جست‌وجوی استاد و پژوهشگر

• Continuous Optimization
• Numerical Methods
• Convex Optimization
• +۱۲ مورد دیگر

Mirai Tanaka is an Associate Professor at The Institute of Statistical Mathematics (ISM) in Tachikawa, Tokyo, where they lead research in optimization theory and its applications. Currently affiliated with the Statistical Decision-Making Group in the Department of Fundamental Statistical Mathematics, Tanaka also holds concurrent appointments at the Risk Analysis Research Center at ISM and the Statistical Science Program at The Graduate University for Advanced Studies. Previously, Tanaka served as an Assistant Professor at ISM (2017-2020) and at Tokyo University of Science (2014-2017). Tanaka's research focuses on continuous optimization, numerical methods, and their applications across diverse fields. Their work spans convex and non-convex optimization, proximal algorithms, DC programming, and mathematical modeling for real-world problems. Specific interests include gradient methods, subgradient methods, Bregman proximal algorithms, Newton methods, and interior point methods. Tanaka has applied these techniques to problems in machine learning, data analysis, signal and image processing, control engineering, maritime affairs, supply chain management, forest science, and polymer chemistry. Their recent publications reveal a strong emphasis on developing efficient algorithms for challenging optimization problems, with particular attention to convergence properties and practical implementations. Tanaka's work bridges theoretical developments with real-world applications, as evidenced by publications spanning pure optimization theory to applied problems in various scientific domains. 12th Research Encouragement Award, Operations Research Society of Japan (2022) Best Paper Award, 15th Congress of the Asian Network for Quality (2017) Best Paper Award, 14th Congress of the Asian Network for Quality (2016) Teshima Seiichi Memorial Research Award (Doctoral Dissertation Award), Tokyo Institute of Technology (2015) Tanaka actively supervises graduate students at The Graduate University for Advanced Studies and has received multiple research grants from the Japan Society for the Promotion of Science (JSPS), including current funding for projects on forest pest control and practical aerial image processing. They have organized numerous workshops including the ZIB-IMI-ISM-NUS-RIKEN-MODAL-NHR Workshop series and the Continuous Optimization and Related Fields Summer School.

Li-Shiuan Pehمشاهده پروفایل

استاد

• Energy-Efficient Hardware Systems
• Neural Network Hardware Acceleration
• Wearable Sensing Technologies
• +۴ مورد دیگر

Li-Shiuan Peh is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS) . She previously held faculty positions at MIT (2013-2016) and Princeton University (2002-2009), advancing from Assistant to full Professor. Education: B.S. from National University of Singapore (1995) Ph.D. from Stanford University (2001) Her research focuses on energy-efficient hardware systems , spanning neural network accelerators for edge computing , privacy-preserving embedded systems , on-chip communication networks , and hardware security . Current projects include AI-on-skin interfaces , secure Network-on-Chip (NoC) architectures , and low-power wearable sensors . Scientific Awards: IEEE Fellow (2017) National Research Foundation Returning Singaporean Scientist Award (2016) ACM Distinguished Scientist (2011) MICRO Hall of Fame Award (2011) National Science Foundation CAREER Award (2003) Her work has driven innovations in bufferless NoC architectures , collaborative traffic advisory systems , and laser attack benchmarks , with publications in top venues like DATE, NOCS, and DAC. She leads an interdisciplinary research group at NUS, advising graduate students in computer architecture and hardware security.

