جستجوی استاد راهنمای دانشگاهی

Giovanni De Micheli is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding appointments in both the School of Computer and Communication Sciences (IC) and the School of Engineering (STI). He is affiliated with the Integrated Systems Laboratory (LSI) and serves as Scientific Director of EcoCloud. His primary office is located in INF 341 building at EPFL's Lausanne campus where he conducts research and teaching activities. Professor De Micheli's research spans multiple domains in electronic design automation and integrated circuit design. His primary interests include: Integrated Circuit Design and Hardware Synthesis Logic Optimization and Boolean Methods Nanoelectronics and 2D Electronics Quantum Computing and Emerging Technologies Low-Power Electronics and Energy-Efficient Systems Electronic Design Automation for Novel Computing Paradigms His recent publications demonstrate a strong focus on advancing logic synthesis techniques for both conventional and emerging technologies. Professor De Micheli's work bridges theoretical foundations with practical applications, particularly in adapting traditional EDA methods to novel computing paradigms like quantum computing and superconducting electronics. His research group has made significant contributions to the development of efficient algorithms for circuit optimization across multiple technology domains, with particular emphasis on area, power, and delay optimization while maintaining functional correctness. Professor De Micheli has supervised numerous doctoral students throughout his career at EPFL, mentoring over 40 PhD candidates whose research spans various aspects of electronic design automation, circuit design, and emerging technologies. His students have gone on to make significant contributions in both academia and industry. As Scientific Director of EcoCloud, Professor De Micheli leads research initiatives focused on energy-efficient computing systems and sustainable cloud infrastructure. His laboratory, the Integrated Systems Laboratory, serves as a hub for interdisciplinary research connecting computer science, electrical engineering, and materials science, with particular focus on next-generation computing technologies.

• Integrated Circuit Design
• Hardware Synthesis
• Logic Optimization
• +۵ مورد دیگر

Prof. Roger Wattenhofer is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland, and Deputy head of the Computer Engineering and Networks Lab. He holds a doctorate in Computer Science from ETH Zurich (1998) and has held positions at Brown University and Microsoft Research before returning to ETH. His research focuses on distributed computing, wireless networks, and algorithmic systems design, with contributions to Byzantine agreement protocols, blockchain technologies, and neural network architectures. He teaches courses such as Distributed Systems and Computational Thinking. Education: Ph.D. in Computer Science (ETH Zurich, 1998). Research interests include distributed systems, network algorithms, and the intersection of machine learning with distributed computing. His work spans both theoretical foundations and practical implementations, addressing challenges in fault tolerance, consensus mechanisms, and algorithmic efficiency. Recent publications explore topics like adversarial robustness in voting systems, privacy in reinforcement learning, and generative music models. He actively contributes to open-source frameworks and benchmarks for neural algorithmic reasoning.

• Distributed Computing
• Wireless Networks
• Distributed Systems
• +۴ مورد دیگر

Prof. Dr. Gonzalo Guillén Gosálbez is a Full Professor at the Department of Chemistry and Applied Biosciences , ETH Zürich. He holds a PhD in Process Systems Engineering (UPC, 2005) and has held academic positions at Imperial College London (Reader), University of Manchester (Senior Lecturer), and Universitat Rovira i Virgili (Assistant/Associate Professor). His research focuses on Sustainable Chemical Processes , integrating life cycle assessment, optimization techniques, and planetary boundary analysis to evaluate and design low-carbon technologies. Current position: Full Professor, ETH Zürich (2019–present) Prior roles: Imperial College London (2016–2019), University of Manchester (2014–2016), URV Spain (2008–2014) Education: PhD (UPC, 2005), MEng/BEng (University of Murcia) His research explores CO2 valorization , green methanol synthesis , circular marine fuels , and planetary boundary compliance in energy and chemical systems. Recent work emphasizes machine learning for process modeling, single-atom catalysis , and decentralized ammonia production . Scientific contributions include 15+ peer-reviewed articles (2023–2025) in journals like Nature Chemical Engineering , ACS Sustainable Chemistry & Engineering , and Energy & Environmental Science . Key themes: Optimization of hybrid fossil/renewable carbon systems Environmental impacts of energy transitions Catalyst design for sustainable chemistry Life cycle assessment of emerging technologies Awarded UPC Top Doctoral Student Award and Top National Student Award , he combines process systems engineering with sustainability metrics to address global challenges in chemical and energy systems.

