ASSOCIATE PROF. IR. TS. DR. LAI KHIN WEE
Department of Biomedical Engineering
Faculty of Engineering
lai.khinweeum.edu.myView CV | |
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Biography | |
Dr Lai received his PhD from Technische Universitat Ilmenau, Germany and Universiti Teknologi Malaysia (UTM) under DAAD PhD Sandwich Programme, and conferred with Chancellor Award from Queen of Johor. He is currently an Associate Professor, and Head of Biomedical Engineering Department, and CTO of BioSight Sdn Bhd (spin-off company of Universiti Malaya). Prior to this, He was affiliated to Technische Universitat Ilmenau, Germany as Doctoral scholar under DAAD (Deutscher Akademischer Austausch Dienst) PhD Sandwich Programme. Dr. Lai pioneered industry-academic engineering programs associating several industrial consultation projects. He has contributed immensely to the development and enhancement in science & technology in Malaysia, particularly in the field of medical engineering. Amongst his significant achievements include the development of a portable, non-invasive device for scoliosis early detection and post-surgery progression monitoring, production of a novel POC device for knee osteoarthritis detection using VAG approaches and, more recently is the tailoring of a novel machine learning approaches that is able to perform cartilage pattern recognition in Magnetic Resonance Images without much human intervention. His work has attracted great interest from the industries locally and internationally. Besides being recognized by students and peers for his excellence as an educator, his contribution in biomedical imaging and Point-of-Care devices research has made him a regular recipient (more than 30 awards) of numerous international and national awards: multiples Special Awards and Gold Medals, Best of the Best Awards from ITEX, MTE, i-ENVEX, AiNEX, PECIPTA, BioMalaysia Expo, and other innovation and technology events organized by the Ministries agency in Malaysia. As for the global competitions, Dr. Lai’s research prototype has represented UM to participate iCREATe global challenge organized in Singapore, Thailand, and Japan in 2015, 2016 and 2017 respectively. In addition, he had received conference best presentation award from Fukuoka University Japan in 2015, the Best Sustainable Prototype Award in Digital Wonderland Singapore Expo 2019, awarded Honorable Mention Award in 2020 NSIEC by NCKU Taiwan,First runner-up of Brunei Crown Prince CIPTA 2021 Award, and elected as Member of Young Scientists Network - Academy of Sciences Malaysia (YSN-ASM) 2021. He upholds his academic pursuit by authoring more than 140 peer-reviewed ISI/WoS- and Scopus-listed publications, proceedings, book chapters, laboratory worksheet and guidelines (h-index 20). His innovations in his areas of expertise awarded him 17 patents and intellectual property rights and several major governments, industries, and international funded projects as principal investigator/Co-researchers (completed 22 projects, 13 projects on-going) in collaboration with local and international researchers. Dr. Lai is a registered Professional Engineer with Practicing Certificate (PEPC) at Board of Engineers Malaysia (BEM), Fellow of the Engineers Australia (FIEAust), APEC Engineer IntPE(Australia), and Chartered Professional Engineer (CPEng.) at NER (Australia), Fellow and past Council member of the Institute of Engineers Malaysia (IEM), Senior Member of IEEE (USA), and Member of the Institution of Engineering and Technology (IET), and U.K. Chartered Engineer (CEng.) and Professional Technologist at MBOT Malaysia. He has been invited to contribute as Technical Programme Committee (TPC) and designated reviewer for more than 50 international conferences, workshops and journal publishers. Following to that, he has been a regular speaker for more than 20 international conference papers and workshops. Besides, he devoted himself to academic community by serving as international journal editorial board members in several indexed journals including Associate Editor of IEEE Access, Frontiers in Public Health, IET Image Processing, and served as Lead Guest Editors of Multimedia Tools and Applications, Current Medical Imaging and etc. He is the key resource person for the engineering programme curriculum review and accreditation exercises (EAC/MQA/QMEC) in his department, and served as EAC Accreditation Panel under the purview of Board of Engineers Malaysia. Dr Lai has been appointed as Fellow by Ministry of Education, Malaysia under CEO@Faculty Programme since September 2018, affiliated to CEO Office, PLUS Malaysia Berhad (PMB) – Datuk Azman Ismail, to work directly with C-suite