• Artificial Intelligence and Data Science
• Data Management & Mining
• Machine Learning & Intelligence
• +۵ مورد دیگر

KAM Tin Seong is a Full-time Associate Professor of Information Systems (Practice) at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). He holds a PhD from the University of London (1995) and specializes in geospatial analytics, data science, and decision support systems. His research focuses on integrating spatial explicit machine learning, urban sustainability, healthcare analytics, and social media insights. His teaching includes courses like Computer as an Analysis Tool, Geospatial Analytics for Business Intelligence, and Visual Analytics for Business Intelligence. He leads the Data Analytics Lab and advises students such as SUN Bing. Key research areas include artificial intelligence applications, machine learning in environmental modeling (e.g., landslide prediction), urban mobility optimization, and health risk profiling. His work bridges theory and practice through tools like DIVAD (Dynamic Interactive Visual Analytical Dashboard) and RIGA (Rich Internet Geospatial Analytics Application). He has received awards for actionable analysis in VAST challenges (2017), emphasizing clear hypothesis presentation and data-driven spatial-temporal exploration. His contributions span over 30 years, with publications addressing topics from geospatial policy analytics to wildlife anomaly detection.

Zhang Huangweiمشاهده پروفایل

پژوهشگر

• Combustion
• Turbulent Combustion Modelling
• Multiphase Combustion
• +۳ مورد دیگر

Dr. Zhang Huangwei is a researcher at the Department of Mechanical Engineering, Faculty of Engineering, National University of Singapore (NUS). He holds a PhD in Energy and Combustion from the University of Cambridge (2015) and has previously worked as a postdoctoral research associate at Cambridge and a research associate at Peking University. His research focuses on combustion theory, turbulent combustion modeling, multiphase combustion, and high-performance computing of reacting flows. Education : PhD (2015), University of Cambridge ME (2009), Beihang University BE (2007), Beihang University Dr. Zhang's work spans turbulent combustion modeling, fire dynamics, and algorithm development for reacting flows. His publications emphasize LES/CMC methods, flame extinction, and multiphase combustion. He has received prestigious awards including the Dorothy Hodgkin Postgraduate Award and the Cambridge Overseas Trust Scholarship. Scientific Awards : Professor Qingzhi He Memorial Scholarship Professor Allen T Chwang Fluid Mechanics Scholarship Cambridge Overseas Trust Scholarship Dorothy Hodgkin Postgraduate Awards Postdoctoral Research Fellowship from Stanford University's CTR Osborne Reynolds Research Student Award finalist (ERCOFTAC) Dr. Zhang serves as a reviewer for journals like Combustion and Flame and Energy & Fuels . His lab at NUS develops high-fidelity combustion models and collaborates on direct numerical simulation projects.

Sriram SAMIمشاهده پروفایل

مدرس

• Systems & Networking
• Internet of Things (IoT)
• Cyber Physical Systems (CPS)
• +۷ مورد دیگر

Sriram SAMI is a Lecturer (Educator Track) at the School of Computing, National University of Singapore (NUS), affiliated with the Department of Computer Science. He holds a Ph.D. and B.Comp. in Computer Science from NUS, where he continues to contribute to teaching and research in systems, networking, and security. Ph.D. in Computer Science, National University of Singapore B.Comp. in Computer Science, National University of Singapore His research centers on Internet of Things (IoT) , Cyber-Physical Systems (CPS) , and mobile sensing , with a focus on security and privacy . He specializes in leveraging commodity smartphone sensors—particularly time-of-flight (ToF) and LIDAR—for novel applications such as detecting hidden cameras and eavesdropping threats in smart environments. His recent publications, including LAPD: Hidden Spy Camera Detection using Smartphone Time-of-Flight Sensors and Spying with Your Robot Vacuum Cleaner: Eavesdropping via Lidar Sensors , demonstrate a strong trend in identifying privacy vulnerabilities in everyday sensing devices. These works span subfields such as optical sensing, side-channel attacks, embedded systems security, and sensor exploitation, highlighting an interdisciplinary approach combining systems, hardware, and security. He has been recognized for his teaching excellence with multiple awards: Annual Teaching Excellence Award (ATEA) - Team Category (2023/2024) Full Time Teaching Assistant Award (2021/2022) Full Time Teaching Assistant Award (2020/2021) Honors List of Student Tutors (2018/2019) Sriram has taught foundational courses such as CS1010: Programming Methodology , CS3210: Parallel Computing , and CG1111A/CG2111A: Engineering Principles and Practice I & II . His project work includes the NUS Timetable Optimizer , a browser-based tool using Z3 SMT solvers via WebAssembly, and the Singapore Blood Stocks Telegram bot, which scrapes and visualizes blood inventory data. He has also developed tools like an offline plagiarism detector in Rust and browser extensions for productivity. These reflect a strong commitment to educational technology and public service through software. He leads independent research and development efforts, often as a solo or primary contributor, focusing on practical tools that solve real-world problems in education, healthcare, and privacy. His work bridges academic research with tangible applications, emphasizing accessibility, efficiency, and user empowerment.

