The Promise of Deep Tech: Sensor Data Quality in Smart Building
In this session, the panel will discuss the evolution and challenges of sensors in built environment and in generating good data quality. The panel will also explore innovation and R&D work to improve data quality for accurate and reliable data analysis, especially in smart building applications.
This event is part of SWITCH 2021’s and Deep Tech Summit's year-long innovation journey, where the Global and Asian innovation ecosystems meet to discuss and collaborate on the most innovative technology trends and business opportunities. Please register for a complimentary pass to the event and unlock the gateway to global innovation in Asia with the code “SGINNOVATE”.
Date: 7 October, Thursday
Time: 11:00am - 12:00pm (Sinagpore Time / UTC+8)
Programme:
11:00am - 11:05am: Welcome Remarks by SGInnovate
11:05am - 12:00pm: Panel Discussion and Q&A on The Promise of Deep Tech: Sensor Data Quality in Smart Building with:
- Dr Cui Shan, Assistant Head, Mechanical Metrology Cluster 1, National Metrology Centre (NMC), A*STAR
- Dr Jayantika Soni, Co-founder and CTO, Resync
- Dr Chen Jianping, APAC AI & Analytics Translator Lead, PTC
- Moderator: Dr Daniel Cheong, Programme Director, Industrial Internet-of-Things Innovation (I3), A*STAR
Dr Cui Shan, Assistant Head, Mechanical Metrology Cluster 1, National Metrology Centre (NMC), A*STAR
Dr Cui Shan is the Assistant Head of Mechanical Metrology Cluster 1 at the National Metrology Centre (NMC), Agency for Science, Technology and Research (A*STAR). She has more than 10 years of experience in establishing metrological standards and provide measurement solutions to the industry. She has developed a method for autonomous and data-driven calibration of indoor-air-quality sensor networks to ensure measurement accuracy and automatically compensate for sensor drift while minimising lab-based calibration. Her current research work and interest include digitalisation of metrology, measurement quality assurance of sensor networks, and related measurement uncertainty propagation & evaluation. She is also a technical assessor in the area of acoustic and vibration calibration for the Singapore Accreditation Council – Singapore Laboratory Accreditation Scheme (SAC – SINGLAS). She received the SAC Assessor Award (Gold) in Nov 2020.
Dr Jayantika Soni, Co-founder and CTO, Resync
Dr Jayantika Soni is the Co-founder and CTO of Resync, an early-stage startup building and AI-driven energy cloud. She started Resync with her fellow Co-founder, Emir Nurov in late 2017. Resync make both microgrids and cities more energy efficient by advanced control and machine learning algorithms. Dr Soni holds a Ph.D. in Electrical Engineering from the National University of Singapore and a Bachelors Degree from IIT, Varanasi.
Dr Chen Jianping, APAC AI & Analytics Translator Lead, PTC
Dr Chen Jianping is an AI & Analytics Translator Lead, APAC at PTC. His main responsibility is to lead PTC's customers in APAC via ways of investigation, implementation, and deployment of advanced analytics and machine learning technologies by tapping on PTC's products. In this role, his main effort is focused on IoT, especially the Industrial IoT business. Dr Chen is an ICT veteran and has over 15 years of professional experience in OT, IoT, and Analytics. He received a PhD degree in Network Security and Information Security from the National University of Singapore, and MEng degree in Control Theory and Control Engineering jointy awarded by Xiamen University and Tsinghua University, and a BEng degree in Control Theory from Shanghai Jiao Tong University, respectively. He is a Senior Member of IEEE.
Moderator's Profile:
Dr Daniel Cheong, Programme Director, Industrial Internet-of-Things Innovation (I3), A*STAR
Dr Daniel Cheong is currently the Programme Director for A*STAR’s Industrial IoT Innovation (I3), an industry consortium aimed at driving the adoption of Industrial IoT in close collaboration with industry partners.
Prior to I³, Daniel was at A*STAR’s Institute of High-Performance Computing (IHPC) between 2015 and 2017. From 2006 to 2013, he focused on molecular simulations of soft matter systems, such as surfactants and polymers and peptides.
Daniel also previously worked in Medlinx Acacia, a medical device start-up developing surgical implants, where he was the Business Development Director.
Daniel graduated with a Bachelor of Science (with University Honours) in Chemical Engineering from Carnegie Mellon University in 1997. He obtained his Doctor of Philosophy in Chemical Engineering from Princeton University in 2006. He also received his Master in Business Administration from Singapore Management University in 2014.
