What we’re about
We are data scientists in Canberra. We organise seminars and workshops to share knowledge and experiences in data mining, machine learning, data science and analytics. We also get together for bush walking and networking. Join us to have fun, get fit, make new friends and share knowledge.
Organisers:
Yanchang Zhao
Warren Jin
Richard Gao
Former Organisers:
Jin Li
Dharmendra Sharma
Upcoming events (1)
See all- Seminar: Detecting the Subtle: Fine-Grain Learning for Sparse, and Weak SignalsSynergy Building, CSIRO, Black Mountain, Acton
This is a joint hybrid event by the IEEE Geoscience and Remote Sensing Society ACT&NSW Joint Chapter, the IEEE Computer Society ACT Chapter, and the Canberra Data Scientists Meetup. After the talk, there will be free pizzas and soft drinks provided to encourage people to stay after the presentation and socialise with others. RSVP is required, please following instructions below for registration.
Title: Detecting the Subtle: Fine-Grain Learning for Sparse, Noisy, and Weak Signals in Earth and Space Observations
Speaker: Dr. Ali Zia, La Trobe university
Hosts:
- Yiqing Guo (IEEE GRSS)
- Warren Jin (IEEE CS)
- Yanchang Zhao (CDS)
Date: Monday 12 May 2025
Times:- 4:00pm ~ 5:00pm - Presentation
- 5:00pm ~ 5:30pm - Food/Networking
Venue: Acacia Room, Ground Floor of Synergy Building (B801, corner of North Science Road and Dickson way), CSIRO Black Mountain Science and Innovation Park, Acton ACT
RSVP for In-Person Attendees: Please register here if you are attending in person: Attendance Sheet for In-Person Attendees. To assist in catering, please register by 6pm Saturday 10 May 2025. Parking information is also provided at the link. When you arrive at the Synergy Building foyer, please sign in using the iPad at the counter. Enter 'Yiqing Guo,' 'Warren Jin,' or 'Yanchang Zhao' as the person you are visiting. Attach the printed name tag to your chest and wait to be collected.
RSVP for Online Attendees: Please register here if you are attending online: Attendance Sheet for Online Attendees A Teams link will be sent to your email before the event.
Event Sponsor: SHURAAbstract: From early-stage disease detection in crops to tracking faint space debris, many high-impact problems in agriculture and aerospace involve limited data, weak signals, and complex backgrounds. This talk presents a unified perspective on fine-grain analysis techniques designed for such challenging conditions. Drawing from real-world applications in precision farming, hyperspectral remote sensing, and space target detection, I will introduce methods that leverage weak supervision, higher-order representations, and sparse learning. These approaches are not only effective in extracting nuanced patterns from noisy environments but also demonstrate potential for broader generalization in data-scarce settings. The session will highlight insights gained through practical case studies, including meat contamination detection and mineral exploration, and offer directions for interdisciplinary research in sparse and uncertain domains.
Bio: Dr. Ali Zia is an accomplished Computer Scientist with over fifteen years of expertise in Artificial Intelligence (A.I.), HyperSpectral Imaging (HSI), and Higher-order Representation Learning. Proven track record in leading interdisciplinary research and developing innovative AI-driven solutions across academia and industry. Extensive experience in machine learning applications, precision agriculture, healthcare AI, and intelligent systems. Adept at curriculum development, student mentorship, and advancing educational frameworks. Recognised for pioneering research in hyperspectral imaging for 3D computer vision, AI-driven disease detection, and smart home automation. Committed to pushing the boundaries of AI and contributing to technological advancements with significant real-world applications.
Homepage: www.ali-zia.me
