AIM_fg Team

Dr Jamie Ng is a Senior Principal Scientist and Division Head of the Advanced & Sustainable Manufacturing (ASM) Division at the Institute for Infocomm Research (I2R), A*STAR, Singapore. She specializes in AI and digital technologies in manufacturing and MRO, specifically smart automated visual inspection systems, digital twins and human-machine interface. Her research covers AI for visual inspection, robotics, mixed reality, IIOT, blockchain, predictive maintenance and sustainability. She collaborates extensively with industry partners to research, develop, deploy and commercialize AI and digital technologies for i4.0 and i5.0. She is also the programme lead for the Smart Automated Aircraft Visual Inspection System (SAAVIS) programme looking into automation of defect detection in large structures and surface, such as aircrafts, ships, vehicles and buildings.

Dr Ng served as an associate chair for the ACM SIGCHI 2015 Paper and Notes programme committee in User Experience and Usability and was part of the 7th management committee for the ACM SIGGRAPH Singapore Chapter. She publishes in ACM SIGCHI, ACM SIGGRAPH, ACM Multimedia, Human Factors and Ergonomics Society as well as IEEE’s International Symposium of Mixed and Augmented Reality. Jamie has a PhD in Human Factors Engineering, an MSc in Smart Product Design and BEng in Mechanical Engineering from the Nanyang Technological University, School of Mechanical and Aerospace Engineering, Singapore. She holds several patents, is a recipient of the Tan Kah Kee Young Inventors’ Award and the 2023 IES Prestigious Engineering Award.

Dr Yang Feng is a Principal Scientist in the Computing & Intelligence (CI) department, Institute of High Performance Computing (IHPC), A*STAR. His research interests include knowledge-driven AI, generative AI for inverse problems, information retrieval, prognostics & predictive modelling for condition monitoring and intelligent decision-making, and digital twin.

Dr Yang received his Ph.D. degree in machine learning and bioinformatics from Nanyang Technological University (NTU), Singapore, in 2012. Before that, he received his B.Eng. degree in information engineering and M.Eng. degree in control engineering from Xi’an Jiaotong University (XJTU), Xi’an, China.

Dr Min Wu is currently a Principal Scientist in Machine Intellection Department, Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore. He received his Ph.D. degree in Computer Science from Nanyang Technological University (NTU), Singapore, in 2011 and B.S. degree in Computer Science from University of Science and Technology of China (USTC) in 2006. He received the best paper awards in EMBS Society 2023, IEEE ICIEA 2022, IEEE SmartCity 2022, InCoB 2016 and DASFAA 2015.

He also won the CVPR UG2+ challenge in 2021 and the IJCAI competition on repeated buyers prediction in 2015. He has been serving as an Associate Editor for journals like Neurocomputing, Neural Networks and IEEE Transactions on Cognitive and Developmental Systems, as well as conference area chairs of leading machine learning and data mining conferences, such as ICLR, NeurIPS, KDD, etc. His current research interests focus on AI for time series data, including representation learning, domain adaptation and foundation models for time series, and their applications in manufacturing.

Dr. Doan Ngoc Chi Nam is a Senior Scientist and Manager of the Manufacturing Decision Support Section at the Singapore Institute of Manufacturing Technology (SIMTech), where he leads a multidisciplinary team in developing and deploying AI-driven solutions for smart manufacturing. His work centres on predictive quality management and predictive maintenance, driving enhanced productivity and operational intelligence on the manufacturing shopfloor.

With over a decade of expertise in AI for smart manufacturing, Dr. Nam has made significant contributions to advancing Singapore’s national digital transformation agenda. He currently serves as the Technical Lead for the Predictive Maintenance pillar of the Artificial Intelligence Centre of Excellence for Manufacturing (AIM_fg)—a flagship initiative spearheading sector-wide AI adoption across the manufacturing industry.

Dr. Nam has led and contributed to numerous initiatives with top-tier industry partners, including Rolls-Royce, Halliburton, Philips, etc. His expertise spans foundational AI model development, predictive analytics, and adaptable shopfloor systems—advancing capabilities that boost efficiency, quality, and resilience in manufacturing operations. Notable projects under Dr. Nam include the Smart Manufacturing Joint Lab 2, the Distributed Smart Value Chain (DSVC) programme, and the Dou Yee Technology Joint Lab.

