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Keynote Speakers


Prof. Shum Ping, Director, Centre for Optical Fibre Technology, Nanyang Technological University, Singapore


Prof Shum received his PhD degree in Electronic and Electrical Engineering from the University of Birmingham, UK, in 1995. In 1999, he joined the School of Electrical and Electronic Engineering, NTU. Since 2014, he has been appointed as the Director of Centre for Optical Fibre Technology and was the chair, committee member and international advisor of many international conferences. He was also the founding member of IEEE Photonics Society Singapore Chapter (formerly IEEE LEOS). He is currently the chairman of OSA Singapore Chapter. Prof Shum has published more than 500 journal and conference papers with his research interests being in the areas of speciality fibres and fibre-based devices. His H-index is 30. In recent few years, his publications have been cited about 500 times per year.

Speech Title: Novel Fiber Sensing System
Abstract: Optical fiber-based devices have been widely deployed in recent years. There are many advantages of using fiber as a sensor. These include electrically-passive operation, light weight, immunity to radio frequency interference and electromagnetic interference, high sensitivity, compact size, corrosion resistance, easily multiplexing and potentially low cost. Several novel fiber-based sensors and technologies developed are presented here, including fiber Bragg grating (FBG) based sensors, photonic crystal fiber (PCF) based sensors, specialty fiber-based sensors and distributed fiber sensing systems. FBGs as instinctive sensors, are ingeniously designed as two-dimensional (2D) tilt sensors, displacement sensors, accelerometers and corrosion sensors here; PCF based evanescent field absorption sensor, PCF induced Mach-Zehnder interferometer and Fabry-Perot refractometer for temperature and refractive index sensing are presented; based on localized surface Plasmon resonant (LSPR) effect, nano-sized fiber tip with gold nanoparticles are demonstrated for live cell index bio-sensing applications.



Dr. Dora Juan Juan Hu, Institute for Infocomm Research, Singapore


Dora received her B.Eng (1st Hon.) and Ph.D degree from the school of Electrical and Electronic Engineering, Nanyang Technological University, Singapore in 2004 and 2010 respectively. She joined the RF & Optical Department, Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore from 2009 to 2012 as a scientist and principle investigator to develop novel fibre devices for sensor applications. In 2012 she received A*STAR post-doctoral fellowship (2012-2014). In 2012 she joined the Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, USA as a research fellow and worked on novel photonic technologies for endoscopic diagnosis. Dora joined the Femtosecond Optics Group, Imperial College London in August 2013 and worked on visible and mid-infrared fibre lasers. She is now with the Infrastructure Department, Smart Energy and Environment Cluster, Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore as the department head and working on novel photonic technologies for sensing and biomedical applications.

Speech Title: Photonic crystal fibers for disruptive sensor technology

Abstract: In recent years, photonic crystal fibers (PCFs) with novel microstructures and materials have received significant attention by sensor community. By tailoring their waveguiding properties and material properties, many new sensors and sensors with enhanced performance have been proposed and demonstrated based on specialty fibers. The flexibility in controlling the light-matter interaction in the PCF fiber sensors is demonstrated in both theoretical and experimental studies. In this talk, various PCF-based sensor configurations and applications are presented and discussed.



Prof. Dr. S. Vasavi, VR Siddhartha Engineering College, India


Dr S.Vasavi is working as a Professor in Computer Science & Engineering Department with 20 years of experience. She pursued her MS from BITS, Pilani in the year 1999 and PhD from Acharya Nagarjuna University in the year 2010. She currently holds R&D projects from UGC and ISRO-ADRIN. She published 44 papers in various Scopus indexed conferences and journals. She filed two patents. She is the recipient of UGC International travel grant in the year 2015, for her visit to ICOIP 2015,USA and TEQIP grant for her visit to ICICT 2016, Thailand. She visited reputed universities at U.S.A and Thailand. She also Visited Argonne National Laboratory, A multidisciplinary Science and Engineering Research Center, that address vital national challenges in Clean Energy, Environment, Technology and National Security. Argonne is managed by Chicago Argonne, LLC, for the U.S. Department of Energy's Office of Science. She is an IEEE member, life member of Computer society of India (CSI), Member Machine Intelligence Research Labs , Washington , USA. Her Research Areas are Bigdata analytics: Image object Classification. Reviewer for Scopus Indexed journals [Inderscience, Image vision and computing, Bigdata Journal] and conferences [Springer, IEEE, Elsevier]. Received Best Teacher Award, Vishitta Mahila Award, Conferred Outstanding Women in Engineering Award

Speech Title: Moving Object Classification in a video sequence under Illumination changes

Abstract: The technique of moving object detection and classification from video sequence is important in many applications such as such as airports, banks, military installations etc. Monitoring of data collected from the video cameras by human operators manually for long durations is not feasible in real time and may lead to inaccurate results. Recorded videos are analyzed only when any unwanted event occurs that may help for recovery and not avoidance. Outdoor environments are more challenging for moving object classification because of incomplete appearance details of moving objects due to occlusions and large distance between the camera and moving objects. As such, there is a need to monitor and classify the moving objects by considering the challenges of video in the real time..