جست‌وجوی استاد و پژوهشگر

Prabhakar Pagillaمشاهده پروفایل

استاد

• Robotics
• Control Systems
• Roll-to-Roll Manufacturing
• +۳ مورد دیگر

Dr. Prabhakar Pagilla is the Associate Department Head and a Professor in the Department of Mechanical Engineering at Texas A&M University. He holds the James J. Cain Professor II title and leads the Robotics and Control Engineering Group. His research focuses on advanced control systems for robotics and roll-to-roll manufacturing, with emphasis on nonlinear dynamics, autonomous systems, and mechatronics. Education: Ph.D., Mechanical Engineering, University of California, Berkeley (1996) M.S., Mechanical Engineering, University of California, Berkeley (1994) B.E., Mechanical Engineering, Osmania University (1990) Research Interests: Modeling and control of roll-to-roll manufacturing systems Autonomous vehicles and cooperative adaptive cruise control Robotics/mechatronics, including workpiece localization and human-robot collaboration Control of large-scale nonlinear dynamic systems Recent Trends in Publications: Dr. Pagilla’s recent work emphasizes safety and efficiency in autonomous systems, including platooning strategies, V2V communication impacts, and exoskeleton ergonomics. His robotics research explores real-time path planning, shared control mechanisms, and anomaly detection in manufacturing processes. Awards: Fellow of ASME (2011) John J. Shelton Best Paper Award (2017, 2019) Regents Distinguished Research Award (2012) Lab/Teams: The Robotics and Control Engineering Group at Texas A&M focuses on interdisciplinary projects combining advanced control theory with practical applications in robotics and manufacturing. Current initiatives include surface finishing of curved geometries and predictive intent modeling for human-robot collaboration.

• Formal Verification
• Software Testing
• Programming Languages
• +۱۲ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His work bridges formal methods, software testing, and programming languages, with a focus on enhancing the reliability of high-performance and parallel software systems. He has held key roles including Director of Research (since 2023) and previously served as Lecturer (2011–2014), Senior Lecturer (2014–2017), and Reader (2017–2020) before being promoted to Professor in 2020. His research interests include formal verification, compiler testing, GPU programming, concurrency, and fuzzing. He has made significant contributions to the verification of GPU kernels, metamorphic testing of graphics drivers, and the development of tools like GPUVerify and GraphicsFuzz. His work combines theoretical rigor with practical impact, demonstrated by the acquisition of his startup GraphicsFuzz by Google in 2018 and his subsequent roles as Senior Software Engineer and Visiting Researcher at Google. His recent publications reflect a sustained focus on compiler and system reliability, with trends in fuzzing, formal specification, and automated testing of complex systems such as WebGPU, CXL cache coherence, and large language models for code generation. His work increasingly integrates empirical validation with formal techniques to uncover subtle bugs in real-world systems. Scientific awards and recognitions include: 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Fellow of the British Computer Society Best Paper awards at EuroSys 2024, MET 2021, IISWC 2019, IWOCL 2019, and ICST 2016 Best Industry Paper at ICST 2024 ACM SIGSOFT Distinguished Paper at ISSTA 2023 ACM SIGPLAN Most Influential OOPSLA Paper Award (2012 paper), awarded in 2022 Best Student Paper at PPoPP 2014 He has advised numerous PhD students and leads a vibrant research group. He has secured significant research funding and collaborates extensively with industry and academia. His service includes leadership roles such as General Chair of PLDI 2020, PC Chair of ECOOP 2019, and Steering Committee Chair of PLDI (2022–2025). He also serves on the advisory board of PACM-PL and on program committees for top venues including POPL, OOPSLA, PLDI, ICSE, and ISSTA. He leads the FastPL research group, which focuses on the design and implementation of programming tools and techniques for reliable software. The group conducts cutting-edge research in compiler testing, formal methods, and high-performance systems, fostering collaboration across academia and industry.

