Find Academic Supervisors

• Asynchronous Circuits
• Formal Verification
• Computer-Aided Design (CAD)
• +10 more

Michael Theobald is a researcher at D. E. Shaw Research, focusing on the design and verification of specialized supercomputers for protein simulations. He has previously held postdoctoral and academic positions at Carnegie Mellon University (CMU) and Columbia University. Education: Ph.D. in Computer Science from Columbia University (2002), Postdoctoral Fellow at CMU (2002-2004), and Diplom in Computer Science from Johann Wolfgang Goethe-Universitaet (1994). His research interests span formal verification of software and hardware systems, asynchronous (“clock-less”) circuits, and efficient algorithms for combinatorial optimization. He has contributed to advancements in BDD and SAT techniques, logic synthesis, and hybrid systems verification, with applications in systems biology and robotics. Michael's publications emphasize formal methods, including model checking, abstraction refinement, and SAT-based algorithms applied to hybrid and asynchronous systems. These works align with his broader expertise in embedded systems and computer-aided design.

• Electronic Design Automation (EDA)
• RISC-V Architecture
• TinyML (Tiny Machine Learning)
• +3 more

Philipp van Kempen is a researcher at the Chair of Design Automation (Prof. Schlichtmann) at the Technical University of Munich. His work focuses on electronic design automation, specifically targeting RISC-V architecture, TinyML optimization, and LLVM compiler infrastructure for custom hardware accelerators. Key Research Areas: RISC-V ISA extensions, autovectorization, neural network accelerators, and compiler toolchain automation. Collaborations: Works with Daniel Mueller-Gritschneder, Ulf Schlichtmann, and Jefferson Parker Jones. His recent publications highlight contributions to benchmarking TinyML CNN kernels on RISC-V vector hardware, developing semi-automated LLVM support for ISA extensions, and optimizing TinyML inference through frameworks like MLonMCU and muRISCV-NN.

Rolf DrechslerView profile

Professor

• Computer Science
• Formal Verification
• Circuit Design
• +3 more

Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture at the University of Bremen since 2001, with additional role as Director of the Cyber-Physical Systems Group at DFKI Bremen since 2011. He holds a Dr. phil. nat. in computer science from Johann Wolfgang Goethe University Frankfurt and has held academic positions at Albert-Ludwigs University Freiburg and Siemens AG. Education: Diploma and Dr. phil. nat. in Computer Science (Johann Wolfgang Goethe University Frankfurt, 1992-1995) Previous Roles: Albert-Ludwigs University Freiburg (1995-2000), Siemens AG Munich (2000-2001) His research focuses on formal verification , circuit/system design , and data structures for hardware validation . He has pioneered work on polynomial verification methods, BDD-based synthesis, and quantum computing verification frameworks. Recent publications analyze memristor-based in-memory computing, RISC-V security, and LLM-assisted hardware validation. Key awards include ACM Fellow IEEE Fellow Berninghausen Teaching Award (2018) Multiple best paper awards at ICCAD, DATE, DAC, and DDECS He serves as Associate Editor in journals like IEEE Transactions on CAD and ACM Journal on Emerging Technologies. He co-founded the Graduate School of Embedded Systems and Data Science Center at University of Bremen.

• Computer Architecture
• Deep Learning Accelerators
• Heterogeneous Computing
• +4 more

Pedro Petersen Moura Trancoso is a Full Professor at the Department of Computer Engineering , Chalmers University of Technology, Sweden. His research focuses on deep learning accelerators , heterogeneous computing , energy-efficient architectures , and memory system optimization for IoT and edge devices. Key projects: AutoPIM (autonomous vehicle accelerators), VEDLIoT (efficient AIoT), eProcessor (European processor ecosystem), PRIME (PIM systems) Collaborations: European Commission, Swedish Research Council, Swedish Foundation for Strategic Research Research Trends : Hybrid CNN/GPU/FPGA Acceleration On-Chip/Scratchpad Memory Optimization Adaptive Resource Allocation for Energy Efficiency Hardware-Software Co-Design for AIoT Publications demonstrate leadership in deep learning hardware , heterogeneous memory systems , and edge computing architectures . Key journals: IEEE ISPASS, ACM Computing Frontiers, DATE Conference.

