جستجوی استاد راهنمای دانشگاهی

Rolf Wankaمشاهده پروفایل

استاد

• Algorithms
• Combinatorial Optimization
• Swarm Intelligence
• +۳ مورد دیگر

Prof. Dr. Rolf Wanka is a Professor at the Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specializing in efficient algorithms and combinatorial optimization. His research focuses on swarm intelligence, discrete optimization algorithms, and scheduling problems, particularly in timetabling and robotics applications. Education : Sc.D. (Dr. rer. nat.) in Computer Science His work includes theoretical and experimental analyses of particle swarm optimization (PSO) algorithms, addressing runtime complexity, stagnation behavior, and convergence properties. He has developed novel heuristics for timetabling and sorting problems, with applications in multi-robot systems and medical imaging. Notable collaborations include studies on Markov chain-based PSO and fairness in academic scheduling. Key trends in his recent publications span swarm intelligence , discrete optimization , and scheduling heuristics , with a focus on robust timetabling , runtime analysis , and stochastic algorithm behavior . While no explicit scientific awards are listed, his mentorship in the Max Weber-Programm highlights his advisory role in academia. His publications demonstrate interdisciplinary applications of algorithms in robotics , medical imaging , and parallel computing , leveraging both theoretical rigor and practical experimentation. The full description below provides exhaustive details on his academic contributions and affiliations.

Akbar Siami Naminمشاهده پروفایل

استاد

• Cybersecurity
• Software Engineering
• Program Analysis
• +۵ مورد دیگر

Dr. Akbar Siami Namin is a Professor in the Department of Computer Science at Texas Tech University's Whitacre College of Engineering . He leads the AdVanced Empirical Software Testing & Analysis (AVESTA) research group and contributes to cybersecurity, software engineering, and program analysis. Ph.D., Computer Science, University of Western Ontario (2008) M.S., Lakehead University/University of Western Ontario (2004) Research Interests : Dr. Namin specializes in Natural Language Processing , Software and Cyber Security , Machine Learning , Time Series Analysis , Modeling Human Factors , and Program Analysis . His work bridges security testing , mutation analysis , and empirical software engineering . Publications : His research spans sonification of security threats , keystroke dynamics , statistical fault localization , and mutation testing , with recent works published at CHI , ICMLA , and CyberWorlds (best paper award 2015). Scientific Awards : Best Paper Award at CyberWorlds 2015; 'Most Influential Professor' recognition by Computer Science undergraduates (2012). Students & Grants : Supervised numerous Ph.D. and Master's students, including Alaa Darabseh and Xiaozhen Xue. Secured over $1M in NSF grants for projects like CyberCorps Capacity Building , Security Sonification , and Cybersecurity Education for Community Colleges .

• Computational Linguistics
• Natural Language Processing
• Formal Language Theory
• +۲ مورد دیگر

Giorgio Satta is a Full Professor at the Department of Information Engineering , University of Padua, Italy. He received his Ph.D. in Computer Science from the University of Padua in 1990. His career includes research positions at Fondazione Bruno Kessler (Trento) and the University of Pennsylvania (IRCS). Research Focus : His work centers on computational linguistics and formal language theory , with emphasis on: Parsing algorithms (CCG, TAG, LCFRS) Computational complexity of grammar formalisms Probabilistic language modeling Dependency parsing and synchronization techniques Professional Service : He chaired the European Chapter of the ACL (2009-10), served on editorial boards for Computational Linguistics , Transactions of the ACL , and co-chaired ACL-2001/IWPT-2001. Teaching : Current courses include Automata, Languages, and Computation and Natural Language Processing (2024-25).

• Mobile Computing
• Mobile Cloud Computing
• Context-aware and -adaptive Applications
• +۱ مورد دیگر

Dr. Gabriel Orsini is a researcher at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Hamburg. He works on context-adaptive systems for mobile cloud computing and has developed the CloudAware middleware framework. PhD (2017): Kontextadaptive Anwendungsarchitekturen für das mobile Cloud Computing Diploma Thesis (2008): Maschinelles Lernen zur Prognose von Erlösen im Luftverkehr His research focuses on mobile cloud computing , context-aware systems , and resource optimization through dynamic adaptation. Article trends show expertise in context adaptation , energy efficiency , and IoT integration . Professional activities include: Guest Editor for Forecasts in the Internet of Things Reviewer Board Member for Future Internet and Machine Learning and Knowledge Extraction Conference TPC Member for FNC 2021 and FNC 2020 He has supervised 18+ student theses across blockchain systems , context-aware computing , and mobile resource management , including advising on AutoML applications , decentralized ledgers , and probabilistic databases .