Caroline Trippelمشاهده پروفایل

استادیار

• Computer Architecture
• Hardware Security
• Formal Methods
• +۵ مورد دیگر

Caroline Trippel is an Assistant Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. Her research focuses on ensuring correctness and security in computer systems through formal methods, with particular emphasis on hardware verification, memory consistency models, and mitigating vulnerabilities like Spectre/Meltdown. She previously worked at Facebook’s FAIR SysML group before joining Stanford. Education: PhD in Computer Science, Princeton University BS in Computer Engineering, Purdue University Her work has influenced the RISC-V ISA memory consistency model and produced tools like CheckMate, which automatically synthesizes hardware exploits for security verification. She explores privacy-preserving ML, ML-driven hardware optimizations (e.g., neural recommendation), and datacenter reliability. Her research has earned awards including the 2020 ACM SIGARCH Dissertation Award and NVIDIA Fellowship. Key contributions include: Formal analysis of RISC-V memory models Exploitation synthesis frameworks (CheckMate) Hardware-software contracts for security Defenses against microarchitectural side-channel attacks Current projects include: VeriCoder: LLM-enhanced RTL code verification Multi-μPATH synthesis for security validation Near-data processing (RecSSD) for recommendation systems

Oliver Crönertzمشاهده پروفایل

استاد

• Digital Transformation
• Business Analytics
• Industry 4.0 Technology Potentials
• +۴ مورد دیگر

Prof. Dr. Oliver Crönertz serves as Dean and Professor of Business Administration and IT-Supported Business Processes at the Faculty of Digital Transformation , HTWK Leipzig. His work bridges digital transformation with business management, focusing on interdisciplinary project management, digital business models, and sustainability. Current roles: Dean, supervising professor for HTWK Robots/nao Team Research areas: Digital Transformation, Business Analytics, Industry 4.0, Stoffstrommanagement Research Trends : Recent publications emphasize digital solutions for environmental management, business process optimization, and smart urban logistics. His work connects Industry 4.0 with financial sustainability and societal impacts of digitalization. Projects : Leads Mittelstand-Digital Zentrum Leipzig-Halle, involved in EXIST-Potentiale, Future Parking, and FAssMII (Feedback-based E-Assessment in STEM).

• Organic Chemistry
• Glycobiology
• Plant Biology
• +۳ مورد دیگر

Fabian Pfrengle is a full Professor of Organic Chemistry at the Institute of Organic Chemistry , Department of Natural Sciences and Sustainable Resources , University of Natural Resources and Life Sciences Vienna (BOKU). He previously led research groups at the Max Planck Institute of Colloids and Interfaces (2013-2020) and worked at The Scripps Research Institute (2010-2013). Research Focus: His work bridges carbohydrate chemistry and plant biology , specializing in plant cell wall glycans and glycosyltransferases . He develops synthetic glycan arrays for enzyme characterization and investigates immune response triggering mechanisms in plants through oligosaccharide fragments . His projects include automated polysaccharide synthesis and liposome-based immune tolerance applications. Publication Trends: His 15 most recent articles emphasize chemical synthesis of sugar nucleotides , plant glycan arrays , and enzyme specificity analysis , reflecting his focus on carbohydrate engineering and plant immunity . Key subfields include UDP-sugar derivatization , Xylan structure-function relationships , and Glycosyltransferase profiling . Grants & Projects: Currently leads 5 major projects including Automated Algal Polysaccharide Synthesis (EU-funded, 2023-2028) and Synthetic Glycan Ligands for Plant Immune Receptors (FWF-funded, 2022-2026). His research also explores thrombocyte biology and Rhamnogalacturonan-II fragments with support from FWF and City of Vienna . Community Service: Serves on editorial boards ( Monatshefte für Chemie , 2021-present) and as reviewer for 12 journals including JACS Au , Nature Communications , and Angewandte Chemie . Member of professional societies: Gesellschaft Österreichischer Chemiker (2020), Deutscher Hochschulverband (2019), and Gesellschaft Deutscher Chemiker (2008).

• Battery simulation
• Cyber physical system
• Design simulation
• +۱۲ مورد دیگر

Sara Vinco is an Associate Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy. She specializes in battery simulation, digital twins, and energy-efficient design automation for heterogeneous embedded systems, aligning with Industrial and Information Engineering (Area 0009) and ERC sectors including Computer Architecture and Machine Learning . Her research focuses on advancing cyber-physical systems through simulation frameworks like SystemC-AMS, enabling holistic modeling of analog, digital, and thermal domains. Key projects include data-driven digital twins for EV batteries and low-area digital circuits in industrial/medical applications, supported by commercial contracts such as C-based virtual prototyping. Her recent publications (2022-2023) emphasize machine learning for battery SOH/SOC estimation , energy monitoring in production lines , and multi-domain fault modeling . These works span journals like IEEE Transactions and conferences including DATE and ISLPED. Awarded the FFABR 2017 grant and IEEE FDL Best Paper Award 2011 , she also chairs editorial boards for IEEE Transactions on CAD and DATE Conference. She supervises PhD students Giovanni Pollo (Digital Circuits) and Khaled Alamin (EV Battery Twins), reflecting her leadership in smart systems design.