• Process Systems Engineering
• Sustainable Chemistry
• Environmental Impact Assessment
• +۷ مورد دیگر

Andras Kis is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI) across multiple institutes including the Institute of Electrical Engineering (IEL), Institute of Materials Science (IMX), and teaching programs in Electrical Engineering (SEL-ENS). He leads the Laboratory of Nanoscale Electronics and Structures (LANES) and serves on the PhD program committee for Microsystems and Microelectronics. PhD, EPFL (2003) MS, Physics, University of Zagreb (1999) Baccalaureate, MIOC High School Research Focus: Pioneering work on 2D materials for electronic and optoelectronic devices, particularly transition metal dichalcogenides like MoS2 and PtSe2. His research spans: Transistor design with atomically thin semiconductors Excitonic devices and valleytronics Nanofluidics and ionic logic Optical properties of 2D heterostructures Scalable fabrication of 2D materials Defect engineering and doping techniques Scientific Impact: Based on analysis of 15 most recent publications, his work focuses on advancing 2D materials for next-generation electronics through innovations in: Van der Waals heterostructures Thermoelectric and optoelectronic applications Nanofabrication techniques Spintronic and quantum transport phenomena Memristive and neuromorphic devices Characterization of electronic and optical properties Awards & Recognition: Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Lotfi A. Zadeh Award for Emerging Technologies (2024) Highly Cited Researcher (Clarivate Analytics) Teaching & Academic Leadership: Currently teaching courses including Lab in Nanoelectronics , Physical Models for Micro and Nanosystems , and Semiconductor Devices II . He has supervised over 20 PhD students in his research group at EPFL. Laboratory & Collaborations: Directs the Laboratory of Nanoscale Electronics and Structures (LANES) which focuses on fundamental and applied research in 2D materials and nanoelectronic devices. His work bridges materials science, condensed matter physics, and microelectronics engineering.

• 2D Materials
• Nanoscale Electronics
• Optoelectronics
• +۳ مورد دیگر

Prof. Peter Müller is a Full Professor at the Department of Computer Science at ETH Zurich since 2008. Previously, he held positions as Assistant Professor at ETH Zurich (2003-2008), Researcher at Microsoft Research Redmond (2007-2008), and IT project manager at Deutsche Bank. He earned his Diploma in Computer Science from Technical University of Munich (1996) and his Dr. rer. nat. from University of Hagen (2001) with a dissertation on modular verification of object-oriented programs. His research focuses on enabling correct software development through programming languages, verification methods, and tools. Key areas include formal verification for Rust and Go programs (Prusti and Gobra projects), separation logic, security protocols, and distributed systems verification. Müller's work emphasizes practical verification techniques for real-world systems, including secure router implementations and smart contract verification. Recent research trends highlight advancements in hyperproperties, modular reasoning for iterators and closures in Rust, and formal validation of verification tools. His methodologies bridge theoretical foundations with industrial applications, addressing challenges in concurrency, memory safety, and security assurance. Notable contributions include the SCION internet architecture, the Prusti verifier for Rust, and formal verification frameworks for distributed systems. His work often integrates rigorous mathematical foundations with scalable software engineering practices.

• Formal Methods
• Program Verification
• Programming Languages
• +۴ مورد دیگر

Sebastijan Dumancic is an Assistant Professor at Delft University of Technology, focusing on neuro-symbolic AI through program synthesis and probabilistic programming. He leads the RAIL lab and collaborates with institutions like Harvard, MIT, and CNRS. His research bridges symbolic AI and machine learning, applying program synthesis to scientific discovery, transportation, and robotics. He holds an FWO-funded PhD from KU Leuven and has participated in initiatives like ELLIS and the Symbolic Computation and Machine Learning Initiative. Program synthesis Probabilistic programming Neuro-symbolic AI Constraint-based learning His recent articles highlight advancements in program synthesis, neuro-symbolic integration, and constraint satisfaction. Projects like Find2Fix and Intelligent Greenhouse Horticulture (funded by NWO) demonstrate practical applications. ELLIS Membership University Teaching Qualification He supervises numerous MSc and PhD students in projects involving logic programming, program synthesis, and probabilistic modeling. Active in workshops and symposia, he contributes to neuro-symbolic AI and scientific discovery.

• Program Synthesis
• Probabilistic Programming
• Neuro-Symbolic AI
• +۲ مورد دیگر

Andrea Costamagna is a researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL), working within the School of Computer and Communication Sciences and the Department of Communication Systems. His research focuses on logic synthesis, digital circuit design, and the intersection of machine learning with hardware implementation. His work includes optimizing digital circuits using techniques like resynthesis, resubstitution, and decomposition, with applications in FPGA design and low-power systems. Recent publications explore symmetry-based synthesis, glitch-aware power minimization, and the use of resistive switching devices in machine learning hardware. His research also extends to quantum physics modeling with deep learning.

