جست‌وجوی استاد و پژوهشگر

• Biofluidics
• Biomechanics
• Cardiac Mechanics
• +۷ مورد دیگر

Dr. Yong Wang is a Group Leader and Scientist at the Laboratory for Fluid Physics, Pattern Formation and Biocomplexity (LFPB) within the Department of Fluid Physics, Pattern Formation and Biocomplexity at the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany. He joined the institute as a Research Scientist in March 2015 after completing postdoctoral research at UC Irvine from 2011-2015. His educational background includes a PhD in Engineering Thermal Physics from Xi'an Jiaotong University (2010), where he also earned dual bachelor's degrees in Process Equipment and Controlling Engineering and Applied Mathematics. He is also a Scientist at the German Centre for Cardiovascular Research (DZHK) since 2017 and a member of the American Physical Society since 2016. Dr. Wang's research spans interdisciplinary areas at the intersection of physics, biology, and engineering. His work primarily focuses on biofluidics and biomechanics with specific emphasis on heart modeling for personalized medicine, cilia coordinated flow in brain ventricles, and turbulent flow dynamics in human upper airways. He employs advanced computational methods including the Lattice Boltzmann Method, Finite Element methods, and Immersed Boundary Method, complemented by experimental techniques like Particle Image Velocimetry. His publication record demonstrates strong activity in computational biophysics, with recent work analyzing cardiac mechanics, cerebrospinal fluid dynamics, and respiratory flow patterns. His research shows increasing integration of medical imaging technologies with computational modeling to address clinically relevant problems. Interdisciplinary Team Science Award, Institute for Clinical and Translational Science, University of California, Irvine, USA (2014) Distinguished Doctoral Dissertation of Xi'an Jiaotong University (2010) Provincial Distinguished Graduate of Shaanxi Province (2009) Multiple scholarships and honors from Xi'an Jiaotong University (2006-2009) Dr. Wang has successfully secured research funding including an XSEDE project as PI (2011-2012) and participation in NIH-funded research (2011-2015). He leads a research group with current members including postdoctoral researchers and has previously mentored numerous graduate students and researchers. His collaborative network spans multiple institutions including University Medical Center Göttingen, MPI for Biophysical Chemistry, University of Pittsburgh, and UC Irvine.

Chao Zhangمشاهده پروفایل

دانشیار

• Software Security
• System Security
• Data Security
• +۶ مورد دیگر

Chao Zhang is a Tenured Associate Professor at Tsinghua University, specializing in software security, system security, data security, and AI security. He leads the VUL337 research group and serves as the coach of the Blue-Lotus CTF team. His educational background includes a Ph.D. in Computer Science from Peking University (2008-2013), a B.S. in Mathematical Science from Peking University (2004-2008), and a postdoctoral position at UC Berkeley (2013-2016). Dr. Zhang's research focuses on Software Security , System Security , Data and AI Security , Program Analysis , and Vulnerability Discovery . His work spans binary code analysis, fuzzing techniques, blockchain security, and AI security. His recent publications demonstrate a strong emphasis on developing novel frameworks for vulnerability detection, binary code analysis, and securing AI systems against adversarial attacks. His publication trends show a consistent focus on practical security solutions with increasing attention to AI security challenges. Over the past decade, he has published extensively in top security conferences including IEEE S&P, USENIX Security, CCS, NDSS, and ISSTA, with a significant acceleration in publications since 2020. Tencent CSS TSec Professional Prize (2nd place, 2019) Tencent CSS TSec Breakthrough Prize (1st place, 2018) DARPA Cyber Grand Challenge CFE, 2nd in exploiting (2016) DARPA Cyber Grand Challenge CQE, 1st in defense (2015) Microsoft BlueHat Prize Contest's Special Recognition Award (2012) 5th place in Defcon CTF 2017 2nd place in Defcon CTF 2016 5th place in Defcon CTF 2015 Dr. Zhang leads the VUL337 research group at Tsinghua University, which focuses on vulnerability discovery and security analysis. He also serves as the coach of the Blue-Lotus CTF team and is a member of the V group of LiST. His research has received significant attention in the security community, with numerous publications in top-tier security venues and practical contributions to vulnerability discovery and mitigation techniques.

Zhou Yangمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence
• AI for Software Engineering
• +۳ مورد دیگر

Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.