Patrick LESERFView profile

Associate Professor

• Embedded Systems Engineering
• Model-Based Systems Engineering (MBSE)
• Automotive Software Architecture
• +4 more

Patrick LESERF is an Associate Professor at ESTACA, a French engineering school specializing in transport systems, where he serves as a Teacher-researcher in ESTACA'Lab. Since joining in 2005, he has founded the embedded systems laboratory, developed academic programs including a specialized master's degree in Embedded Lighting Systems (with IOGS, Renault, and PSA), and led research collaborations with CEA-LIST on transport systems reliability using model-based approaches. His research centers on Model-Based Systems Engineering (MBSE) for embedded automotive systems, with expertise in SysML modeling, safety-security co-optimization, and AUTOSAR methodology. Key contributions include architecture optimization for critical systems, real-time communication networks (CAN/LIN/FlexRay), and embedded OS design. Recent work expands into intelligent transportation systems and electric vehicle powertrain optimization. Analysis of his 2023-2024 publications reveals a strategic shift toward AI-integrated solutions: neural architecture search for efficient deep learning models, predictive analytics for urban traffic optimization using Eclipse MOSAIC, and multi-objective optimization of battery/motor systems in electric vehicles. This evolution demonstrates integration of traditional embedded systems engineering with data-driven approaches. Scientific Awards: No major awards documented in source materials. Advising and Grants: Co-supervises PhD candidate Léo Pouy on MBSE for autonomous decision-making systems. Led the European Matelo project (statistical testing for embedded software) during industrial tenure and established ESTACA's joint research team with CEA-LIST. Directs curriculum development for embedded systems education across multiple specialized master's tracks. Labs and Teams: Founded ESTACA'Lab's embedded systems research group in 2005, scaling it to four teacher-researchers. The lab focuses on model engineering, transport communication networks, and software architecture optimization, supported by a 350-hour teaching program covering embedded networks, OS, and microcontrollers. Current activities include steer-by-wire systems and IoV applications.

• Deep Learning
• Computer Hardware
• Biomedical Signal Processing
• +3 more

Zhenya Zang is a researcher specializing in deep learning applications for biomedical optics and hardware-accelerated signal processing, with recent focus on diffuse correlation spectroscopy for medical diagnostics. Education PhD completed January 2025 with thesis: "Towards highly efficient algorithms and hardware architecture design for single-photon signal processing" Research Focus Zang's work bridges computer science and biomedical engineering through: Development of back-propagation-free neural network algorithms Hardware-embedded data processors for real-time imaging Optimization of deep learning architectures for optical diagnostics Extreme learning machine implementations in medical hardware Publication Trends 2025 research demonstrates a clear trajectory toward deployable medical AI systems, emphasizing hardware-software co-design to solve latency challenges in blood flow monitoring. Key innovations include convolutional neural network adaptations for diode array sensors and accuracy-focused detection frameworks. Scientific Awards No awards documented in available records. Grants & Collaboration Researcher on "Smart Hardware-embedded Data Processors for Rapid 3D Ranging & Imaging" (2019-2022), a studentship project led by Principal Investigator D. Li Current work shows no student supervision activity. Research Infrastructure Publications indicate work within embedded hardware development environments for medical imaging, though specific laboratory affiliations remain undocumented.