• Mathematical Optimization
• Mixed Integer Programming
• Parallel Computing
• +۴ مورد دیگر

Dr. Yuji Shinano is a Researcher at the Zuse Institute Berlin (ZIB) in the Department of Applied Algorithmic Intelligence Methods within the Mathematical Algorithmic Intelligence division. His work focuses on mathematical optimization, particularly the development and parallelization of algorithms for solving complex optimization problems. His research interests span Mathematical Optimization, Mixed Integer Programming, Parallel Computing, Energy Systems Optimization, and Combinatorial Optimization. He has made significant contributions to the SCIP Optimization Suite, a prominent framework for solving mixed integer programming problems. His work often involves applying these optimization techniques to practical problems in energy system design and transportation networks. Dr. Shinano's publication record shows a consistent research trajectory from 2012 through 2025, with particular emphasis on parallel implementations of optimization algorithms, energy system modeling, and challenging combinatorial problems like the Quadratic Assignment Problem. His recent work (2023-2025) demonstrates continued innovation in optimization methodology, with publications on QUBO solving, parallel branch-and-bound techniques, and the latest SCIP Optimization Suite release. Among his notable projects are HPO-NAVI, BEAM-ME, and work on Linear, Integer, and Constraint Programming. His collaborations span multiple institutions, with frequent co-authorship with researchers like Thorsten Koch and Ryohei Yokoyama, particularly on energy system optimization projects. Dr. Shinano has contributed to both theoretical advances in optimization methodology and practical implementations that solve real-world problems in energy systems and transportation networks. His work bridges the gap between theoretical optimization and practical applications requiring high-performance computing solutions.

• Systems & Networking
• Computer Architecture
• Embedded Systems
• +۶ مورد دیگر

Associate Professor at the Department of Computer Science , School of Computing , National University of Singapore . Research focuses on systems-level optimization across hardware-software stacks, including GPU computing, memory systems, and approximate computing for deep learning. Dr.Eng.Sc. (University of Tsukuba, 1993) M.Sc. (NUS, 1991) B.Sc. (NUS, 1989) Research interests span computer architecture , compiler design , and embedded systems , with recent emphasis on precision analysis , variable precision arithmetic , and deep learning approximation using hardware accelerators . Publications reveal trends in GPU optimization, memory management for NAND flash, and fault-tolerant cloud-based GPU computing. Scientific Recognition: Best Paper Finalist at IEEE High Performance Extreme Computing Conference (HPEC) 2017 Professional memberships include ACM Member and IEEE Senior Member , with editorial contributions to Software Practice and Experience . Teaching experience includes courses like CS2100 Computer Organisation and CS5250 Advanced Operating Systems .

Gary Tan Soon Huatمشاهده پروفایل

دانشیار

• Parallel and Distributed Systems
• Symbiotic Simulation
• Traffic Simulation
• +۵ مورد دیگر