Vincent Dufour-Décieuxمشاهده پروفایل

پژوهشگر

• Materials Science
• Computational Chemistry
• Environmental Engineering
• +۵ مورد دیگر

Vincent Dufour-Décieux is a researcher at the Professorship for Energy and Process Systems Engineering at ETH Zürich , focusing on developing computational methods for material screening in separation processes and global net-zero transitions. He earned his Master's in Materials Chemistry from Ecole Polytechnique (France) and a PhD in Materials Science from Stanford University , where he pioneered statistical methods combining Kinetic Monte Carlo and random graph theory to study planetary diamond formation. Research Highlights: Application of Classical Density Functional Theory (cDFT) for 100x faster adsorption property predictions in porous materials Development of science-based definitions for "hard-to-abate" emissions to guide climate action prioritization Integration of Coulombic interactions in cDFT for CO2 adsorption accuracy Article Trends : His work spans computational materials science (cDFT, random graph theory) and climate policy analysis, with recent publications in Joule , AIChE Journal , and Physical Review E . These studies emphasize scalable solutions for carbon capture, material screening efficiency, and accurate thermodynamic modeling. Collaborations : Active in international conferences (FOA15, MolMod, Gordon Research Conference) and cross-institutional projects with teams at Stanford, ETH Zürich, and industry partners.

Ryan Caloمشاهده پروفایل

استاد

• Law and Technology
• Privacy Law
• Artificial Intelligence Policy
• +۷ مورد دیگر

Ryan Calo is the Lane Powell & D. Wayne Gittinger Professor of Law at the University of Washington School of Law, with joint appointments at the Information School and adjunct roles at the Paul G. Allen School of Computer Science and Engineering. He co-founded the UW Tech Policy Lab and Center for an Informed Public, focusing on technology policy, data privacy, and AI ethics. His research explores the intersection of law and technology, emphasizing AI regulation, surveillance law, and privacy harms. Key themes include legal indeterminacy in tech policy, ethical challenges of autonomous systems, and market manipulation in digital economies. His work spans law reviews, technical journals, and policy reports. Ryan Calo's articles highlight critical gaps in AI governance, surveillance frameworks, and robotics law. His publications address algorithmic bias, cultural responsiveness in AI, and legal implications of autonomous vehicles, with recurring focus on consumer protection, constitutional challenges, and cross-disciplinary policy solutions. Phillip A. Trautman 1L Professor of the Year Award (2014, 2017) Washington Law Review Faculty Award (2019) As a public intellectual, Calo has testified before the U.S. Senate multiple times, including on AI-driven privacy risks. He serves on advisory boards for major tech policy organizations and frequently appears in media discussing AI ethics, data breaches, and constitutional tech regulation.

• Journalism and Communication
• Intelligent Communication
• Digital Media Art
• +۶ مورد دیگر

Wang Jianmin serves as Professor and Doctoral Supervisor at Tongji University's School of Art and Media, concurrently holding the position of Vice Dean since 2014. With a computer science PhD from Sun Yat-sen University, he bridges engineering and media arts through pioneering research in intelligent communication systems and digital media interfaces. His work focuses on human-centered design for emerging technologies, particularly in automotive and virtual environments. His academic foundation includes: PhD in Engineering (Computer Software and Theory), Sun Yat-sen University (2003) Master's in Computational Mathematics, Sun Yat-sen University (1999) Bachelor's in Computational Mathematics, Nankai University (1996) Professor Wang's research centers on intelligent communication systems and digital media art, with significant contributions to automotive human-machine interfaces (HMI), virtual reality applications, and user experience methodologies. His investigations into driver-robot transparency, augmented reality navigation, and mixed-reality educational platforms demonstrate interdisciplinary innovation connecting computer science, cognitive psychology, and design theory. Current projects explore AI-driven media systems for urban environments and safety-critical interaction frameworks. Analysis of his recent publications reveals a cohesive research trajectory focusing on automotive HMI (40% of output), human-robot interaction (30%), and mixed reality applications (30%). His work consistently emphasizes experimental validation through driving simulators and user studies, yielding practical design guidelines for industry implementation. The interdisciplinary nature spans computer science, cognitive ergonomics, and media studies, with increasing emphasis on AI integration in communication systems. His scientific recognition includes national and provincial awards for innovation in human-computer interaction and educational technology: 2019 China Industry-University-Research Innovation Award for automotive HMI systems 2020 China User Experience Alliance Excellence Award 2012 Guangdong Dingying Science and Technology Award Multiple national/provincial science progress awards (2001-2009) 2020 Tongji University Teaching Achievement Award for curriculum development As an educator, Professor Wang mentors graduate students in national design competitions including the 'Core Cup' Future Automotive HMI Challenge and International User Experience Innovation Competition. His research program is supported by substantial funding from diverse sources: National Grants: National Natural Science Foundation projects on driver behavior modeling and cognitive testing Ministry of Education: 15+产学合作 projects for virtual simulation labs and curriculum development Shanghai Municipal: Publicity Department funding for smart city media research Industry Partnerships: Huawei (intelligent vehicle HMI), SAIC Motor (AR-HUD design), and automotive electronics firms He directs Tongji's Media Experiment and Practice Teaching Center and the All-Media Research Institute, leading teams developing virtual simulation platforms for emergency news reporting, intelligent vehicle interaction testing systems, and mixed reality educational tools. Current initiatives focus on AI-enhanced media art for urban applications and next-generation HMI frameworks for autonomous mobility solutions.

