جست‌وجوی استاد و پژوهشگر

Ori Lahavمشاهده پروفایل

دانشیار

• Programming Languages
• Verification
• Concurrency
• +۴ مورد دیگر

Ori Lahav is a faculty member in the School of Computer Science at Tel Aviv University. His research is generously supported by an ERC Starting Grant and an ISF Grant. He actively supervises PhD and MSc students, and seeks highly motivated candidates for postdoc, PhD, and MSc positions in programming language theory, concurrency, and formal methods. Dr. Lahav completed his PhD at Tel Aviv University under the supervision of Arnon Avron. In 2014, he was a postdoctoral researcher at Tel Aviv University hosted by Mooly Sagiv. From 2014 to September 2017, he was a postdoctoral researcher at MPI-SWS in Germany hosted by Viktor Vafeiadis and Derek Dreyer. His primary research areas focus on programming languages and verification, with specialization in concurrency and relaxed memory models. He also has significant interests in proof-theory, semantics of non-classical logics, and automated reasoning. His work bridges theoretical foundations with practical applications in programming language design and implementation. Dr. Lahav's publication record shows a consistent trajectory of high-impact research in top-tier conferences including PLDI, POPL, OOPSLA, and ESOP. His recent work (2023-2025) demonstrates continued leadership in memory models, concurrency semantics, and verification techniques. His research spans both theoretical contributions in denotational semantics and practical tools for verification. Best Paper Award DISC 2024 Best Student Paper Award DISC 2024 Distinguished Artifact Award ESOP 2022 Distinguished Paper Award OOPSLA 2021 Kleene Award for Best Student Paper LICS 2013 Dr. Lahav actively advises students including Yoav Ben Shimon, Yotam Dvir, Amir Karniel, and Roy Margalit (PhD students), Yuval Katsman Ezra (MSc student), and has alumni including Ori Saporta (MSc) and Abhishek Kr Singh (postdoc, now Assistant Professor at IIIT Hyderabad). He has organized significant events including VMCAI 2024 and Dagstuhl Seminars on persistent programming. His teaching portfolio includes courses on Shared Memory Concurrency Semantics, Programming Language Foundations, and Software Foundations in Coq.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Lung-Pan Cheng is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University, where he leads the Human-Computer Interaction Laboratory. His research focuses on bridging the gap between physical and virtual realities through innovative interface technologies. Cheng's research expertise spans human-computer interaction, augmented/virtual reality, and tactile feedback systems. His work explores how people exist across three types of reality: physical reality governed by physics, imagined realities where things act by wishes, and programmable virtual realities. By examining the mismatches between these realities, Cheng develops novel interfaces, techniques, and devices that extend and interface these realities toward an ultimate unified experience. His recent publications reveal strong trends in haptic feedback systems, procedural generation in VR, and tangible interaction techniques. Cheng's work often involves creating physical props and mechanisms that enhance virtual experiences, with a particular focus on how humans can interact with and manipulate virtual objects through physical interfaces. His research has significant implications for VR training, gaming, and therapeutic applications. Best Paper Award at CHI 2022 for AirRacket: Perceptual Design of Ungrounded, Directional Force Feedback to Improve Virtual Racket Sports Experiences SIC People's Choice Award at UIST 2022 for Garnish into Thin Air Cheng has secured numerous research grants supporting his work in VR and haptic interfaces, with collaborations spanning multiple institutions. His laboratory develops working prototypes that demonstrate practical applications of his theoretical concepts, often resulting in award-winning publications at top HCI conferences. Current projects appear to focus on advanced fabrication techniques for interactive objects, perceptual illusions in VR, and novel haptic feedback mechanisms that don't require traditional grounded hardware. The Human-Computer Interaction Laboratory under Cheng's direction consists of graduate students and researchers working on various aspects of tangible and virtual interfaces. The team frequently publishes in premier venues like CHI, UIST, and IEEE VR, demonstrating consistent productivity and impact in the field. Current research directions include density-varying soft fabrication, polarized light mosaics, and systems for creating infinite virtual spaces within limited physical environments.