Gary Tan Soon Huat serves as Associate Professor (Educator Track) and Vice-Dean of Student Life at the National University of Singapore's School of Computing, Department of Computer Science. With over three decades of continuous service since 1990, he has established himself as a leading educator and researcher in parallel and distributed systems. His educational background includes a B.Sc (1st class Honours) from NUS, followed by M.Sc and Ph.D degrees from the University of Manchester, UK. As a pioneer in NUS's Direct Honours Programme, his academic journey reflects deep institutional commitment. Tan's research focuses on parallel and distributed computing , symbiotic simulation , and traffic and crisis management simulation . His work bridges theoretical computer science with practical applications in disaster response systems, where he develops frameworks that analyze real-life video feeds to model human movement during emergencies. This research has evolved from foundational work on High Level Architecture and Data Distribution Management to current innovations like the Conscious Movement Model (CMM) that extracts behavioral patterns from CCTV footage. His publication record spans nearly three decades, showing a clear evolution from neighborhood-based multiprocessor scheduling to sophisticated GPU-accelerated traffic simulations and crisis management frameworks. The research demonstrates consistent focus on distributed systems while adapting to emerging technologies like deep learning and GPU computing. ASIASIM FELLOW 2016 NUS Annual Teaching Excellence Awards (03/04, 04/05, 06/07) School Teaching Excellence Awards (1999, 2002, 2016) Faculty of Science Teaching Awards (1992, 1998) ATEA Honour Roll 2008 As an educator, Tan has supervised PhD candidates Wang Chengxin and Muhammad Shalihin bin Othman, focusing on pedestrian movement analysis during crises. His leadership extends beyond research to academic service, including roles as Program Chair of DSRT 2016, Conference Co-chair of SIMUTOOLS 2016, and President of both the Society of Simulation and Gaming of Singapore and the ASIASIM federation. His administrative contributions include serving as Master of Sheares Hall (2003-2013) and current Vice-Dean of Student Life. Tan leads the Modelling and Simulation Group within NUS's Computer Systems Lab, collaborating internationally with KTH (Sweden), FOI (Swedish Defence Research Agency), SMART, and Beihang University. His team's work bridges academic research with practical applications in transportation systems and emergency response planning.

• Distributed Systems
• Operating Systems
• Data Center Networks
• +۳ مورد دیگر

Jialin Li is the Sung Kah Kay Assistant Professor at the School of Computing , National University of Singapore (NUS). They earned a PhD from the University of Washington under the advisement of Dan Ports and a bachelor's degree from the University of Michigan . Their research focuses on distributed systems and operating systems, particularly on co-designing systems with data center networks, data plane operating systems, and decentralized infrastructure. Research Interests : Distributed systems, network ordering, consensus algorithms, in-network processing, decentralized infrastructure, and programmable hardware. Awards : OSDI '14 Jay Lepreau Best Paper Award, NSDI '15 Best Paper Award. Students : Mentors PostDocs (Chaoyi Ruan), Graduate Students (Inho Choi, Yunfan Li, Ziji Shi, etc.), and Undergraduate Students (Mohsen Ghasemi, Akshaye Shenoi, etc.). Service : Conference Organizer (APSys '25 Program Co-Chair), Technical Committee for EuroSys, SOSP, NSDI, and others.

Koh Chan Gheeمشاهده پروفایل

استاد

• Structural Dynamics
• Structural Health Monitoring
• Offshore/Marine Engineering
• +۵ مورد دیگر