Alexander Kollerمشاهده پروفایل

استاد

• Computational Linguistics
• Neural-Symbolic Models
• Semantic Parsing
• +۵ مورد دیگر

Professor Alexander Koller is a leading academic in Computational Linguistics at Saarland University's Department of Language Science and Technology. He holds a courtesy appointment in Computer Science and contributes to the Saarland Informatics Campus - one of Europe's premier computer science research centers. He leads the Computational Linguistics group and serves as speaker for the DFG-funded Research Training Group 'Neuroexplicit Models of Language, Vision, and Action'. PhD in Computer Science (Saarland University) Former positions: University of Potsdam, Columbia University, University of Edinburgh Sabbatical experiences: Meta AI (Paris), Allen Institute for AI (Seattle) His research focuses on computational modeling of meaning and reasoning in NLP, combining neural and symbolic approaches. Key contributions include semantic parsing systems like the AM parser and Alto, neurosymbolic models, and the GIVE Challenge for NLG evaluation. His recent work explores LLMs' limitations in problem-solving and compositional generalization. Recent publications highlight diverse applications across semantic parsing, dialogue systems, and LLM evaluation. Awards include ACL 2020 Best Theme Paper and multiple Outstanding Paper recognitions at ACL conferences. 2025 - AI Action Summit keynote speaker 2023 - ACL Outstanding Paper Awards 2022 - ELLIS Faculty appointment He maintains the DialogOS system for spoken dialogue development and teaches advanced computational linguistics topics. His group includes multiple postdocs and PhD students working across LLMs, dialogue systems, and semantic modeling.

• Medical Physics
• Artificial Intelligence in Medicine
• Radiation Therapy Treatment Planning
• +۷ مورد دیگر

Dan Nguyen, Ph.D., is a faculty member in the Department of Radiation Oncology at UT Southwestern Medical Center, where he is part of the Division of Medical Physics and Engineering. He is a founding member of the Medical Artificial Intelligence and Automation (MAIA) Laboratory, collaborating closely with Dr. Steve Jiang to advance AI applications in radiotherapy. His work focuses on deep learning for treatment planning, dose prediction, auto-segmentation, and adaptive radiotherapy. Ph.D. in Biomedical Physics, University of California, Los Angeles (UCLA), 2017 Mentor: Dr. Ke Sheng Faculty appointment at UT Southwestern since 2017 Dr. Nguyen’s research is centered on applying artificial intelligence to solve critical challenges in radiation oncology. His primary interests include deep learning-based dose prediction, auto-segmentation of anatomical structures, optimization of treatment plans, and real-time adaptive radiotherapy. He has pioneered work in direct aperture optimization, 4π radiotherapy, and uncertainty quantification in AI models. His research bridges the gap between AI innovation and clinical implementation, with a focus on improving plan quality, reducing planning time, and enhancing accessibility for less experienced clinicians. The most recent publications (2023–2025) demonstrate a consistent trend in developing fast, accurate, and robust deep learning models for radiotherapy. Key themes include dose prediction with transfer and meta-learning, adaptive segmentation using test-time optimization, uncertainty assessment in AI predictions, and mathematical modeling of radiotherapy-immunotherapy synergy. These works span high-impact journals in medical physics, AI, and oncology, reflecting interdisciplinary innovation. While no specific scientific awards are listed, Dr. Nguyen’s leadership in the MAIA Lab and extensive publication record in top-tier journals indicate significant recognition in the field of medical physics and AI in medicine. Dr. Nguyen has co-authored numerous studies involving mentoring and collaborative research, particularly with trainees and junior faculty in the MAIA Lab. His work is supported by institutional and likely federal funding, given the scale and scope of AI deployment studies. He has contributed to large-scale collaborative efforts such as OpenKBP-Opt, involving international teams evaluating knowledge-based planning pipelines. The MAIA Laboratory is a multi-investigator research group focused on innovating, developing, and applying artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. The lab’s work spans machine learning, deep learning, reinforcement learning, and mathematical modeling in radiation oncology.