• Construction Engineering
• Simulation Science
• Information Technology in Construction
• +۳ مورد دیگر

Simaan Abourizk, PhD, PEng, is the Dean of the Faculty of Engineering at the University of Alberta and holds the rank of Professor in Construction Engineering and Management. He also served as the NSERC/Alberta Construction Industry Research Chair (1997–2011) and Canada Research Chair in Operations Simulation (2001–2008). His roles include Executive Board membership at the Construction Research Institute of Canada. Education: Doctor of Philosophy in Construction Engineering and Management from Purdue University (1990), Master of Science and Bachelor of Civil Engineering (Honors) from Georgia Institute of Technology (1985 and 1984). Research focuses on advancing simulation technologies for construction and natural resource industries, including: Development of the Simphony simulation environment and COSYE framework Integration of AI, visualization, and scheduling tools (e.g., SmartEst, MTRACK) Optimization of tunneling, modular assembly, and industrial fabrication processes Key awards include the E. Whitman Wright Award (2002), E.W.R. Steacie Memorial Fellowship (2001), and Walter Shanly Award (2001). Current projects emphasize synthetic environments, safety analytics, and data-driven decision support systems in construction. He leads initiatives on risk simulation, resource allocation, and industrial automation.

Qingjin Pengمشاهده پروفایل

استاد

• Product Design and Manufacturing
• Digital Manufacturing
• Design Methodology
• +۵ مورد دیگر

Qingjin Peng is a Professor in the Department of Mechanical Engineering at the University of Manitoba’s Price Faculty of Engineering. His work focuses on Product Design and Manufacturing, with expertise in Digital Manufacturing, Design Methodology, and Virtual Reality applications. He holds a PhD from the University of Birmingham (1998) and master’s and bachelor’s degrees from Xi’an Jiaotong University (1988, 1982). Education: PhD in Mechanical and Manufacturing Engineering, University of Birmingham (1998) M.Sc. Mechanical and Manufacturing Engineering, Xi’an Jiaotong University (1988) B.Sc. Mechanical and Manufacturing Engineering, Xi’an Jiaotong University (1982) Research Interests: His research spans Digital Manufacturing, Product Assembly/Disassembly Planning, CAD/CAM systems, and System Modeling. He pioneered methods integrating AI (e.g., Reinforcement Learning, Machine Learning) into product design and manufacturing processes. Notable contributions include optimizing Additive Manufacturing parameters using Taguchi methods and developing VR-based training systems for Coordinate Measuring Machines. Publications: Recent work emphasizes AI-driven innovation in manufacturing, with focus areas including sustainability in Additive Manufacturing, fault diagnosis of rotating machinery, and multi-agent systems for concept evaluation. His 2024 studies highlight advancements in product design through radical problem-solving frameworks, causal chain analysis, and genetic algorithm optimization. Advising & Grants: Currently no graduate student opportunities are listed, but his past collaborations include projects funded by national grants. Research teams often involve interdisciplinary partnerships, leveraging AI and data-driven approaches. Labs/Teams: His lab focuses on Digital Manufacturing and AI applications, though specific team names are not explicitly mentioned in the provided text.

Adarsh Pyarelalمشاهده پروفایل

استادیار

• Artificial social intelligence
• Automated causal model assembly
• Machine learning
• +۳ مورد دیگر

Adarsh Pyarelal is an Assistant Professor at the School of Information , University of Arizona. His research focuses on socially-aware AI teammates, automated assembly of causal models from text/software, and probabilistic modeling of human coordination. He holds a Ph.D. and has contributed to projects like MultiCAT and Eidos/INDRA/Delphi frameworks. His work spans multimodal dialogue systems, variable extraction from scientific literature, and applications in particle physics collaborations. Notable contributions include the Future Circular Collider feasibility studies and vector quantization techniques in reinforcement learning. Despite numerous grant proposal rejections (noted in his Shadow CV), his research emphasizes resilience in academic pursuits. Current focus areas include AI team coordination and improving model interpretability through causal frameworks. He does not currently accept new PhD students. Technical interests include cross-platform GUI libraries (wxWidgets), MacPorts Python management, and reproducible research workflows using Pandoc/Zotero.