• Logic Synthesis
• Digital Circuit Design
• Machine Learning
• +۳ مورد دیگر

Aleksandra Radenovic is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) holding multiple positions across the institution. She is a Full Professor at the Laboratory of Nanoscale Biology (LBEN) within the School of Engineering (STI), a Full Professor in Teaching at the School of Life Sciences (SV), and a Full Professor in Teaching at the School of Engineering (STI). Additionally, she serves as Co-Director of both the IBI-STI and IBI-SV administrative units, and is a Member of both the STI School direction and SV School direction. Dr. Radenovic received her PhD from the University of Lausanne in 2003, where she worked with Prof. Dietler in the Laboratory of Physics of Living Matter. Prior to that, she studied physics at the University of Zagreb from 1994-1999, and completed her baccalaureate at a Classical gymnasium in 1994. She conducted postdoctoral research at the University of California, Berkeley from 2004-2007 in the group of Prof. Liphardt. Her research focuses on single molecule biophysics, with particular emphasis on developing techniques and methodologies based on optical imaging, biosensing, and single molecule manipulation. Her laboratory works on three major research directions: (i) developing and using nanopores as platforms for molecular sensing and manipulation, particularly solid-state nanopores in glass nanocapillaries and 2D-material membranes; (ii) studying biomolecular function, especially protein and nucleic acid interactions, using force-based manipulation techniques like optical tweezers and Anti-Brownian Electrokinetic traps; and (iii) developing super-resolution optical microscopy based on single molecule localizations for quantitative cellular imaging. Her work bridges physics, engineering, and biology to create innovative tools for understanding molecular processes at the nanoscale. Analysis of her recent publications reveals a strong focus on nanofluidics, 2D materials (particularly MoS 2 and hBN), nanopore sensing, super-resolution microscopy, and the development of novel instrumentation for biophysical applications. Her research demonstrates increasing interdisciplinary collaboration, integrating materials science, nanotechnology, and biological applications to address fundamental questions in molecular biophysics. Dr. Radenovic has received numerous prestigious awards and grants, including: 2021: ERC Advanced Grant 2021: Optica Fellow 2016: CCMX Materials challenge award 2015: SNSF-ERC Consolidator Grant 2010: ERC Starting Grant 2003: SNSF Fellowship She has successfully advised numerous PhD students whose research spans single molecule biophysics, nanofluidics, and optical techniques. Her laboratory, the Laboratory of Nanoscale Biology (LBEN), is well-equipped for advanced biophysical research, with capabilities in nanopore fabrication, optical trapping, super-resolution microscopy, and 2D materials characterization. Dr. Radenovic has secured significant research funding through competitive grants, including multiple ERC grants, which have supported her innovative research program at the intersection of physics, engineering, and biology.

• Single molecule biophysics
• Solid State Nanopores
• 2-D materials
• +۶ مورد دیگر

Laura Pozzi is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Switzerland, since 2015. She previously held positions as Associate Professor (2011–2015) and Assistant Professor (2005–2011) at USI. Prior to joining USI, she was a postdoctoral researcher at EPFL's Processor Architecture Laboratory (2001–2005), a research engineer at STMicroelectronics (2000), and an Industrial Visitor at UC Berkeley (2000). Education: MS and PhD in Computer Engineering from Politecnico di Milano, Italy (1996–2000). Her research focuses on the interaction between compiler and architecture design, particularly in embedded systems , with key areas including approximate computing , coarse-grained reconfigurable arrays (CGRAs) , high-level synthesis (HLS) , and fuzz testing . She has led projects on automated design space exploration, compiler optimizations for reconfigurable architectures, and error estimation in approximate circuits. Recent Publications span topics like SAT-based mapping for CGRAs , grammar-based fuzzing of shell interpreters , and approximate logic synthesis , reflecting her interdisciplinary work bridging hardware/software co-design and software verification. Scientific Awards: Credit Swiss Best Teaching Award IEEE DAC Best Paper Award Leadership Roles: Co-Program Chair, IEEE Symposium on Application Specific Processors (SASP) Editorial Board Member, IEEE Design and Test Students: Current: Rodrigo Otoni (Postdoc), Morteza Rezaalipour (PhD), Riccardo Felici (PhD), Cristian Tirelli (PhD) Alumni: Ilaria Scarabottolo (PhD/Postdoc), Lorenzo Ferretti (PhD/Postdoc), Georgios Zacharopoulos (PhD), Giovanni Ansaloni (PhD/Postdoc), Paolo Bonzini (PhD)