Thomas WiemannView profile

Professor

• Autonomous Robotics
• 3D Mapping
• SLAM
• +7 more

Thomas Wiemann is a temporary Professor for Autonomous Robotics at Osnabrück University and a researcher at the German Research Center for Artificial Intelligence (DFKI) , group Kooperative und Autonome Systeme . He has been active since 2007, focusing on 3D mapping, SLAM, and semantic interpretation of sensor data for robotics. He received his Dr. rer. nat. in 2013 and his habilitation in 2020. His work is widely recognized, with awards such as the Karman Innovation Award (2007) and the Intevation Free Software Award (2014). Education: Habilitation in Computer Science, Osnabrück University (2020) Doctorate (Dr. rer. nat.) in Computer Science, Osnabrück University (2013) M.Sc. in Physics and Computer Science, Osnabrück University (2007) B.Sc. in Physics and Computer Science, Osnabrück University (2005) Research Focus: Thomas Wiemann's research is centered on autonomous robotics , particularly in 3D mapping , SLAM , and semantic environment understanding . His work includes the automatic generation of polygonal maps from point cloud data, large-scale 3D reconstruction, hyperspectral data integration, and hardware-accelerated SLAM systems using FPGAs and GPUs. He has developed open-source tools like the Las Vegas Reconstruction Toolkit (LVR) and contributed to ROS packages for 3D mapping and navigation. Scientific Awards: Karman Innovation Award (2007) for his master’s thesis Intevation Free Software Award (2014) for his contributions to open-source software Advising & Grants: He has supervised over 60 bachelor’s and master’s theses, primarily in the areas of 3D mapping, SLAM, and robotics systems. His projects include SOILAssist (2019–2021), focusing on sustainable agriculture using robotics, and 3DinOS (2016–2017) for 3D documentation of historical buildings. He has also worked on DFG-funded projects like RoboRithmics . Labs & Teams: He is part of the Knowledge Based Systems Group at Osnabrück University and collaborates with the DFKI Robotics Innovation Center . His lab focuses on advanced 3D perception, semantic mapping, and energy-efficient robotic systems.

Dinesh Acharya UView profile

Professor

• Machine Learning
• Data Mining
• Image Processing
• +4 more

Dinesh Acharya U serves as a Professor in the Department of Computer Science and Engineering at Manipal Institute of Technology, Manipal University. His academic leadership spans both foundational computer engineering and interdisciplinary medical applications, with research output consistently growing since 2006. Current affiliations include active roles at the School of Computer Engineering with verified ORCID profile (0000-0002-0304-4725) and institutional webpage. Research interests prominently feature Machine Learning (68% fingerprint weight), Data Mining (40%), and Medical Informatics applications. His work bridges computer science with healthcare challenges, particularly in neonatal sepsis detection, diabetic complications, and low-resource language processing. The research fingerprint shows strong emphasis on prediction (52%), algorithms (53%), and India -specific healthcare contexts (40%). Publication trends reveal accelerating output since 2018, with 12 papers in 2022 and continued productivity through 2025. Recent work demonstrates interdisciplinary convergence, particularly in Medical AI (neonatal sepsis, diabetic kidney disease) Natural language processing for low-resource languages Transformer-based architectures across domains Notable patterns include increasing clinical collaborations and emphasis on practical implementation tools. Professional recognition includes an h-index of 13 with 596 citations across 71 research outputs. Key distinctions: Scopus profile verification ORCID registration Multi-institutional collaborations evident in co-authorship Academic supervision and grant activity cannot be confirmed from available data, though 15+ recent publications suggest active research teams. Current projects appear focused on Medical diagnostic tool development Low-resource language technology Clinical decision support systems with evident laboratory infrastructure supporting computational healthcare research.

Arijit RaychowdhuryView profile

Professor

• Low Power Digital Circuits
• Compute-in-Memory (CIM)
• Adaptive Clocking and Power Management
• +7 more

Arijit Raychowdhury is a Professor and the Steve W. Chaddick School Chair at Georgia Tech's School of Electrical and Computer Engineering (ECE). He leads the Center for the Co-Design of Cognitive Systems (CoCoSys) and directs the DoD-sponsored SCALE Workforce Development Program in SoC Design. Current affiliations: Georgia Tech (ECE), Integrated Circuits and Systems Research Lab Prior affiliations: Intel Corporation (6 years), Texas Instruments (1.5 years) Research interests focus on low-power circuits, compute-in-memory (CIM) systems, cryogenic electronics, and neuro-symbolic AI. His work bridges circuit design with emerging device technologies and machine learning applications. Scientific contributions include: Over 250 publications and 27 patents Leadership in top conferences (ISSCC, VLSI Symposium, DAC, CICC) Pioneering 3D Gaussian Splatting acceleration, adaptive echo-cancellation networks, and CIM architectures Advancing GaN-based power converters and cryogenic CMOS Awards : IEEE Fellow (2022) SRC Technical Excellence Award (2021) Qualcomm Faculty Award (2021, 2020) IEEE/ACM Innovator under 40 (2018) Intel Young Faculty Award (2015) Dimitris N. Chorafas Award (2007) Leadership : • Director of CoCoSys Center • Site Director for SCALE Program • Distinguished Lecturer, IEEE Solid-State Circuits Society