Kyoung-Yun Kimمشاهده پروفایل

استاد

• Design Science
• Design Informatics
• Semantic Assembly Design
• +۴ مورد دیگر

Dr. Kyoung-Yun Kim is a Professor in the Department of Industrial and Systems Engineering at Wayne State University's College of Engineering, where he directs the Computational Intelligence and Design Informatics (CInDI) Laboratory and serves as Director of the Smart Manufacturing Demonstration Center (SMDC). He holds a PhD from the University of Pittsburgh and BS/MS from Chonbuk National University, South Korea. As a Fellow of the Society for Design and Process Science (SDPS) and Editor-in-Chief of the Journal of Integrated Design and Process Science, Dr. Kim leads research in design science, semantic assembly modeling, and smart manufacturing. Research Focus: His work integrates ontology-based design, welding/joining technologies, and cyber-physical systems. Key domains include: Semantic reasoning for CAD/CAE systems Data-driven weldability certification Industrial IoT in manufacturing Sustainable product lifecycle management Human-machine collaboration frameworks Publication Trends: Recent articles (2020-2023) demonstrate strong emphasis on AI-driven manufacturing analytics, ontology-based knowledge systems, and cyber-physical integration. Earlier foundational work established novel methods for collaborative assembly design and robotic welding optimization. Awards & Honors: Fellow, Society for Design and Process Science (2017) Top Cited Article Award, Journal CAD (2005-2010) IIE Transactions Best Paper Award (2003) Google Scholar Classics in Manufacturing 1st Place, Center for e-Design Best Poster (2019) Leadership & Grants: Secured over $10M in funding from NSF, DOD, NIST, and industry partners (Ford, GM). Directs NSF I/UCRC for e-Design and co-leads the $3.8M NIST Rx Marketplace Orchestrator project. Educational innovations include NSF-supported curricula in sustainable design and smart manufacturing. Labs & Teams: Leads the CInDI Lab focusing on computational intelligence in design. Coordinates multi-institutional teams with Oregon State, Iowa State, and international collaborators (France, South Korea) for Industry 4.0 initiatives.

Gus Hahn-Powellمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Gus Hahn-Powell is an Assistant Professor in the Department of Linguistics at the University of Arizona. He directs the online MS in Human Language Technology (HLT) and the Graduate Certificate Program in Natural Language Processing (NLP). He holds affiliate appointments in the College of Information Science, Cognitive Science GIDP, and Computational Social Science Program. His research focuses on machine reading systems to address scientific information overload, enabling automated discovery through analysis of scientific literature. Education: PhD in Computational Linguistics (University of Arizona), MS in Human Language Technology (UA), MA in Applied Linguistics (University of Alabama), BA in Japanese (UA). Research interests include AI-driven systems for knowledge synthesis, natural language processing, and causal graph generation from texts. His work bridges computational linguistics with information science, emphasizing practical applications in scientific discovery. Recent publications span neural-guided program synthesis, causal graph frameworks, and rule-based information extraction tools like Odinson. No scientific awards listed. Advising and grants: He oversees HLT/MSCS programs but no specific grants or advisees listed here. Collaborative efforts include developing tools for multilingual causal interaction analysis and stakeholder performance modeling. Labs/Teams: Directs the HLT program and collaborates on projects involving interdisciplinary teams across linguistics, computer science, and information science.

Clayton Morrisonمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Causal Inference
• +۳ مورد دیگر

Clayton Morrison is an Associate Professor at the University of Arizona, specializing in artificial intelligence and machine learning. His research focuses on machine learning, probabilistic modeling, causal inference, knowledge representation, and automated planning. He is affiliated with the Core Faculty and PhD Faculty in Artificial Intelligence and Machine Learning programs. His recent work emphasizes information extraction from scientific literature, legal documents, and code binaries, leveraging neural networks and generative models. Notable projects include the Eidos, INDRA, and Delphi systems for causal model recovery and the Tomcat dataset for benchmarking. His research bridges theoretical advancements with practical applications in 3D texture generation, lightweight object detection, and code synthesis. He has contributed to over 60 peer-reviewed articles spanning machine learning, computer vision, and computational linguistics. His work often addresses interdisciplinary challenges such as linking mathematical formulas to textual descriptions (MathAlign) and modeling biological event contexts in biomedical texts. Morrison's lab focuses on creating AI systems that can autonomously learn from complex data, with applications in automated model assembly (Automates) and federated learning frameworks. His research has been supported by grants exploring reinforcement learning, multi-hop inference, and explainable AI.

Nitin Baligaمشاهده پروفایل

استاد

• Systems Biology
• Gene Regulatory Networks
• Microbial Communities
• +۶ مورد دیگر

Nitin Baliga is Senior Vice President, Director, and Professor at the Institute for Systems Biology (ISB), with a joint appointment as Professor of Microbiology at the University of Washington. His research spans systems biology, environmental science, and medicine, focusing on developing predictive models of complex biological systems to advance personalized medicine and environmental sustainability. Dr. Baliga's work centers on understanding how biological information within DNA is decoded into observable phenotypes through environmental interactions. His lab develops predictive models to explain, predict, and manipulate complex biological behaviors. Key research areas include: Deciphering engineering principles governing biological system assembly Developing patient-specific disease-relevance network maps for cancer treatment Studying climate change impacts on coral reefs and marine diatoms Investigating syntrophic interactions in microbial communities Mapping gene regulatory networks across diverse organisms His recent publications reveal a strong interdisciplinary focus bridging computational biology with real-world applications. Significant work includes genetic program activity models for multiple myeloma risk assessment, coral bleaching research using the Coral Bleaching Automated Stress System (CBASS), and studies on diatom resilience in acidified oceans. His research demonstrates how systems-level approaches can predict complex biological behaviors across diverse contexts from cancer to climate change impacts. Dr. Baliga has secured major funding including a $4 million grant from the Paul G. Allen Family Foundation to identify naturally resilient corals for conservation efforts. His work on coral bleaching has demonstrated how identifying heat-tolerant corals can help preserve reef ecosystems facing climate change. As leader of the Baliga Lab at ISB, Dr. Baliga oversees a multidisciplinary team working on diverse projects spanning cancer research, climate change impacts, and microbial community dynamics. His lab has developed important resources including the Diatom Portal for studying diatom gene regulation and network models that integrate multi-omics data across biological scales.