A strong advocate of both scientific excellence and workforce development, Dr. Nam has authored over 40 peer-reviewed publications and 8 technical disclosures, with citation metrics including over 880 citations, an h-index of 13, and an i10-index of 15. He has also trained more than 200 professionals through national upskilling programmes, contributing to the development of a future-ready manufacturing workforce.

Dr. Nam’s focus aligns closely with Singapore’s National AI Strategy, reinforcing his role in driving innovation, capability building, and industrial transformation at scale.

Dr. Zeng Zeng is a former Group Leader of AI Meets Semiconductor at the Institute for Infocomm Research (I2R), A*STAR. As a Principal Investigator (PI), he has led multiple high-impact projects, including NRF-NSFC, CRP, SMART, and Innovation2Startup.

With over 140 publications in top-tier international conferences and journals, such as AAAI, IEEE T-PAMI, TPDS, and IJCAI, his research spans AI, deep learning, distributed/parallel computing, computer vision, IC manufacturing, healthcare, and transportation.

Dr Zhang Jie is currently the Group Manager of the Intelligent Product Verification (IPV) Group at Advanced Remanufacturing and Technology Centre (ARTC), A*STAR.

Her research background and current interest include vision inspection, computer vision, and AI for industrial applications. With 15 years of experience in deploying image processing and computer vision technologies in industrial settings, she has led her team in delivering impactful solutions that improve product quality and operational efficiency, benefiting a wide range of industries, from multinational corporations to small and medium enterprises.

Dr. Wang Zhenbiao is the Section Manager of the Intelligent Product Verification Group at the Advanced Remanufacturing and Technology Centre (ARTC), where he leads a multidisciplinary team focused on developing intelligent algorithms for vision inspection to accelerate the adoption of AI-driven solutions in manufacturing.

With over 11 years of experience in image processing, deep learning, software development, and system automation, he has built a strong track record in advancing intelligent inspection technologies from concept to deployment. He has driven numerous co-innovation projects with industry partners, advancing AI-assisted vision inspection systems that improve accuracy, reliability, and productivity on the manufacturing floor.

Tan Chin Sheng received his Ph.D. from the College of Computing and Data Science at Nanyang Technological University, where his thesis focused on Inverse Machine Learning for Multi-Criteria Decision Making. His research centers on operations modeling and the application of advanced machine learning and AI techniques to enhance optimization performance. With over a decade of experience collaborating with industry partners, he has helped organizations model, simulate, and optimize their planning operations. His work spans a wide range of areas, including capacity and layout planning, production and inventory planning, as well as detailed operations scheduling and process parameter tuning.

Selected Publications:

• Tan, C.S., Gupta, A., Ong, Y.S., Lam, S.K., Pratama, M. and Tan, P.S., 2024, December. Pareto Set Representation Learning with Application to Multi-criteria Order Optimization. In 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 0947-0951). IEEE.
• Tan, C.S., Gupta, A., Ong, Y.S., Pratama, M., Tan, P.S. and Lam, S.K., 2023. Pareto optimization with small data by learning across common objective spaces. Scientific Reports, 13(1), p.7842.
• Tan, C.S., Gupta, A. and Xu, C., 2022, December. Are two heads always better than one? human-ai complementarity in multi-criteria order planning. In 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 0939-0943). IEEE.

Dr. Xu Meng is a Scientist at SIMTech, A*STAR. She received her Ph.D. in 2024 from the Centre for Data Science & Artificial Intelligence and the School of Engineering and Computer Science at Victoria University of Wellington, New Zealand. Her research interests include evolutionary computation, machine learning for combinatorial optimization, genetic programming, hyper-heuristics, reinforcement learning, job shop scheduling, workflow scheduling, and inventory management.

Dr. Xu has published a number of papers, including in leading journals such as IEEE Transactions on Evolutionary Computation, IEEE Computational Intelligence Magazine, IEEE Transactions on Services Computing, and Artificial Intelligence Review. She is a member of the IEEE Task Force on Evolutionary Scheduling and Combinatorial Optimization and serves as a reviewer for several international journals.

Myat Min is the Coordinating Lead for the AI Center of Excellence for Manufacturing (AIM_fg), where he drives the strategic integration of AI technologies into manufacturing systems. He plays a key role in coordinating technical efforts across multidisciplinary teams, supporting the development of scalable, AI-enabled solutions for productivity enhancement, quality assurance, and smart decision support in factories.

