanning over two decades, evidenced by publications from 2003 to 2023. His work bridges educational technology, computer science, and autonomous systems, demonstrating significant interdisciplinary reach across multiple domains. Dr. Kuhn's research has evolved through distinct phases. Initially focused on educational technology (2003-2007), he published extensively on classroom scenarios, collaborative learning, and media integration. His work then broadened to include physics computation (2008) and process support for inquiry learning (2010). More recently (2016-2023), his research has shifted toward autonomous systems, with publications on self-localization technologies and map generation for autonomous vehicles. This publication trajectory reveals a researcher who has successfully adapted his expertise from educational applications to more technical domains while maintaining connections to his foundational work in learning systems. His research demonstrates consistent innovation in applying computational approaches to solve practical problems across different contexts. Dr. Kuhn has maintained long-term collaborations with researchers including Heinz Ulrich Hoppe, Andreas Harrer, and Andreas Lingnau, indicating strong interdisciplinary networks. His work has been published in diverse venues ranging from IEEE Access and Microelectronics Reliability to Research and Practice in Technology Enhanced Learning and International Conferences on Computer-Supported Collaborative Learning.

• Materials Science
• Nanotechnology
• Thermoelectrics
• +7 more

Dr. Yolita Eggeler is an Assistant Professor in the Department of Physics at the Karlsruhe Institute of Technology (KIT), leading the LEM (Laboratory for Experimental Materials) research group. Her work focuses on advanced materials science, nanotechnology, and additive manufacturing, with a particular emphasis on laser-based fabrication techniques, thermoelectric materials, and micro/nanostructural characterization. She is affiliated with the KIT Physics Department and collaborates on projects involving energy harvesting, semiconductor devices, and high-temperature alloy behavior. Research interests include: Laser microprinting of semiconductors and metals Thermoelectric generator design and optimization Nanoparticle synthesis and applications High-temperature material degradation and creep mechanisms Recent publications highlight innovations in photothermal laser printing of crystalline materials, novel thermoelectric modules, and core-shell nanocrystal engineering. Her work bridges fundamental materials science with applied technologies like flexible electronics and energy conversion systems. Key collaborations involve advanced TEM analysis for microstructural studies and correlative microscopy techniques. She is actively developing new methodologies for in-situ pyrolysis of 3D-printed materials and exploring AI-driven materials discovery through concept graph analysis. Laboratory facilities include state-of-the-art laser printing systems, electron microscopy setups, and thermal characterization equipment. Her team focuses on translating lab-scale innovations into scalable manufacturing processes for next-generation electronic and energy systems.

Veit Dominik KunzView profile

Professor

• Electrical Engineering
• Renewable Energy
• Wind Energy
• +4 more

Prof. Veit Dominik Kunz is a Professor of Electrical Engineering and Renewable Energy at the Department of Process Engineering, Hamburg University of Applied Sciences. His academic role includes teaching and research in advanced electrical systems, power electronics, and renewable energy technologies. He is affiliated with the Faculty of Engineering and Computer Science and leads research projects such as FLEDERWIND (focusing on bat detection in wind parks) and Drones4Bats (wildlife impact assessment). His expertise spans semiconductor device design, nanotechnology, and strategic product development. Research interests include optimizing renewable energy systems, mitigating environmental impacts of wind energy, and advancing semiconductor technologies for high-performance electronics. His work bridges academic research with practical applications, particularly in energy management and sustainable technologies. Publications highlight contributions to vertical MOSFET design, renewable energy systems, and product development strategies. He is also involved in academic governance as head of the examination committee for his department.

Tianran MaView profile

Researcher

• Semiconductor Technology
• Electrical Engineering
• Physics
• +1 more

Tianran Ma serves as a Researcher at the Institute of Semiconductor Technology within the Faculty of Electrical Engineering, Information Technology, Physics at Braunschweig University of Technology. The institute operates from Langer Kamp 6a/b, Room 226, Brunswick, Germany, focusing on semiconductor device development and materials research. Research spans semiconductor technology fundamentals, electrical engineering applications, and cross-disciplinary physics/information technology integration. Key activities include semiconductor fabrication, device characterization, and electronic/photonics systems innovation, directly supporting the institute's mission in advancing microelectronics. Contact accessibility: Email: tianran.ma@tu-braunschweig.de Phone: 0531 391-65330 No scientific awards or fellowship recognitions were documented in the source material. Advisory roles and grant management responsibilities were not specified, though collaborative research within the institute's framework is implied through team listings. The Institute of Semiconductor Technology constitutes the primary research ecosystem, operating under the university's LENA building infrastructure with dedicated laboratory facilities for semiconductor processing and testing.

Dennis HohlfeldView profile

Professor

• Silicon-based microsystem technology
• Energy-autonomous systems
• Energy Harvesting
• +3 more

Prof. Dr.-Ing. Dennis Hohlfeld serves as Professor and Chair of Micro- and Nanotechnology of Electronic Systems at the University of Rostock's Institute of Device Systems and Circuit Technology. He holds key administrative roles as Study Advisor and Chairman of the Computational Science and Engineering (CSE) Examination Board, while actively contributing as a reviewer for research funding organizations and scientific publishers. His research spans five core domains: Silicon-based microsystem technology focusing on nanoscale material behavior for high-performance electronics Energy-autonomous systems leveraging environmental energy sources through harvesting techniques Energy-efficient circuit design for miniaturized applications Microoptics development for photonic integration Modeling and simulation techniques enabling system-level analysis of complex multiphysics phenomena Analysis of his 15 most recent publications reveals a dominant trend toward biomedical energy solutions, particularly thermoelectric generators for implantable devices. His work demonstrates strong interdisciplinary integration across electrical engineering, materials science, and neuroscience, with increasing emphasis on model order reduction for efficient simulation of MEMS devices and optogenetic applications. The publications consistently address miniaturization challenges while maintaining system-level performance. No scientific awards were documented in the provided materials. As Study Advisor and Examination Board Chairman for CSE, Prof. Hohlfeld oversees academic progression for computational science students. His research leadership encompasses: Technical Domains Energy harvesting systems for medical implants Photonic integration in microelectronics Multiphysics modeling frameworks Application Areas Autonomous environmental sensors Neuroprosthetic interfaces Power-efficient microsystems The Institute of Device Systems and Circuit Technology houses specialized laboratories for microsystem fabrication, energy harvesting characterization, and optical circuit development, supporting his research in silicon-based nanotechnology and energy-autonomous systems.

• Electrical Engineering
• Information Technology
• Power Systems
• +3 more

Frank Hecht serves in the Dean's Office of the Faculty of Electrical Engineering and Information Technology at RWTH Aachen University, providing administrative leadership for academic and research operations within this major engineering faculty. His research spans core domains of Electrical Engineering and Information Technology, with emphasis on Power Systems for sustainable energy infrastructure, Telecommunications for data networks, Microelectronics in semiconductor design, and Control Systems for automation. These fields align with the faculty's mission to advance technological innovation in industrial and societal applications.