SmartSat PhD Webinar

Join us for this webinar with current SmartSat PhD students as they showcase their research, the outcomes of their projects and the lessons learned along the way.

This webinar will feature:

• Geekiyanage Deepa Rakshitha De Silva (Deakin University) | P1.27 Cognitive Satellite Radios
  Rakshitha has a strong background in Telecommunication. He obtained his honours degree of Bachelor of the Science of Engineering in Electrical & Electronic Engineering from the University of Peradeniya, Sri Lanka and pursued his Master of Science in Telecommunications from the University of Moratuwa, Sri Lanka. His present research focus is on intelligent spectrum management in satellite networks. He has around nine years of work experience in the field of mobile telecommunication engineering and several professional certificates in networking complementing his academic studies. 
  
• Xiongren Chen (University of South Australia) | P2.47s Interpretable Machine Learning for the Early Smoke Wild-fire Detection
  Xiongren has a master’s degree in computer science from the University of Adelaide and an MSc in computational finance from the University of Essex. His research is focused on explainable machine learning, which is a rapidly expanding area of study that aims to make machine learning more accessible to non-experts by providing clear and understandable explanations for how the system reaches its conclusions. Specifically, Xiongren is interested in improving explainable machine learning methods for satellite images in computer vision. Through his work, he hopes to advance the field and develop techniques that enhance the effectiveness of machine learning while also making it more transparent and interpretable. Xiongren has already published 2 papers and one of them has been accepted by the AAAI Conference on Artificial Intelligence, one of the most prestigious international conferences in the field.
  
• Francesca Devoto (University of Queensland) | P3.35s Phenotyping of cotton production traits for different management and environment options utilising high-resolution remote sensing technologies
  Francesca Devoto is an agronomist and PhD student at the University of Queensland. Devoto received a bachelor degree in Agricultural, Forestry and Environmental Sciences in October 2020 and a Master’s degree in Agricultural Science and Technologies in April 2023, both with honours, from the University of Naples “Federico II”. Devoto’s thesis work was based on the phenotyping of 10 varieties of rice under two different nitrogen regimes through the processing of multispectral images acquired by drone and direct observation at the canopy and leaf scales.

Please note this event is at 2.00pm ADST (Adelaide) time.