Concurrently, Myat Min serves as the Group Manager of the Smart Virtual Systems (SVS) Group at ARTC. Under his leadership, the group develops intelligent digital platforms, enterprise modelling & simulation, and enterprise multi-resource decision-support systems to enable smarter and more adaptive manufacturing operations. His work includes developing a Smart Manufacturing Platform under R&D programmes (Distributed Smart Value Chain) and collaborative industry projects that deliver real-time planning, enterprise digital twin technologies, and flexible autonomous systems for manufacturers in Singapore.

With a background in system engineering, AI application development, and integrated manufacturing systems, Myat Min has led multiple projects across both public and private sectors. He brings over a decade of experience in digital transformation, and has worked closely with industry partners to deploy scalable solutions that support Singapore’s push toward Industry 4.0.

Myat Min holds a Master of Science from Nanyang Technological University and a Bachelor’s degree in Electronics Engineering. His professional interests include digital transformation, intelligent manufacturing, and the deployment of AI systems in real-world production environments.

Edward Khant Tun currently leads the AI Sandbox initiative under the AI Centre of Excellence for Manufacturing (AIM_fg), where he focuses on building practical AI toolkits and fostering collaborations to help manufacturers adopt AI in scalable and meaningful ways. He also serves as a Senior Research Engineer and Section Manager at A*STAR’s Advanced Remanufacturing and Technology Centre (ARTC) and the Singapore Institute of Manufacturing Technology (SIMTech). His role involves designing and maintaining secure, modular digital systems based on Microservices Architecture, DevSecOps practices, and Kubernetes, contributing to national platforms like the Model Factory@SIMTech. Earlier in his career, Edward was part of the Science and Engineering Research Council (SERC), where he supported strategic R&D portfolio development and helped establish A*STAR’s first Software and Systems Engineering Communities of Practice.

He holds a Bachelor of Engineering (Mechanical Engineering) from the National University of Singapore, graduating with Highest Distinction. Edward is a Certified Kubernetes Application Developer (CKAD) and Certified Scrum Master (CSM), with further training in DevSecOps Engineering and Digital User Experience Design.

Dr Nicholas Tan graduated with First Class Honours in Mechanical Engineering from NTU, with a focus on innovative design. He subsequently joined SIMTech as a Research Engineer and was awarded the A*STAR Graduate Scholarship to pursue a PhD in Mechanical Engineering at NUS. His doctoral research specialised in algorithmic development for the fabrication of complex freeform optical lenses with multi-axis Ultra-Precision Machining (UPM). After which, he returned to the A*STAR family as a research scientist.

Dr Tan is currently the Deputy Group Manager of the Remanufacturing Process Technology group, leading research in sustainable thermo-mechanical process innovation and intelligent solutions for manufacturing process planning and monitoring.

Dr. Ng Lai Xing is a Senior Scientist in I2R from the Visual Intelligence (VI) Department and Advanced and Sustainable Manufacturing (ASM) Division. Currently, he is the Group Leader for the Visual Interaction and Dynamic Augmentation (VIDA), focusing on interactive visual interfaces, dynamic perception and human intelligence augmentation.

His expertise lies in creating algorithms and models that enhance dynamic and real-time visual processing, 2D/3D scene understanding, automated content creation, synthetic visual data generation, procedural task reasoning, and human-in-the-loop operations. In the manufacturing domain, he has developed vision-based solutions for automated aircraft inspection, such as surface defects detection, synthetic defect generation, and AR-enabled wearable assistant applications to provide automated task instructions, real-time video streaming for task guidance and collaboration.

Jung-jae Kim has worked on multimodal data analytics, natural language processing and knowledge engineering for applications including manufacturing, robotics, intelligence and education domains, and is currently Principal Scientist and the leader of Knowledge & Explainable AI Group in the Department of Machine Intellection at Institute for Infocomm Research (I2R), A-STAR, Singapore. He also worked as an Assistant Professor at Nanyang Technological University (NTU), Singapore from 2010 to 2015 and as a post-doctoral researcher for European Bioinformatics Institute (EBI), UK from 2006 to 2009.

He received his PhD from Korea Advanced Institute of Science and Technology (KAIST), South Korea in 2006. He secured and led over 10 industrial and grant research projects and published over 80 peer-reviewed papers at prestigious journals and conferences.