• Embedded Systems
• Compiler Techniques
• Coarse-Grain Reconfigurable Architectures
• +۳ مورد دیگر

Malte Helmert is a Professor at the University of Basel in the Department of Mathematics and Computer Science. He previously worked at the University of Freiburg's Research Group on the Foundations of Artificial Intelligence from 2001 to 2011. His research focuses on intelligent problem-solving , particularly in automated planning , combinatorial search , constraint satisfaction , and NP-hard graph problems . Helmert has made significant contributions to classical planning, including the development of the Fast Downward planning system and its derivatives. Education : Diploma in Computer Science (M.Sc.) from the University of Freiburg (2001) Ph.D. in Computer Science from the University of Freiburg (2006) Research interests encompass the theoretical and practical aspects of automated planning, including heuristic search , optimal planning , abstraction techniques , and domain-independent planning . His work explores merge-and-shrink abstractions , landmark progression , and cost partitioning algorithms for classical planning systems. Recent publications analyze advancements in pseudo-Boolean proof logging , higher-dimensional potential heuristics , and correlation complexity in planning domains. These works often integrate mathematical modeling, algorithm design, and empirical benchmarking. Scientific awards include the AAAI Fellow (2021), EurAI Fellow (2020), multiple Best Paper Awards at ICAPS and SoCS conferences, and the Computers and Thought Award (2011). He also received the VDI-Förderpreis for his Master’s thesis. Software contributions include the Fast Downward planning system, MIPS (now maintained by Stefan Edelkamp), and COVER (a vertex cover solver). Helmert has organized tutorials at ICAPS and AAAI conferences on topics like landmark progression , abstraction heuristics , and LP-based heuristics .

• Automated Planning
• Combinatorial Search
• Artificial Intelligence
• +۷ مورد دیگر

K Ram Prabhakar is an Assistant Research Scientist at Johns Hopkins University, advised by Prof. Rama Chellappa. Previously, he earned his Ph.D. from the Video Analytics Lab at the Computational and Data Sciences department of the Indian Institute of Science under Prof. R. Venkatesh Babu. He also worked as a Research Scientist at TCS Research in Bangalore. His research focuses on Computer Vision and Computational Photography , particularly in High Dynamic Range (HDR) Imaging , 3D vision, and image processing. His work spans applications in biometrics, remote sensing, and medical imaging. Recent publications highlight advancements in distillation-guided representation learning for video authentication diffusion models for fairness in face generation gait recognition thermal modality integration for low-light imaging and SAR (Synthetic Aperture Radar) applications . Scientific awards include IAPR Best Biometrics Student Paper Award (2024) Best Student Paper - Runner Up at BMVC 2021 . He has advised multiple students, including Yuxiang, Vishal, and Susmit, and contributed to projects on HDR deghosting, image fusion, and deep learning for computer vision tasks.

• Computer Vision
• Image Processing
• Machine Learning
• +۵ مورد دیگر

Filip Ilievski serves as an Assistant Professor of Commonsense AI (Sr.) at Vrije Universiteit Amsterdam, where he leads the Learning and Reasoning Group. He holds additional affiliations as an Affiliated Scientist at USC Information Sciences Institute and Amsterdam Sustainability Institute, and serves as Scientific Coordinator of the Digital Sustainability Institute (DiSC). His academic journey includes a PhD from Vrije Universiteit Amsterdam (2015-2019), research positions at USC (2019-2023), and a research visit to Carnegie Mellon University (2017). Dr. Ilievski's research focuses on advancing human-centric AI with common sense for social good applications. His work spans three interconnected areas: commonsense reasoning (including situational awareness, numeracy, and modeling of other agents), analogy and abstraction (studying cognitive generalization mechanisms through narratives and lateral thinking puzzles), and AI for social good (interpreting complex online media like internet memes and developing knowledge-based solutions for sustainable policies). He employs neuro-symbolic methods including prototype-based networks, combining LLMs with deterministic engines, and reasoning with scene knowledge graphs to create robust, interpretable AI systems. His publication record shows a strong trend toward multimodal reasoning and practical applications of commonsense AI, particularly in understanding internet memes, developing sustainable AI solutions, and creating robust evaluation frameworks like the MARVEL benchmark. Recent work increasingly integrates cognitive theories with neural architectures to address limitations in current foundation models, with particular emphasis on explainability and cultural context awareness. Best Student Paper Award at K-CAP for 'Knowledge-enhanced Agents for Interactive Text Games' Best Paper and Best Presentation Award at Workshop on Multimodal Content Analysis for Social Good (MM4SG) Book 'Human-Centric AI with Common Sense' published in Springer Nature Synthesis series Dr. Ilievski actively supervises a growing team of PhD students and postdocs, with current projects focusing on visual commonsense reasoning, meme semantics, analogical abstraction, multimodal alignment, and architectures for human-centric AI. His Digital Sustainability Institute (DiSC) coordinates research on knowledge-driven AI for sustainable policies, while his Situated AI minor program develops next-generation AI education. He maintains active collaborations with institutions including USC, CMU, RPI, University of Lyon, UvA, University of Bielefeld, and industry partners like Bosch Research, NEC Labs, Merit Technologies, and Tencent.