David Langeمشاهده پروفایل

دانشیار

• Fire Safety Engineering
• Structural Engineering
• Risk Analysis
• +۳ مورد دیگر

Associate Professor David Lange serves as Deputy Director of Higher Degree by Research at the School of Civil Engineering , University of Queensland . With academic qualifications from the University of Edinburgh (PhD and MSc), he specializes in fire safety engineering and structural engineering , focusing on timber buildings, lithium-ion battery fire safety, and risk analysis techniques. Chartered Engineer (CPEng), Fellow of Engineers Australia (FIEAust) Registered Professional Engineer of Queensland (RPEQ) APEC Engineer and International Professional Engineer (IntPE) His research explores fire behavior in mass timber structures , vertical fire spread , and infrastructure resilience . Publications highlight his expertise in probabilistic modeling, fire dynamics, and structural response to extreme conditions. Recent collaborative studies examine flame spread in ventilated façades, compartment fire behavior, and risk evaluation frameworks. He actively supervises PhD projects in areas like fire safety of low-carbon concrete, diagrid structures, and physics-informed machine learning for fire modeling.

David Wainwrightمشاهده پروفایل

پژوهشگر ارشد

• Coastal Engineering
• Environmental Hydraulics
• Coastal Geomorphology
• +۳ مورد دیگر

David Wainwright is an adjunct research fellow at the University of Queensland's School of Civil Engineering and a adjunct lecturer at the University of Newcastle. With over 20 years of industry experience as a consulting engineer, he specializes in coastal engineering , environmental hydraulics , and climate change adaptation , particularly in coastal zones. University: University of Queensland Secondary Affiliation: University of Newcastle Academic Rank: Research Fellow His research focuses on coastal geomorphology , numerical modeling of coastal processes, and risk assessment for coastal flooding and sea level rise. He has developed frameworks for probabilistic hazard lines , coastal lagoon management , and stochastic erosion modeling . His work integrates engineering design with policy considerations, including local government planning and community consultation . A chartered engineer with Engineers Australia since 2001, he contributes to coastal risk evaluation and climate adaptation guidance . He founded the consulting firm Salients Pty Limited in 2015, extending his expertise to state and national projects .

Nicole Kessissoglouمشاهده پروفایل

استاد

• Mechanical Engineering
• Dynamics
• Vibration and Vibration Control
• +۵ مورد دیگر

Professor Nicole Kessissoglou is a distinguished academic in the School of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW Sydney). She holds the position of Professor and conducts her research within the Ainsworth Building (J17), Level 4, Room 408 at the Kensington Campus. Her academic profile is prominently featured on UNSW's research portal, highlighting her expertise in structural vibration, acoustics, and fluid-structure interaction. Professor Kessissoglou's research interests span across several critical areas of mechanical engineering, with a particular focus on Structural vibration and transmission , Acoustics , Structure-fluid coupling , Active vibration control , and Active structural acoustic control . Her work falls within the broader Fields of Research categories of Mechanical Engineering, Dynamics, Vibration and Vibration Control, and Acoustics and Noise Control. Her research addresses fundamental challenges in how structures interact with fluids and how sound and vibrations propagate through these systems. Analysis of her most recent publications (2023-2025) reveals a strong focus on wave phenomena in periodic and resonant systems, with significant attention to underwater applications. Her work spans theoretical modeling, numerical simulation, and experimental validation of acoustic and vibration phenomena. Key themes include structural cloaking technology, uncertainty quantification in resonant systems, vibroacoustic responses of coated cylindrical shells, and novel acoustic metamaterial designs. Her research has important applications in naval engineering, underwater acoustics, and noise control technologies. Professor Kessissoglou maintains an extensive publication record with 140 journal articles, 9 book chapters, 187 conference papers, and various other scholarly outputs. Her work demonstrates a consistent trajectory of advancing knowledge in structural acoustics and vibration control, with increasing focus on metamaterial applications and hybrid active-passive control systems in recent years. Her research activities appear to be well-integrated within UNSW's broader engineering research ecosystem, particularly within the university's strengths in aerospace, structural engineering, and technology for good initiatives. While specific grant information isn't detailed in the available materials, her publication output suggests sustained research funding and active collaboration with other researchers in her field.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +۱۲ مورد دیگر

