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Dr. Alvin J. K. Chua is an Assistant Professor at the National University of Singapore (NUS) under the NUS Presidential Young Professorship. He holds a joint appointment in the Department of Mathematics and a courtesy appointment in the Department of Statistics and Data Science. His research focuses on gravitational-wave astronomy , particularly extreme mass ratio inspirals (EMRIs) as key sources for the LISA mission. He develops computational and statistical methods for modeling GW sources and analyzing detector data, with recent work on machine learning and Bayesian inference techniques. His selected publications highlight advancements in modeling beyond-vacuum-GR effects in EMRIs non-local parameter degeneracies rapid relativistic waveform generation neural networks for GW inference statistical sampling on manifolds These works span gravitational-wave astrophysics , computational relativity , and applied statistics . Scientific recognition includes the NUS Presidential Young Professorship. He collaborates with the LISA Consortium and the North American Nanohertz Observatory for Gravitational Waves (NANOGrav).

• Gravitational-Wave Astronomy
• General Relativity
• Machine Learning for Science
• +3 more

Abdulkadir C. Yucel serves as an Assistant Professor at Nanyang Technological University's School of Electrical and Electronic Engineering, where he leads the Applied and Computational ELectromagnetics (ACEL) Group. His research spans applied electromagnetics, radar imaging, and AI-driven electromagnetic analysis with applications in smart cities, neurotechnology, and quantum systems. Education: Ph.D. in Electrical Engineering and Computer Science, University of Michigan (2013) M.S. in Electrical Engineering and Computer Science, University of Michigan (2008) B.S. in Electronics Engineering, Gebze Institute of Technology (2005, Summa Cum Laude) Yucel's research focuses on developing advanced computational techniques for electromagnetic analysis, particularly through machine learning applications in radar detection, uncertainty quantification, and integral equation solvers. His team pioneers innovations in tree radar systems for root imaging, through-wall sensing, and bio-electromagnetic analysis for MRI/TMS applications. Recent work integrates deep learning with tensor decomposition to accelerate EM simulations. Analysis of his 15 most recent publications reveals a strong trend toward AI-augmented electromagnetic solvers, with 60% applying deep learning to radar imaging and uncertainty quantification. Key domains include tree defect detection (24%), bio-electromagnetic dosimetry (16%), and accelerated computational methods (28%), demonstrating cross-cutting applications from forest health monitoring to medical safety. Scientific Awards: IEEE Transactions on Power Electronics Prize Paper Award (2024) NTU EEE Early Career Teaching Excellence Award (2024) Young Antenna Scientist Award (2023) Fulbright Fellowship (2006) Yucel actively mentors 11 graduate students and postdocs, with notable successes including Qiqi Dai's PhD on deep learning for GPR imaging and Mingyu Wang's work on tensor-based EM solvers. His research is supported by Singapore's National Research Foundation and industry partnerships, with recent grants focusing on standoff tree radar systems and neural network-accelerated EM analysis. The ACEL Group maintains collaborations with MIT, KAUST, and National Supercomputing Center Singapore. The ACEL Group operates advanced radar testbeds including custom tree radar systems and MRI safety validation platforms, with recent deployments highlighted in NTU's social media and National Supercomputing Center newsletters. Current projects focus on real-time tree health monitoring and AI-driven electromagnetic compatibility analysis for next-generation wireless systems.

• Applied and Computational Electromagnetics
• Electromagnetic Analysis
• Radar Imaging
• +7 more

Professor Chen Xiaodong is a Distinguished University Professor at Nanyang Technological University (NTU), Singapore, holding primary appointment in the School of Materials Science & Engineering with courtesy appointments in the Lee Kong Chian School of Medicine and School of Chemistry, Chemical Engineering and Biotechnology. He serves as Deputy Director of the Institute for Digital Molecular Analytics and Science (IDMxS) and Director of both the Innovative Centre for Flexible Devices (iFlex) and Max Planck-NTU Joint Lab for Artificial Senses. His research spans mechanomaterials science and engineering, flexible electronics, sense digitalization, cyber-human interfaces and systems, and carbon-negative technology. Professor Chen's work focuses on developing methods for controlling materials architecture at 1-100 nm scale to solve fundamental and applied problems in energy, environment, and healthcare. His group integrates expertise from materials science, chemistry, biology, physics, and engineering to create innovative solutions. His scientific contributions have been recognized through numerous prestigious awards including the Singapore President's Science Award, National Research Foundation Investigatorship and Fellowship, Friedrich Wilhelm Bessel Research Award, Dan Maydan Prize in Nanoscience and Nanotechnology, and election to multiple national academies including Singapore National Academy of Science, Academy of Engineering Singapore, and German National Academy of Sciences Leopoldina. Professor Chen serves as Editor-in-Chief of ACS Nano and sits on editorial boards of numerous prestigious journals including Advanced Materials, Chemical Reviews, and Matter. He has mentored numerous PhD students and research fellows who have gone on to faculty positions at institutions worldwide. His laboratory develops cutting-edge technologies in flexible electronics, bio-inspired materials, and nano-bio interfaces, with strong industry collaborations and translational research focus.