• Post-Quantum Cryptography
• Lattice-Based Cryptography
• Hardware/Software Co-Design
• +10 more

Tim Fritzmann is a researcher at the Department of Security in Information Technology (Technische Universität München). His work focuses on post-quantum cryptography, lattice-based algorithms, and secure hardware/software co-design for constrained environments like automotive systems and embedded devices. Post-Quantum Cryptography Lattice-Based Cryptography Hardware/Software Co-Design Error-Correcting Codes RISC-V Architecture ASIC Design His recent publications (2018–2022) highlight advancements in fault attacks, side-channel countermeasures, and efficient implementations of lattice-based protocols for IoT, automotive systems, and FPGA-SoC platforms. Key themes include parameter optimization for decryption reliability, masked accelerators, and instruction-set extensions for quantum-resistant algorithms. Research projects involve collaborations with institutions like the University of Leuven and TU München, emphasizing post-quantum security integration into real-world hardware architectures. No explicit awards or student advisement details are listed publicly.

• Electronic Design Automation
• Computer Architecture
• Performance Simulation
• +5 more

Conrad Foik is a researcher at the Chair of Electronic Design Automation at the Technical University of Munich , working under Prof. Dr.-Ing. Ulf Schlichtmann. His research focuses span analog and digital design automation, processor modeling, and performance simulation. University: Technical University of Munich Department: Electronic Design Automation Research Areas: Processor Description Languages, Software Performance Simulation, Hardware-Software Co-Design His recent work addresses flexible generation of performance simulators, mapping instruction set models to hardware, and RISC-V simulation environments. Publications highlight tools like CorePerfDSL for accurate performance modeling.

Patricia DesgreysView profile

Professor

• Analog and Mixed Signal (AMS) Circuit Design
• Cognitive Radio Systems
• Internet of Things (IoT)
• +7 more

Patricia Desgreys is a full professor at Institut Polytechnique de Paris , where she leads the Communication Circuits and Systems (C2S) research team within the Laboratory of Information Processing and Communication (LTCI) . Her work spans analog and mixed-signal (AMS) circuit design, cognitive radio systems, and digitally enhanced mixed-signal architectures for IoT and cyber-physical systems. Agrégation in Applied Physics, École Normale Supérieure de Cachan M.Sc. and Ph.D. in Microelectronics, University of Bordeaux (1995-1999) Her research focuses on AMS circuit design from transistor to architectural levels, including software-defined radio , cognitive radio , and neural-inspired analog-to-feature converters . She has contributed to digital predistortion techniques for power amplifiers, compressive sampling for astrophysical signals, and leadless pacemaker communication channels . Her 150+ publications highlight advancements in wireless systems, biomedical sensors, and 5G infrastructure. Recent work (2024) explores AI-driven analog design and 75 years of circuits innovation in IEEE Transactions. She has graduated 16 PhD students and co-authored the book Digitally Enhanced Mixed Signal Systems (IET, 2019). Her leadership includes Technical Program Chair roles at IEEE PRIME (2019), ICECS (2016), and NEWCAS (2012-2013), plus editorial work for IEEE TCAS-II special issues (2018-2019). She directs the ICS Master’s program (Institut Polytechnique de Paris/Paris-Saclay University) and teaches advanced electronics at SJTU-ParisTech in Shanghai . Her patents include signal sampling circuits and power amplifier linearization techniques.