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

Yoseph Barashمشاهده پروفایل

دانشیار

• Machine Learning
• Computational Biology
• Bioinformatics
• +۴ مورد دیگر

Yoseph Barash is an Associate Professor at the University of Pennsylvania, jointly appointed in the Perelman School of Medicine's Department of Genetics and the School of Engineering and Applied Science's Department of Computer and Information Science. He leads the BioCiphers Lab, integrating machine learning with experimental biology to decode RNA biogenesis and splicing regulation in human disease. Education: B.Sc. in Physics and Computer Science, Hebrew University Ph.D. in Machine Learning, Hebrew University (2006) His research spans Machine Learning , Computational Biology , and Bioinformatics , focusing on predictive models for RNA splicing and its role in diseases like cancer and neurological disorders. He pioneered the splicing code (Barash et al., Nature 2010) and extended it to genetic variations (Xiong et al., Science 2015). Recent publications emphasize RNA splicing variations in cancer, tool development (e.g., MAJIQ V3, MAJIQ-CLIN), and machine learning for drug discovery (e.g., trametinib sensitivity in AML). His work bridges computational innovation with wet-lab validation, enabling novel high-throughput assays. Scientific Awards: Lap-Chee Tsui Publication Award (2010) NSERC EWR Steacie Fellowship Canadian Institute for Advanced Research Fellowship He advises companies in RNA therapeutics and has licensed splicing quantification tools to Pfizer, GSK, and Biogen. His lab collaborates extensively, training students and postdocs in interdisciplinary approaches to RNA biology.

Bradley Hayesمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Explainable AI (XAI)
• Collaborative Robotics
• +۵ مورد دیگر

Bradley Hayes is an Associate Professor of Computer Science and Director of the Collaborative AI and Robotics (CAIRO) Laboratory at the University of Colorado Boulder. His work focuses on enabling autonomous agents and robots to collaborate safely and effectively with humans through techniques in human-robot interaction, explainable AI, and learning from demonstration. PhD in Computer Science, Yale University (2015) Postdoctoral Associate, MIT Interactive Robotics Group Research interests span collaborative robotics, dependable AI systems, and imitation learning for human-robot teaming, with applications in manufacturing, healthcare, and autonomous vehicles. His lab develops methods for task planning, motion prediction, and trust calibration in human-machine partnerships. Recent publications emphasize explainable sequential decision-making, neuromorphic learning architectures, and augmented reality interfaces for robotic training. Awards include Sustainability Recognition (2025) for motion planning efficiency Best Student Paper Runner-up (AAMAS 2022) Best Technical Paper Runner-up (HRI 2019) As lab director, he has mentored 12 PhD/Master students to completion, including Matthew Luebbers, Aaquib Tabrez, and Christine Chang. Funding sources include NSF grants and industry partnerships like Circadence, where he serves as Chief Technology Officer.

Brian Maggiمشاهده پروفایل

استاد

• Coastal Engineering
• Geotechnical Engineering
• Coastal Resiliency
• +۵ مورد دیگر

Brian Maggi, Ph.D., P.E., is a Professor and Department Head at the U.S. Coast Guard Academy's Department of Civil and Environmental Engineering. He has military, academic, and research experience in geotechnical engineering, coastal engineering, and construction project management. Education: Ph.D. in Civil Engineering from the University of Rhode Island (2022) M.S. in Civil Engineering from the University of Connecticut (2005) B.S. in Civil Engineering from the U.S. Coast Guard Academy (2000) Maggi's research focuses on coastal resiliency, reinforced dunes, and erosion modeling. He has conducted field-monitoring programs using drones, LiDAR, and advanced equipment to develop fragility curves for coastal protection systems. His publications include case studies on geosynthetic sand containers for dune reinforcement and educational strategies for integrating coastal resiliency into engineering curricula. Maggi collaborates with colleagues to incorporate Short Range – Unmanned Aircraft Systems (SR-UAS) into the USCGA academic and mission programs. Professional Affiliations: American Society of Civil Engineers (ASCE) Society of American Military Engineers (SAME) American Society of Engineering Education (ASEE) Maggi teaches courses such as Civil Engineering Design, Construction Project Management, and Short Range – Unmanned Aircraft Systems. He is certified as an SR-UAS Instructor Pilot and contributes to multidisciplinary research and mission support for the Coast Guard.

• Evolutionary Computation
• Genetic Algorithms
• Optimization
• +۵ مورد دیگر

Dirk Thierens is an Associate Professor in the Department of Computer Science at Utrecht University's Faculty of Science, specializing in Intelligent Systems within AI & Data Science. His academic career spans over 25 years, with continuous publications from 1996 through 2025, demonstrating sustained research activity and leadership in his field. He maintains an active research program with numerous collaborations, most notably with Peter A.N. Bosman, indicating a long-standing productive research partnership. Thierens' research focuses on evolutionary computation, particularly model-based evolutionary algorithms, genetic algorithms, and optimization techniques. His work has evolved from foundational genetic algorithm research in the late 1990s and early 2000s to more specialized model-based approaches in recent years, including significant contributions to Gene-pool Optimal Mixing Evolutionary Algorithms (GOMEA). His expertise spans single-objective and multi-objective optimization, permutation problems, mixed-integer problems, and real-valued optimization. In recent years, his research has expanded into applications in machine learning, particularly semi-supervised learning and neural network optimization. His publication record shows a consistent output of high-quality research, with numerous papers in top conferences like GECCO and journals in evolutionary computation. His most recent work (2023-2025) demonstrates continued innovation in synthetic data generation, neural network combination techniques, and parameterless evolutionary algorithms. The breadth of his work spans theoretical algorithm development, benchmarking methodologies, and practical applications in healthcare and other domains. While no specific scientific awards are mentioned in the available information, his extensive publication record, tutorial contributions at major conferences, and sustained research productivity over multiple decades indicate recognition within the evolutionary computation community. His tutorial work at GECCO conferences suggests he is considered an authority on model-based evolutionary algorithms. Thierens maintains an active research laboratory focused on evolutionary algorithms and their applications, with recent work exploring the intersection of evolutionary computation and deep learning. His research continues to advance both theoretical understanding and practical applications of optimization techniques in complex problem domains.