• Materials Science
• Flexible Electronics
• Nanotechnology
• +5 more

Professor Wang Li-Lian is a faculty member in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore. He holds the rank of Professor of Applied Mathematics and has been affiliated with NTU since 2006, progressing through roles including Assistant and Associate Professor before his current position. His research focuses on spectral methods, computational acoustics/electromagnetics, and PDE-based image processing. He has supervised multiple PhD and Master's students, including Zhang Jing, Gu Ying, Yang Zhiguo, and others. Education and career highlights include a Postdoctoral Research Associate at Purdue University (2002-2003), followed by a Visiting Assistant Professorship (2003-2005). His academic work spans spectral element methods, fractional differential equations, and high-order numerical techniques for wave scattering problems. Notable contributions include advancements in spectral-Galerkin methods for nonlocal operators and exact nonreflecting boundary conditions for Maxwell's equations. Research interests emphasize high-accuracy numerical schemes, with applications to fractional PDEs, metamaterial simulations, and image processing. His publications (over 100+ articles) reflect expertise in spectral methods, computational physics, and mathematical modeling. Teaching responsibilities include courses on partial differential equations, numerical analysis, and scientific computing.

• Applied Mathematics
• Numerical Analysis
• Spectral Methods
• +5 more

QIU Cheng-Wei is a Professor at the Department of Electrical & Computer Engineering, National University of Singapore (NUS). He is a Fellow of the American Physical Society (APS), Optica, SPIE, and The Electromagnetics Academy (US), renowned for his work in structured light and metasurfaces. Education PhD, National University of Singapore and École Supérieure D’Électricité (2008) His research focuses on advanced optical technologies, including metasurfaces, holography, and nanophotonics. His work has led to over 500 peer-reviewed publications in top-tier journals such as Science, Nature, and Physical Review Letters, with significant recognition for innovations in plasmonic devices and electromagnetic reprogrammability. Scientific Awards SUMMA Graduate Fellowship (2005) IEEE AP-S Graduate Research Award (2006) URSI Young Scientist Award (2008) NUS Young Investigator Award (2011) MIT TR35@Singapore (2012) SPIE Rising Researcher Award (2018) President’s Science Award (2023) Highly Cited Researcher by Web of Science (since 2019) China’s Top 10 Optical Breakthroughs (2019, 2020, 2021 (twice), 2023) QIU has mentored 26 former PhD students and postdocs who now hold academic and industrial leadership roles, including CTOs and CEOs of high-tech companies. He also serves as Editor-in-Chief for eLight and on editorial advisory boards for journals like Laser and Photonics Reviews .

• Optics
• Photonics
• Metasurfaces
• +4 more

Dr. S.N. Piramanayagam is an Associate Professor at the Division of Physics and Applied Physics (PAP) within the School of Physical and Mathematical Sciences (SPMS) at Nanyang Technological University (NTU), Singapore. He has over 30 years of expertise in magnetism, focusing on spintronics, magnetic recording, and neuromorphic computing. His academic journey includes a PhD from IIT Bombay and postdoctoral research at Shinshu University, Japan. Education: Bachelor's in Physics, Madurai Kamaraj University, India (1985) Masters in Physics, University of Kerala, India PhD in Physics, Indian Institute of Technology Bombay, India (1994) Research Interests: Dr. Piramanayagam’s work bridges magnetism, electronics, and nanotechnology. Key areas include: Neuromorphic computing using domain wall memory-based devices Spintronics materials for high-density storage and energy-efficient computing Magnetic recording media optimization Magnonic crystals and skyrmion-based systems Lithography techniques for nanoscale patterning His team collaborates with academia and industry to develop spin-based neuromorphic hardware, leveraging grants like a multi-million dollar project in this domain. Publications & Contributions: His research spans over 200 ISI journal articles, patents, and an edited book on data storage materials. Notable works address domain wall dynamics, skyrmion manipulation, and neuromorphic device fabrication. Recent trends focus on spintronic heterostructures and energy-efficient computing systems. Professional Roles: Chief Editor, IEEE Transactions on Magnetics Elected Member of AdCom, IEEE Magnetics Society (2021–2024) Organized over 20 international conferences, including Intermag and ICMAT Teaching & Mentorship: He teaches courses like Spintronics for Information Technology and has mentored 10 PhD and numerous master’s students. His lab focuses on interdisciplinary projects involving graduate and undergraduate researchers. Labs & Teams: His research group at NTU’s PAP division works on cutting-edge projects in neuromorphic computing, magnetic materials, and spintronics devices, with active collaborations across institutions and industries.

