Daniel is a PhD candidate in the Research School of Computer Science at the Australian National University (ANU) in Canberra. He is an external student based in the Machine Learning Research Group at Data61, the digital innovation unit of the Commonwealth Scientific and Industrial Research Organisation (CSIRO).
Daniel’s research focuses on the development of algorithms that can learn from and make predictions about data. In particular, he investigates methods for learning representations of data that can be used to demonstrably improve prediction performance. The success of machine learning algorithms is highly dependent on the features they receive as inputs, which have traditionally been handcrafted by human experts. However, cutting edge techniques allow the algorithm to learn such features itself from raw data, similar to the way that humans learn more abstract representations of complex sensory inputs. This has led to state-of-the-art results in applications such as natural language processing and computer vision. Daniel’s research focuses on the theoretical foundations behind such methods in order to better understand and improve upon them.
Daniel has authored academic publications from previous research projects in data mining and the digital humanities. He completed his Honours year in Computer Science at ANU, for which he received a University Medal. He holds a Bachelor of Science/Bachelor of Arts from the University of Melbourne, which included receiving the Google Computer Science Prize. He also has experience in the intelligent use of data in professional contexts, including at the online analytics platform Kaggle, the management consulting firm Nous Group, and the Australian Labor Party. He is the founder of the website lovemetender.com.au, an open democracy project allowing individuals and businesses to visualise government spending on commercial tenders.
Daniel will be spending several months at Carnegie Mellon University (CMU) in Pittsburgh. During his stay he will be hosted by A/Prof Maria-Florina Balcan and will be based in the Machine Learning Department within the School of Computer Science. CMU sits in the elite tier of universities worldwide for computer science, and is particularly known for its strength in fundamental theoretical research in machine learning. Daniel is looking forward to the opportunity to learn from and collaborate with CMU academics and students. Following his return to Australia, he will use the skills gained from the visit within academia and industry.