Aws Albarghouthiمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Formal Verification
• Quantum Computing
• +۵ مورد دیگر

Aws Albarghouthi is affiliated with the University of Wisconsin-Madison, USA. He is an active researcher with significant contributions to program synthesis, formal verification, and machine learning. Key roles: Author, Session Chair, Committee Member in conferences like PLDI, POPL, VMCAI, SPLASH, and ICFP. Research spans quantum computing, differential privacy, and static analysis. Research Trends include: Quantum Circuit Compilation and Optimization Probabilistic Verification of Fairness and Privacy Synthesis of Datalog and MapReduce Programs Neural-Augmented Static Analysis Bias Detection in Data Security Robustness in Machine Learning

• Reinforcement Learning
• Computational Decision-Making
• Artificial Intelligence
• +۵ مورد دیگر

Carlo D'Eramo is Professor and Head of the Reinforcement Learning and Computational Decision-Making professorship at the Center for Artificial Intelligence and Data Science (CAIDAS) of University of Würzburg. He additionally serves as an independent group leader of hessian.AI, focusing on developing lightweight methods to obtain adaptive autonomous agents that can handle real-world complexity. His academic journey includes: B.Sc. in Computer Engineering from Politecnico di Milano (2011) M.Sc. in Computer Engineering from Politecnico di Milano (2015) Double degree in Computer Science from University of Illinois at Chicago (2015) Ph.D. in Information Technology from Politecnico di Milano (2019) Postdoctoral research at TU Darmstadt's Intelligent Autonomous Systems group (2019-2022) D'Eramo leads the LiteRL research group investigating how agents can efficiently acquire expert skills accounting for real-world complexity. His research spans multiple reinforcement learning domains including multi-task, curriculum, adversarial, options, and multi-agent RL. His work bridges theoretical advances with practical applications, particularly in robotics and decision-making systems. His recent publications (2023-2025) demonstrate significant contributions across exploration strategies, neural network architectures, multi-agent coordination, and physics-informed machine learning. His work frequently appears in top-tier venues including TMLR, RLJ, IEEE PAMI, ICML, and ICLR, with multiple papers receiving spotlight or oral presentation designations. Professional activities include: Senior area chair for RLC Area chair for AAAI, ACML, AISTATS, NeurIPS, and ICLR Reviewer for DFG and ERC proposals Creator of MushroomRL reinforcement learning framework D'Eramo actively contributes to academic community service while mentoring researchers in his group. His work on lightweight methods aims to make reinforcement learning more practical for real-world applications across various domains.

Constantin Grigoمشاهده پروفایل

پژوهشگر

• Machine Learning
• Uncertainty Quantification
• Stochastic Differential Equ://grigo.userweb.mwn.de/ueber-mich/
• +۲ مورد دیگر

Constantin Grigo is a PhD researcher at the Technical University of Munich (TU Munich), actively engaged in the Continuum Mechanics group. His work focuses on Uncertainty Quantification (UQ) and Machine Learning (ML), particularly for applications in maritime safety, bicycle traffic modeling, and stochastic systems. He has presented his research at major conferences like SIAM UQ and WCCM, and has been recognized with Student Travel Awards from SIAM UQ 2018 and SIAM CSE 2019. Education: Master of Science in Physics, LMU Munich (2015) Bachelor of Science in Physics, LMU Munich (2012) Year abroad at Grenoble INP (2010-2011) Research Interests: Probabilistic machine learning for coarse-graining high-dimensional systems Bayesian model and dimension reduction Stochastic differential equations in heterogeneous media Microscopic traffic simulation for bicycles and autonomous vehicles Digital twin applications for maritime and urban mobility Reduced-order modeling of random materials Selected Awards: SIAM UQ 2018: Student Travel Award Winner SIAM CSE 2019: Student Travel Award Winner His publications span topics such as data-driven scenario specification for autonomous vehicles, bicycle maneuver prediction using neural networks, and physics-constrained surrogates for UQ. He also contributes to open-source simulation tools like SUMO for traffic modeling.