Ulrich KühneView profile

Lecturer

• Embedded Systems Security
• Formal Methods in Security
• Hardware and Software Attacks
• +3 more

Ulrich Kühne is a Lecturer at Télécom Paris , affiliated with the Secure and Safe Hardware (SSH) team and the Information Processing and Communication Laboratory (LTCI) . His research focuses on embedded systems security and formal methods for security guarantees. Research Interests: Embedded systems security, formal verification of protection schemes, and mitigation of hardware/software attacks. Publications: His work spans moving target defense for connected cars, side-channel attack mitigation in neural networks, and hardware-assisted security mechanisms. Labs & Teams: Active in LTCI and SSH, focusing on hardware-software co-design for security.

• Real-time computer resource management systems
• Heterogeneous memory systems
• Programming models for heterogeneous computing systems
• +2 more

Lazaros Papadopoulos serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Democritus University of Thrace since May 2024, focusing on computational resource management for embedded and high-performance systems. His work bridges hardware-software co-design with energy-efficient computing paradigms. His academic credentials include: Bachelor's in Electrical and Computer Engineering from Democritus University of Thrace (2005) Master's degree from the same institution (2008) PhD from the National Technical University of Athens (2016) Research centers on optimizing computing infrastructure through real-time resource management, heterogeneous memory architectures, and AI workload acceleration. His investigations target energy-performance tradeoffs in GPU systems, persistent memory integration, and edge-device neural network deployment, with direct applications in sustainable computing and high-performance data processing. Publication analysis (2018-2022) reveals consistent focus on heterogeneous system optimization, particularly energy-aware GPU acceleration frameworks, memory management for DRAM/NVM hybrids, and efficient CNN implementations for edge devices. Key thematic threads include sustainable computing practices, hardware-aware AI deployment, and memory hierarchy innovations. Scientific recognition includes: Two Best Paper Awards Research leadership spans major EU initiatives: Work Package Coordinator for LAGO (Horizon Europe, 2022-2024) and PRAETORIAN (H2020, 2022-2024); Technical Coordinator for EXA2PRO (H2020, 2018-2021); and Work Package Coordinator roles in SDK4ED (H2020, 2018-2020) and EXCESS (H2020, 2013-2016). These projects address embedded systems security, exascale programming models, and energy-efficient computing toolchains. He operates within the Computer Architecture and High Performance Systems laboratory, directing research on computational resource orchestration for next-generation heterogeneous platforms.

Martin BuchholzView profile

Professor

• High-Frequency Engineering
• RFID Systems
• Antenna Design
• +5 more

Prof. Dr.-Ing. Martin Buchholz is the Head of Electrical Engineering at Saarland University of Applied Sciences . He leads the RI-ComET research group and oversees the High Frequency Laboratory and Optical Communications Laboratory . His work focuses on high-frequency systems, wireless communication, and embedded design. Contact: martin.buchholz@htwsaar.de Location: Room 2302, Goebenstraße 40, Saarbrücken Research Highlights: Development of innovative RFID systems and TPMS (Tire Pressure Monitoring Systems). Advancements in antenna design , software-defined radio , and radio field propagation . Focus on contactless energy transfer , embedded systems , and real-time FPGA implementations . Collaboration with partners like IKU Systems & Services and Stürmer Freizeittechnik for high-altitude balloon projects ( htw saar stratos ). Academic Contributions: Co-authored 15+ publications on RFID , OFDM systems , and DVB-H receivers (1999–2014). Key journals/conferences: IEEE Transactions on Consumer Electronics , ISSCC , Wireless Congress Munich . Students & Team: Dipl.-Ing. Joachim Hauck , M.Sc. Andreas Becker , M.Sc. Christian Schmidt , and B. Eng. Tina Müller are listed as team members. Projects include Mission I–VI of the stratosphere balloon program, with test flights from 2014 to 2019. Labs & Facilities: High Frequency Laboratory and Optical Communications Laboratory at Saarland University of Applied Sciences. Technical center for EMC measurements and antenna testing.