Professor Koh Chan Ghee holds the rank of Professor in Civil Engineering at the National University of Singapore (NUS). He completed his B.Eng.(Hons 1) from the University of Singapore in 1979, followed by M.Eng. from NUS (1983), M.S. and Ph.D. in Civil Engineering from the University of California, Berkeley (1983 and 1986, respectively). His research focuses on structural dynamics, vibration mitigation, offshore engineering, and structural health monitoring. He has authored over 300 journal/conference papers, seven book chapters, and a textbook. Notable achievements include the Marie Curie Fellowship (1993) and Stanford’s Top-2% Scientist ranking (2022). He has secured over S$13M in research grants and serves on editorial boards of journals like Structural Health Monitoring . Currently, he directs the Coastal Protection and Flood Resilience Institute Singapore and the Centre for Hazards Research at NUS. Education: B.Eng. (Hons 1), University of Singapore, 1979 M.Eng., National University of Singapore, 1983 M.S., University of California, Berkeley, 1983 Ph.D., University of California, Berkeley, 1986 P.Eng., Professional Engineers Board (Singapore), 1995 Research Interests: Structural dynamics, system identification, train-track dynamics, offshore system reliability, and coastal protection. His work bridges academic and industrial applications, including over 130 infrastructure projects and 40+ short courses on seismic design and structural analysis. Professional Contributions: Editorial board memberships for journals like Structural Health Monitoring and Smart Structures and Systems . Key contributions include patents on sensors for load measurement, rail flaw detection, and wave hydrodynamics. Awards & Recognition: Top-2% Global Scientist (Stanford, 2022) Marie Curie Fellowship (EU, 1993) IES Prestigious Publication Award (1997) Teaching Commendations (over 10 years) Grants & Projects: Over S$13M in competitive grants, including S$7M as Principal Investigator. Projects span structural health monitoring, offshore engineering, and blast/earthquake analysis. Leadership Roles: Former Director of LRF Institute for Public Understanding of Risk (2019–2023). Current Directorships include Coastal Protection Institute Singapore and NUS’s Centre for Hazards Research.

• Applied Mathematics
• Optimization
• Data Science
• +۳ مورد دیگر

Dr. Xin Yee Lam is a Lecturer in the Department of Mathematics at the National University of Singapore (NUS). Her research focuses on optimization, data science, and machine learning, with applications in computational mathematics and financial risk modeling. She has contributed to advancements in decomposition methods for large-scale optimization problems and parallel algorithms for high-dimensional data analysis. Her work spans convex programming, stochastic programming, and generalized distance-weighted discrimination. She has developed efficient algorithms for problems arising in financial networks and has published in top journals such as Computational Optimization and Applications and Journal of Computational and Graphical Statistics . Dr. Lam’s research emphasizes practical applications of optimization techniques to real-world challenges, including liquidity risk stress testing and large-scale machine learning problems. Her methods often address computational efficiency and scalability for complex systems.

Ilya Sergeyمشاهده پروفایل

دانشیار

• Programming Languages
• Software Verification
• Distributed Systems
• +۵ مورد دیگر

Associate Professor Ilya Sergey leads the Verified Systems Engineering (VERSE) lab at the School of Computing, National University of Singapore (NUS). He holds a PhD in Computer Science from KU Leuven and an MSc in Mathematics from Saint Petersburg State University. His research focuses on programming languages, software verification, distributed systems, and program synthesis. He is a recipient of the AITO Dahl-Nygaard Junior Prize (2019) and multiple ACM SIGPLAN Distinguished Paper Awards. His work includes developing the Scilla smart contract language and the Veil verification framework, emphasizing formal methods for ensuring software correctness. **Education**: PhD in Computer Science, KU Leuven, Belgium (2012) MSc in Mathematics and Computer Science, Saint Petersburg State University, Russia (2008) **Research Interests**: Design and Implementation of Programming Languages Formal Verification using Separation Logic Distributed Systems and Concurrency Program Synthesis and Automated Proof Repair **Recent Articles Trends**: His recent work emphasizes automated verification tools (e.g., Veil), exploit generation via synthesis, and compositional verification of Byzantine protocols. These contributions bridge foundational theory with practical applications in distributed systems and smart contracts. **Awards**: AITO Dahl-Nygaard Junior Prize (2019) ACM SIGPLAN Distinguished Paper Awards (PLDI'23, PLDI'21, POPL'19) Google, Facebook, and Amazon Research Awards **Advising & Grants**: He actively mentors PhD students in formal methods and verification. His grants include support from Google and industry partnerships. He organizes the ICFP Programming Contest and co-chairs ICFP'25. **Labs & Teams**: Leads the VERSE lab, part of the PLSE@NUS group, focusing on verified software systems and program synthesis.