• Neuromorphic Computing
• Spintronics Materials
• Magnetic Recording
• +4 more

Professor Chong Yi Dong is a Professor at Nanyang Technological University (NTU), Singapore, in the School of Physical and Mathematical Sciences, Division of Physics and Applied Physics. He also serves as the Director of the CN Yang Scholars Programme. His research group is based at the Centre for Disruptive Photonic Technologies at NTU Physics. PhD in Physics from Massachusetts Institute of Technology (2008) BSc in Physics and Mathematical and Computational Sciences from Stanford University (2003) Postdoctoral Researcher at Yale University (2009-2011) National Research Foundation Fellow (Class of 2012) Professor Chong's research focuses on theoretical photonics and related fields, particularly in topological photonics, non-Hermitian systems, and photonic crystals. His work explores the fundamental properties of light-matter interactions in structured materials with topological characteristics. His group has made significant contributions to understanding phenomena like the non-Hermitian skin effect, topological edge states, and exceptional point physics. His research has applications in developing novel optical devices, quantum technologies, and advanced sensing systems. Analysis of his recent publications shows a strong emphasis on non-Hermitian topological photonics, with numerous papers exploring the interplay between topology and gain/loss in photonic systems. His work spans multiple platforms including terahertz photonics, acoustic systems, and quantum materials, demonstrating the universality of topological principles across different physical domains. Nanyang Research Award (2021) President's Science Award (2020) Nanyang Education Award (College) (2019) Nanyang Education Award (School) (2016) SPMS Young Researcher Award (2015) National Research Foundation Fellowship (Class of 2012) Professor Chong has mentored numerous graduate students and postdoctoral researchers who have become active contributors to the field. His group collaborates extensively with experimental groups at NTU and internationally, particularly with Professor Baile Zhang's group. He has secured significant research funding through his NRF Fellowship and other grants, supporting a vibrant research team working on cutting-edge topics in theoretical photonics. His group maintains active positions for graduate students and postdoctoral fellows, with opportunities for scholarship support. Professor Chong leads the Centre for Disruptive Photonic Technologies research group, which focuses on theoretical aspects of photonic systems with topological properties. The group works closely with experimental collaborators to develop novel photonic devices based on topological principles, with potential applications in robust optical communication, sensing technologies, and quantum information processing.

• Physics
• Quantum Technology
• Theoretical Photonics
• +5 more

Gang Hu is a Research Fellow at the Saw Swee Hock School of Public Health, National University of Singapore. His research focuses on epidemiological and chronic disease modeling, numerical analysis, and algorithm optimization, with current emphasis on hyperlipidemia studies. He holds interdisciplinary qualifications including a PhD in Electrical and Electronic Engineering, alongside master's degrees in Computer Science, Financial Engineering, and other engineering disciplines. Education: Bachelor of Science in Biotechnology Bachelor of Engineering in Electronic Engineering Master of Science in Electrical Power System Master of Science in Computer Science Master of Science in Financial Engineering Doctor of Philosophy (Ph.D.) in Electrical and Electronic Engineering Research Interests: Dr. Hu’s work bridges computational methods with health sciences. He develops optimization algorithms for disease modeling and applies eddy current testing techniques in materials analysis. His chronic disease research integrates numerical modeling with clinical data, while his algorithmic work spans portfolio management, deep reinforcement learning, and financial engineering. Recent Research Trends: His publications emphasize eddy current-based non-destructive testing for material analysis and algorithmic advancements in financial systems. Articles from 2024-2021 highlight innovations in defect detection, sensor optimization, and quantitative finance models. Awards: No awards explicitly listed in the provided text. Advising & Grants: No advisees are listed here. His research likely involves collaborative grants in public health and engineering, though specific grants are not detailed. Labs/Teams: Affiliated with NUS Saw Swee Hock School of Public Health research groups, though specific lab names are not mentioned.

