Achivement Summary and Bio
Firstly, please see my achievement summary as well as my brief bio
I started research 20 years ago mostly working alone, until 2016 when I started building a very large team. We have developed many research, engineering prototypes, demos, research notes and commercial projects. Because of such a long time span, my (our) digital footprint is all over the web. Therefore, I organized them into a single repository. Please click these links below:
My continously updated machine learning notes
Firstly my constantly updated machine learning notes! It has 46 traditional and emerging research topics, and currently has 6600 GitHub stars!
10% of the materials were recorded in Mandarin-speaking videos in 2015 and became viral.
- YouTube link has 6000+ subscribers!
- Bilibili link has 18000+ subscribers!
My computer vision Demos in YouTube
Between 2006 to 2009, I have built at least a dozen state-of-the-art AI systems based on computer vision at CSU. In addition to being a researcher, I am also an excellent engineer. I built most of these systems myself, including research, coding, purchasing, and even the hard carpentary work of installing the cameras. Here are the links to my video demo channels:
- YouTube Demo Channel one and YouTube Demo Channel two, circa 2005-2009, contains nine demo systems. including PTZ camera control, face tracking, augmented reality, automated whiteboard capturing, body pose tracking, etc. Note that these two channels have overlaping videos.
- My TV Interview with Prime TV, Prime TV news team came to interview me at CSU to talk about my computer vision work in 2009.
My student's computer vision Demos in YouTube
Fortunately, since 2017, I finally have a laboratory space at UTS to continue computer vision. These are some examples of resume work for my postdoctoral and PhD students:
- My lab team's video demo, circa 2017-2019 developed by my research and engineering team. You can see this is a modern version of what I built previously (now using Deep Learning!)
- Marker less mulitple people tracking, published by my student, Taohui (Carter) Huang Cong in ECCV 2020.
Global Machine Learning meetup community
In 2016, I started (with my co-founder) one of the largest global meetup groups focused on AI knowledge sharing. To date, it has nearly 5,200 members globally. Its members include industry data scientists, academics, researchers, start-ups, and talent recruiters. We are proud to have a range of sponsors (for venues and catering) including Google, AWS, Deloitte, KPMG, QBE, Atlassian and Servian. and a range of internationally renowned speakers from industry and academia. In 2022, I have expanded it to Sydney (flagship), Hong Kong, Melbourne and Athens. I am actively looking for co-organizers in these cities.
List of Funded Industry Contractural Research Projects
This is my official UTS website which shows all the projects that I am the first Chief Investigator since 2015 (approx AUD$2 millions). The funded project names are extracted from the UTS Grants database. My research partners include, Transport for NSW, Sydney Trains, NSW DFSI, Magellan financial group, CSIRO, Ausgrid, CCH Australia, DSTG, Office of Naval Research, NSW DPI,Food Agility CRC (with Dairy Australia, Coles, USYD, CSU and DataGene). In addition, two Australian companies requested not to list the company & project name due to commercial confidence.
Led $900K Newcrest Mining project in 2008
When I was 30 years old working at Charles Sturt University as a lectuer in 2008, I became in charge of a large industry research team composed of senior lecturers and even associate professors! The above is a link to the 2008 annual report from CSU, which contains the following paragraph:
Dr Richard Xu, a lecturer in computer science at the School of Accounting and Computer Science, has begun leading a three-year project to develop a truck-mounted prototype with video camera, sonar and radar to automate a mining process when large rocks jam the rock crusher. The device could prevent costly shutdowns of plant. Newcrest Mines provided $900,000 to fund the project.
Cloud demo: ridll.com
RIDLL is an acronym for Richard Xu's Deep Learning Lab: This Cloud based demo website has about nine research demos developed by my talented team since 2016. Some notable examples include:
- What-If scenarios planning for sydney train networks The number in the circle represents the estimated number of people on the train using our prediction algorithm based on tap-on/tap-off information alone. Click a moving train to bring up a timetable to create a what-if scenario - it also support multi-person-interactions. Completed in 2017. (Note all the data are synthetically generated)
- Automatic word-completion tool for writing Job Descriptions the language model was trained using 140,000 job description data. Completed in 2016. (it may take about 30 seconds to load)
- Web Tool for optimal maintenance planning using TSM algorithm a software tool (complete with web interface) to compute the most cost effective maintenance schedule using Travelling Salesman's Algorithm. Completed in 2020.
- Natural Language to SQL Translation completed in 2016.
some of the links do not work due to changes in Google API.
World Champion in IEEE Games Conference's Micro-RTS competition
In 2019, my postdoctoral fellow Dr. Jason Traish led a team of my PhD students to win the IEEE Games Conference's Micro-RTS competition. Our Reinforcement Learning based AI bot, UTS_Imass has a significantly higher win rate compare to the second best team. You can visit the official website of IEEE Games Conference https://ieee-cog.org/2019/competitions_conference/ then click the "Competition Site" link to browse the above Goolge document in the same way.
My LinkedIn
I am super connected with industry in Australia and internationally. In the past five years, I have interacted with at least 136 companies in ASX200. I have 12,000+ LinkedIn contacts.
International Industry Collabration and outreach
- I had a funded UTS research project, with China/Middle East e-commerce retailer company, https://www.jollychic.com/, 2018 - 2019
- I visited Singapore in 2019 and met many Singaporian business leaders and entrepreneurs to discuss the possibilities of AI, including Huttons Realestate Group, MM2, Chartered Accountants Singapore, Asia One, Moran Lewis Stamford Singapore, Singapore Press Holdings etc.
My Publications
- I published at many top international conferences, including AAAI, IJCAI, ECAI, ECCV, AI-STATS and ICDM
- I also published at many prestigeous IEEE Transactions: IEEE-(T-NNLS, T-Image Processing, T-Signal Processing, T-KDE, T-Mobile Computing and T-Cybernetics).
- I have co-authored with many world-leading scholars, including Chair Prof Arnaud Doucet of Oxford University & DeepMind, Prof Zoubin Gharamanni of Cambridge University & Chief Scientist of Uber.
International Knolwedge dissemination
- In 2018, I have the privilege of being invited by Dr Kai-Fu Lee (founding CEO of Google China, MSRA, Sinovation Ventures) to become a master teacher in his machine learning summer camp DeeCamp, together with Prof Andrew Ng (founder of Google Brain, co-founder of Coursera) and Prof John Hopcroft (Turing Award winner) and twelve other celebrated AI researchers around the world. I was invited again in 2019 and will be again in 2021.
- In 2019, I am honored to be invited by Professor Horst Stocker of the Frankfurt Institute for Advanced Research to conduct a 2-hour machine learning course/seminar, together with other well-known scholars in machine learning, theoretical physics and other science topics, including Prof Christiane Nüsslein-Volhard, a Nobel Prize winner.