Vignesh Narayananمشاهده پروفایل

استادیار

• Dynamical Systems
• Artificial Intelligence
• Computational Neuroscience
• +۴ مورد دیگر

Vignesh Narayanan is an Assistant Professor in the Artificial Intelligence Institute (AII) and Department of Computer Science and Engineering at the University of South Carolina (USC), with affiliations to the Carolina Autism and Neurodevelopment (CAN) Research Center. He bridges AI with dynamical systems theory, computational neuroscience, and cyber-physical systems (CPS) to enhance safety and efficiency in human-AI collaboration. Education: B.Tech (SASTRA University, India, 2012), M.Tech (National Institute of Technology, India, 2014), Ph.D. (Missouri University of Science and Technology, 2017), Postdoc (Washington University in St. Louis, 2017-2021) His research spans dynamic modeling , AI integration , and neuroscience-inspired systems . Key projects include: Developing safety-constrained virtual health assistants using knowledge graphs to align with medical protocols Advancing collaborative autonomy for drones/vehicles through event-triggered control mechanisms Creating digital twins for opinion dynamics to analyze information propagation in social systems Designing quantum-echo state networks for chaotic system prediction on NISQ hardware Recent publications demonstrate expertise in reinforcement learning for battery health monitoring ( 2024 ), reservoir computing for time series reconstruction ( 2025 ), and knowledge-infused AI frameworks for explainable decision-making. His lab team includes researchers like Bharath Muppasani and Erik Connerty, while recent grants from NSF , AFOSR , and DoD fund projects on collaborative autonomy and secure cyber-physical control.

Brent Cochranمشاهده پروفایل

استاد

• Cancer Biology
• Glioblastoma
• Jak-Stat Signal Transduction Pathway
• +۵ مورد دیگر

Brent Cochran is a Professor at Tufts University School of Medicine in the Department of Developmental, Molecular and Chemical Biology. His research focuses on understanding how cell growth and differentiation pathways are disrupted in cancer, particularly glioblastoma stem cells. Discovered the Jak-Stat signal transduction pathway First to isolate human glioblastoma stem cell lines Developed RNAi screening methods for cancer stem cell research DIRECTOR OF CELL, MOLECULAR AND DEVELOPMENTAL BIOLOGY PROGRAM (2018-2023) EDUCATION: PhD in Molecular Biology from Harvard University (1984) BS in Biology from MIT (1978) RESEARCH HIGHLIGHTS: STAT3 signaling in cancer stem cells Protein network modeling Multi-omics data integration Dynamic causal modeling of tumor systems He teaches Endocrinology to medical and graduate students and directs the first-year journal club. His grants include funding from National Science Foundation , DARPA , and NINDS . Professional memberships span AACR , ISSCR , and Society for Neuro-Oncology .

Pablo Martinez Rodriguezمشاهده پروفایل

استادیار

• Industrialized Construction
• Robotics and Automation
• Computer-aided Process Planning
• +۴ مورد دیگر

Dr. Pablo Martinez Rodriguez is an Assistant Professor at Northumbria University's Architecture and Built Environment Department. He specializes in multi-disciplinary engineering, focusing on Industry 4.0 integration in low-digitalized sectors like construction and agriculture. His research emphasizes industrialized construction, robotics automation, lean manufacturing, and precision farming. Education: BEng in Electromechanical Engineering (Comillas Pontifical University), MSc in Mechanical Engineering (University of Alberta), and PhD in Civil and Environmental Engineering (University of Alberta). Previously held roles include NSERC post-doctoral fellow and International Visiting Professor at Tecnologico de Monterrey. Research Interests: Industrialized Construction (Modern Methods of Construction), Robotics & Automation, Computer-aided Process Planning, Lean Manufacturing, Waste Management, and Precision Farming Automation. His work addresses challenges in smart safety systems, digital twins, and sustainable construction practices. Key Projects: Developed an IALF-certified learning factory, created ontology-based safety management tools, and advanced aquaponics 4.0 systems. Recent articles highlight digital twin applications, gamified safety training, and AI-driven generative design. Grants & Collaboration: Active in organizing international conferences like the Modular and Offsite Construction Summit. Supervises PhD students and collaborates on projects aligning with UN Sustainable Development Goals, particularly education and sustainable cities. Labs/Teams: Leads the AllFactory transdisciplinary educational facility focusing on aquaponics 4.0 and smart manufacturing systems. Engages in cyber-physical systems research for zero-defect production.