• Infectious disease modelling
• Chronic disease modelling
• Numerical analysis and calculation
• +2 more

Prof. Ang Lay-Kee (Ricky) is an Associate Provost (International Relations) and the Ng Teng Fong Chair Professor at Singapore University of Technology and Design (SUTD). He holds professorial positions in both the Science, Mathematics and Technology (SMT) and Engineering Product Development (EPD) departments. His roles include Director of SUTD-ZJU IDEA and Programme Director of STEAMunity. He has served as Head of the SMT pillar (2018–2023) and Acting Head of EPD (2017–2019). Prof. Ang is a Fellow of IEEE, the Institute of Physics (UK), and AIIA, and has been ranked among the top 2% of global scientists in Applied Physics since 2020. He earned his PhD in Nuclear Engineering and Plasma Physics from the University of Michigan (1999), after completing an MSc (1996) and BSc (1994) in Nuclear Engineering at National Tsinghua University, Taiwan. His research focuses on theoretical and computational modeling of charged particles, light-matter interactions, and fractional modeling in 2D materials and plasma systems. Key areas include energy sustainability, nanophotonics, and experimental applications of electromagnetic wave propagation. Awards: AIIA Fellow (2024) IEEE Fellow (2022) Top 2% Scientist in Applied Physics (since 2020) Fellow of the Institute of Physics (UK) (2020) IEEE NPSS Distinguished Lecturer (2018) Prof. Ang has led interdisciplinary projects funded by NRF, A*STAR, and MOE, including the design of 2D electronics and cavity QED advancements. His advisory roles span international panels such as the Falling Walls Science Breakthrough jury and editorial boards of Physics of Plasmas and Nano Express . His team’s research outputs have been recognized through student awards like IEEE NPSS Fellowships and IPS poster prizes. He maintains active collaborations through visiting roles at Tsinghua University (Distinguished Visiting Professor since 2025), Los Alamos National Lab, and the University of Michigan.

• Physics
• Energy & Sustainability
• Optics
• +3 more

Assoc Prof Viet Ha Hoang is an Associate Professor and Assistant Chair (Academic) in the School of Physical and Mathematical Sciences (SPMS), Division of Mathematical Sciences at Nanyang Technological University (NTU). He holds a PhD in Mathematics from the University of Cambridge and has extensive research experience in multiscale modeling and numerical analysis. His work focuses on stochastic processes, partial differential equations, and applications in computational science. Education: Bachelor of Mathematics, University of Wollongong, 1996 PhD in Mathematics, University of Cambridge, 2000 Research interests include multiscale problems , probabilistic PDEs , and numerical methods , with contributions to homogenization theory, Bayesian inversion, and computational fluid dynamics. Current grants support his work on multiscale systems and stochastic modeling. Key achievements include pioneering finite element methods for multiscale equations and developing Bayesian frameworks for inverse problems. His lab collaborates on interdisciplinary projects in mathematical physics and biomedical engineering.

• Multiscale Problems
• Probabilistic Partial Differential Equations
• Numerical Analysis
• +3 more

Dr. Sasani Jayawardhana is a full-time Lecturer at the University of Colombo, where she co-founded the ALOeKA research facility to integrate artificial intelligence with spectroscopic techniques in materials science. Her academic journey includes a BSc in Physics from the University of Colombo, a PhD in nanostructured sensors from Swinburne University of Technology, and postdoctoral research in optical instrumentation at the University of Sri Jayewardenepura. She has pioneered low-cost experimental setups, including optical fiber sensors and Raman spectrometers. Education: BSc (Physics, University of Colombo), PhD (Swinburne University), Postdoc (University of Sri Jayewardenepura) Her research focuses on leveraging machine learning to accelerate materials discovery, particularly in nanotechnology and optical sensing. Key areas include SERS (Surface-Enhanced Raman Scattering), biomimetic surface engineering, and energy harvesting systems. Her work bridges experimental physics with computational tools, emphasizing cost-effective instrumentation for global accessibility. Publications highlight innovations like solar radio burst analysis, gemstone identification via Raman-ML hybrid systems, and low-cost lab equipment. These advancements underscore her commitment to both theoretical and applied materials science. No scientific awards are explicitly noted, but her contributions to accessible research tools and interdisciplinary collaboration are notable. She has advised no listed students but has mentored teams in lab development. The ALOeKA facility exemplifies her vision for integrative research frameworks.

• Materials Science
• Machine Learning
• Nanotechnology
• +3 more