SOO Yuen Jienمشاهده پروفایل

دانشیار

• Systems & Networking
• Education Technology
• Computer Architecture
• +۱ مورد دیگر

SOO Yuen Jien is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS) , where he has been teaching for over 20 years. He serves as the Director of the Centre for Development of Teaching and Learning and focuses on pedagogical innovation in computing education. Education: Ph.D. (2006), M.Sc. (2002), B.Sc. (2000) in Computer Science from NUS Research Areas: Systems & Networking, Education Technology, Computer Architecture, Parallel Programming Scientific Awards: NUS Teaching Academy Fellow (2011–present; Executive Council 2015–2018) NUS Outstanding Educator Award (2018) NUS Annual Teaching Excellence Awards (2008, 2011, 2013) with Honor Roll (2014) School of Computing Faculty Teaching Excellence Awards (2006–2009, 2016) with Honor Roll (2010)

Bruno Loic Alexandre Bodinمشاهده پروفایل

استادیار

• Dataflow Programming
• Compilers
• Static Analysis
• +۳ مورد دیگر

Bruno Bodin is an Assistant Professor at Yale-NUS College, Singapore, with a joint appointment at the National University of Singapore (NUS) School of Computing. He previously held roles as Senior Research Associate at the University of Edinburgh (2014–2018), Visiting Research Fellow at INRIA ENS Paris, and Software Engineer at Kalray (2011–2014). He earned his PhD and M.S. in Computer Science from Université Pierre & Marie Curie, Paris. His research focuses on dataflow programming , compilers , and static analysis , with applications in signal processing and robotics . Notable contributions include benchmarking frameworks for SLAM systems and compiler techniques for heterogeneous computing. Teaching includes courses on Operating Systems, Programming for Data Science, and Software Engineering at Yale-NUS. Active in open-source projects, he maintains repositories on GitHub related to dataflow graph generation and SLAM evaluation.

• Formal Verification
• Model Checking
• Automated Reasoning
• +۹ مورد دیگر

Georg Weissenbacher is a Full Professor of Computer Science at Vienna University of Technology (TU Wien), working in the Institute of Logic and Computation within the Faculty of Informatics. He leads the Formal Methods in Systems Engineering research group and has established himself as a leading researcher in formal verification and automated reasoning. His educational background includes a DPhil from Oxford University (2008-2010), research at ETH Zürich (2005-2010), and a Master's degree from TU Graz (completed by 2003). He completed his Habilitation at TU Wien in 2016 with a thesis on Logical Methods in Automated Hardware and Software Verification. Weissenbacher's research focuses on developing automated tools for software and hardware verification, with particular emphasis on detecting and explaining bugs in complex systems. He is renowned for his work on heisenbugs - bugs that disappear when analyzed, which are particularly challenging in concurrent and multi-core systems. His research bridges theoretical foundations in logic with practical applications in software engineering, with significant contributions to interpolation-based verification techniques and SAT/SMT solving applications. His recent publications show a clear progression from traditional software verification toward emerging challenges in AI security, neural network verification, and sophisticated concurrency models. The research trajectory demonstrates increasing sophistication in handling complex systems properties, with a growing emphasis on probabilistic guarantees and formal methods applied to modern computing challenges. OOPSLA'18 Distinguished Paper Award for 'Randomized Testing of Distributed Systems with Probabilistic Guarantees' Weissenbacher has advised numerous PhD students and postdocs, including current researchers Mai AL-Zu'bi, Katalin Fazekas, and Sarah Sallinger. His research has been supported by significant grants including the Vienna Research Groups for Young Investigators (2011), the National Research Network 'Rigorous Systems Engineering' funded by FWF, and a Microsoft Research PhD Scholarship (2016). He actively contributes to the academic community through his service as co-chair for major conferences including CAV 2018 and FMCAD 2017. As leader of the FORSYTE research group at TU Wien, Weissenbacher oversees a vibrant research team working at the intersection of logic, verification, and practical software engineering challenges. The group is currently involved in the Doctoral College on Automated Reasoning, funded by FWF, which aims to train the next generation of researchers in this critical field.