Stephen Chongمشاهده پروفایل

استاد

• Programming languages
• Information security
• Language-based security
• +۳ مورد دیگر

Stephen Chong is a Gordon McKay Professor of Computer Science in the Harvard John A. Paulson School of Engineering and Applied Sciences, where he serves as Co-Director of Undergraduate Studies for Computer Science. His academic career spans over a decade of teaching and research at Harvard, where he has made significant contributions to programming languages and information security. Chong received his PhD from Cornell University under the guidance of Andrew Myers, and a bachelor's degree from Victoria University of Wellington, New Zealand. Prior to graduate school, he worked as a consultant and contractor in the software industry, bringing practical experience to his academic research. Professor Chong's research focuses on language-based information security, using programming language techniques to provide information security assurance. His work bridges the gap between theoretical foundations and practical applications, developing tools and frameworks that help programmers write trustworthy programs. His research has evolved to address increasingly complex security challenges in modern computing environments, from web applications to cyber-physical systems. His recent publications reveal a strong trend toward integrating advanced programming language techniques with security analysis, particularly through the use of Datalog, SMT solvers, and program synthesis. His work on Formulog has been particularly influential, extending Datalog with mechanisms to construct and reason about SMT formulas for static analysis. His research has expanded to address security challenges in cyber-physical systems, where sensor attacks pose unique threats to safety-critical infrastructure. Chong has received numerous prestigious awards including an NSF CAREER award, an AFOSR Young Investigator award, and a Sloan Research Fellowship. He has also served in leadership roles for major conferences including CSF 2012-2013, PLMW @ PLDI 2021, and as SIGPLAN-M Chair for 2025-2026. As an educator, Chong has mentored numerous students through Harvard's undergraduate research programs and has served as a thesis advisor. His teaching portfolio includes foundational courses like CS51, systems courses like CS61, and advanced topics in programming languages (CS152) and compilers (CS1530). He has been instrumental in shaping Harvard's computer science curriculum, particularly in security and programming languages. Chong leads a research group focused on language-based security, with projects including Formulog (for SMT-based static analysis), PRINCESS (for autonomous adaptation of software), and work on secure shell scripting (Shill). His group collaborates with researchers across Harvard and other institutions to tackle challenging problems at the intersection of programming languages and security.

Ori Lahavمشاهده پروفایل

استاد

• Programming Languages
• Verification
• Concurrency
• +۴ مورد دیگر

Ori Lahav is a faculty member in the School of Computer Science at Tel Aviv University. He holds a PhD from Tel Aviv University (supervised by Arnon Avron), completed postdoctoral research at Tel Aviv University (hosted by Mooly Sagiv) and MPI-SWS in Germany (hosted by Viktor Vafeiadis and Derek Dreyer). His research is supported by an ERC Starting Grant and ISF Grant. His research focuses on programming languages, verification, concurrency, and relaxed memory models, with additional interests in proof theory, semantics of non-classical logics, and automated reasoning. His work bridges theoretical foundations with practical applications in compiler design, hardware verification, and distributed systems. Lahav's publications consistently explore concurrency paradigms, weak memory models, and verification techniques. Recent works emphasize formal methods for RDMA, persistent memory, compositional semantics, and automated tooling for memory consistency. Awards: Best Paper & Best Student Paper Awards (DISC 2024) Distinguished Paper Award (OOPSLA 2021) Best Paper Award (TABLEAUX 2017) Distinguished Paper Award (PLDI 2017) Best Paper Award (ECOOP 2017) Kleene Award for Best Student Paper (LICS 2013) He advises PhD and MSc students including Yoav Ben Shimon, Yotam Dvir, and Roy Margalit. His group investigates shared-memory concurrency, denotational semantics, and verification tools. Lahav co-organizes conferences (VMCAI 2024) and Dagstuhl seminars (2023, 2026). He teaches courses on Programming Language Foundations, Discrete Mathematics, and Weak Memory Concurrency.