Michael Ellisمشاهده پروفایل

دانشیار

• Fuel Cell Systems
• Energy Systems Modeling
• Building Energy Consumption
• +۸ مورد دیگر

Michael Ellis is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech since 2012, with prior roles as Associate Professor and John R. Jones Faculty Fellow (2007–2012). His work spans fuel cell systems, energy modeling, and sustainable technologies. Ph.D. , Mechanical Engineering, Georgia Institute of Technology (1996) M.S. , Mechanical Engineering, Georgia Institute of Technology (1993) B.S. , Mechanical Engineering, University of Tennessee (1985) Research interests include fuel cell systems for building cogeneration, energy consumption modeling, industrial process analysis, and optimal hybrid energy system design. Recent work focuses on battery recycling processes, microbial fuel cells, and thermal stress characterization of membranes. His 15 most recent publications highlight trends in battery recycling scalability , fuel cell durability , microbial energy conversion , and nanomaterials for energy applications . Key subfields include membrane stress modeling, microbial adhesion mitigation, and hybrid gas/electric system optimization. Excellence in Architecture Award (2006) Woodruff Teaching Fellowship (1995) Tau Beta Pi Member Multiple teaching awards at Virginia Tech (2000–2003) As faculty advisor for the award-winning Solar Decathlon team (2002), he contributed to interdisciplinary energy projects. His work connects mechanical engineering with sustainable energy systems, focusing on practical implementations and material innovations.

• Mechanical Engineering
• Energy Systems
• Hydraulic Engineering
• +۳ مورد دیگر

Jyrki Kajaste is a Lecturer at the Department of Energy and Mechanical Engineering, Aalto University. His academic career focuses on mechanical engineering and energy systems, with a strong emphasis on fluid power and hydraulic technologies. His research bridges theoretical and applied engineering, particularly in sustainable energy solutions and mechatronic systems. Research Focus: Mechanical Engineering, Fluid Power, Sustainable Energy Key Projects: CO2 adsorption heat engines, hydraulic system optimization, energy-efficient machinery Jyrki's publications highlight advancements in hydraulic systems, pneumatic efficiency, and additive manufacturing. His collaborations span international conferences like SICFP and the Baltic Mechatronics Symposium, showcasing interdisciplinary applications of mechanical engineering principles.

Arash Joorabchiمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Educational Technology
• +۴ مورد دیگر

Arash Joorabchi is an Assistant Professor at the Department of Electronic and Computer Engineering, Faculty of Science and Engineering, University of Limerick, Ireland. His research focuses on the intersection of machine learning, educational technology, and digital library systems, with particular emphasis on automated assessment, text mining, and knowledge organization techniques. Research Trends: Analysis of his publications reveals sustained contributions to automated short-answer grading, Arabic text classification, and semantic integration of Wikipedia with academic resources. Key methodologies include sentence transformers, hybrid text representation models, and citation-based indexing techniques. Technical Domains: His work spans natural language processing, educational data mining, metadata management, and semantic web technologies. Specific applications include Q&A platform analysis, library resource discovery, and curriculum development systems.

Soeren Lienkampمشاهده پروفایل

استادیار

• Molecular Biology
• Genetics
• Developmental Biology
• +۵ مورد دیگر

Prof. Dr. Soeren Lienkamp is an Assistant Professor at the Institute of Anatomy , Faculty of Medicine , University of Zurich . His work bridges digital education and genetic research , focusing on enhancing medical teaching through innovative formats. Research Interests : Genetics, developmental biology, kidney disease modeling, CRISPR applications, digital medical education, and advanced microscopy. Methodologies : Combines Xenopus tropicalis models, deep learning , and bioengineering to study genetic kidney disorders and improve diagnostic tools. Publication Trends : His recent articles highlight predictable genome editing , 3D imaging technologies , and mechanistic insights into kidney and eye development. Earlier works focus on ciliary function , Wnt signaling , and metabolic stress in renal cells.