level top management on policies, strategy planning in digital innovation transform to drive business embarking IR4.0. He drafted the strategy for commercial potentials of the imminent PLUS Video Analytics (VA) Infrastructure. Part of its strategy, he proposed the needs to develop and continuous improve on a variety of regression and analytical models based on the real-time output of VA, as well as a variety of templates for Reports, Dashboard and API that ensures output from the VA models are actionable by various Divisions of PMB (Commercial, Operational and TechInno).The entire VA projects’ investment costs more than Malaysian Ringgit twenty million, and Dr Lai served as one of the panels evaluating multiple Proof-of-Concepts (POC) stages and tenders from multinational companies. Dr. Lai was awarded an ACU Fellowship by the Association of Commonwealth Universities by UK in 2021 for his research on the risk of hospital readmission among recovered COVID-19 patients. Following to that, Dr. Lai has been conferred The IEM Young Engineer Award 2021; one of the most prestigious awards by President of Institute of Engineers Malaysia during its AGM, in recognition of his research excellence and contribution to the profession and nation. Dr. Lai was also awarded the IEEE-EMBS Early Career Achievement Award 2021 by the IEEE EMBS Malaysia Chapter the same year. In 2022, Dr Lai was bestowed the BEM Malaysia Most Prominent Young Engineering Leader Award by the Prime Minister Malaysia. Dr. Lai currently heads Advanced Analytic Research Group at Medical Imaging Laboratory, and supervised 55 postgraduate students (15 PhD, 8 MSc and 19 MEng completed, 12 PhD and 1 MSc on-going). His research group has secured more than RM2millions of research funding for numerous projects relating to healthcare technology, medical imaging and bioinstrumentation. He and his teams developed two prototypes that contribute significantly to the clinical diagnostic setting and protocol in the hospital, namely OsteoKneeKitTM, and Scoltech. These prototypes are currently under commercialization stages and have been featured by multiple Medias and magazine. A spin-off company under UM Deep Tech accelerator programme for ScoltechTM with capital RM50K has been approved and led by Dr Lai as CTO. Meanwhile, he is serving in numerous capacities as external examiner (PhD and Master Dissertations both locally and internationally), professional mentor of IEM (Malaysia) and EA (Australia), resource person, external assessor (HLAF), advisor of Industry Liaison Unit (Asia Pacific Region), Industry Advisory Panel (IAP), and Universiti Sains Islam Malaysia (USIM) Board Member for new technologist programme. |
Publication
Finance
Project Title | Progress | Status |
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Advanced Diagnostic Technologies Using Deep Learning, Graph Neural Networks, And Medical Imaging, Biosensors, And Biomems |
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new |
Elucidating Knee Osteoarthritis Multi-biomarkers For Pain Associated Radiological Features Prediction In Response To Nonpharmacological Interventions Using Multi-task Deep Hybrid Learning |
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on going |
Correlation of Detoxification of High Blood Pressure Subjects with Reflexology Approaches |
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on going |
This information is generated from Research Grant Management System |
Impact of visual enhancement and color conversion algorithms on remote sound recovery from silent videos
Electroencephalography (EEG) based epilepsy diagnosis via multiple feature space fusion using shared hidden space-driven multi-view learning
Histopathological Cancer Detection Using Intra-Domain Transfer Learning and Ensemble Learning
Enhancing early breast cancer diagnosis through automated microcalcification detection using an optimized ensemble deep learning framework
Medical Imaging Technology: Reviews and Computational Applications, Lecture Note in Bioengineering. Springer, DOI 10.1007/978-981-287-540-2 ISBN 978-981-287-539-6 ISBN 978-981-287-540-2 (eBook) Library of Congress Control Number: 2013934273
Advances in Medical Diagnostic Technology. Lecture Notes in Bioengineering. Springer
Detection of Fetal Abnormalities Based on Three Dimensional Nuchal Translucency
Ultrasound Image Processing: And Its Application Using Matlab
Measurement of Ultrasound Attenuation and Protein Denaturation Behavior During Hyperthermia Monitoring
Position Tracking Systems for Ultrasound Imaging: A Survey
Review on Image Guided Lung Biopsy
B-Mode Ultrasound Imaging Contrast Enhancement for Osteoarthritis Early Detection