• Commonsense Reasoning
• Neurosymbolic AI
• Analogy and Abstraction
• +۱۱ مورد دیگر

Heinz Riener is a Researcher at the Integrated Systems Laboratory (LSI) within the School of Computer and Communication Sciences (IC) at EPFL, Lausanne, Switzerland. He holds a Ph.D. (Dr.-Ing.) in Computer Science from the University of Bremen, Germany. Previously, he worked at the German Aerospace Center (DLR) and the University of Bremen's Reliable Embedded Systems group. His research focuses on logic synthesis , formal methods , and computer-aided verification of hardware and software systems. Key areas include quantum computing (e.g., AQFP circuits), nanotechnology (e.g., RFET-based circuits), and emerging technologies like adiabatic quantum-flux parametron systems. Developed open-source tools like mockturtle and easy for logic synthesis and ESOP forms. Principal Investigator on projects like the Open Logic Synthesis Libraries initiative. Active in program committees for conferences like DAC, DATE, and FDL. Collaborates with institutions such as TU Graz, TU Hamburg, and UC Berkeley. His work emphasizes reproducibility and open-source collaboration in logic synthesis, contributing to benchmarks and libraries widely used in academia and industry.

• Logic Synthesis
• Formal Methods
• Computer-Aided Verification
• +۴ مورد دیگر

Prof. em. Dr. Peter Maas is an Affiliate Professor of Management at Vlerick Business School, specializing in Service Management and Insurance Management. His research focuses on digital transformation's impact on consumer behavior, particularly in the insurance sector, emphasizing prevention through advanced technologies. He explores topics like customer experience, omnichannel strategies, and organizational ambidexterity in SMEs. Key research areas include the role of self-tracking technologies in healthcare, cultural influences on information sharing, and the evolution of experience research over four decades. His work bridges academic insights with practical strategies for enhancing customer value and organizational effectiveness. Notable contributions address challenges in digital reputation management, the ethical implications of nudging in consumer decisions, and fostering cooperation among insurers and insurtech firms. He advises students like Lukas Fischer (2021) and Matthias Rüfenacht (2017), focusing on impactful research in service innovation and organizational dynamics.

• Insurance Management
• Service Management
• Digital Transformation
• +۳ مورد دیگر

Dr. Emir Demirović is an Assistant Professor in the Department of Computer Science at Delft University of Technology (TU Delft), The Netherlands. He leads the Constraint Solving ("ConSol") research group and co-directs the Explainable AI in Transportation Lab ("XAIT") as part of Delft AI Labs. Prior roles: Postdoc at University of Melbourne (2017-2020), PhD at Vienna University of Technology (2017) Collaborations: Civil Engineering, QuTech, and industry partners Funding sources: Dutch national funding agency, TU Delft, VoestAlpine Research Focus: Constraint programming and combinatorial optimisation Explainable AI methods for decision-making systems Integration of optimisation with machine learning Robust/resilient optimisation for industrial applications Optimal decision trees with dynamic programming Quantum computing scheduling techniques Scientific Contributions: Pioneered "Pseudo-Boolean Reasoning" for algorithm certification Developed "Blossom" algorithm for optimal decision trees Advances in "Predict+Optimise" frameworks Created Pumpkin constraint programming solver Bridge between SAT/CP and Machine Learning Awards: First Place, MaxSAT Evaluation 2018+ First Place, ROADEF/EURO 2012 Adoption of methods in Google OR-Tools Collaborations: Research visits to EPFL, ANITI/CNRS, CUHK, Monash University, TU Wien Participated in Dagstuhl seminars, Lorentz workshops, and Simons-Berkeley programme

• Constraint Programming
• Combinatorial Optimisation
• Explainable AI
• +۴ مورد دیگر