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Xuan-Duc Nguyen  
Thao Minh Le  
Dung Nguyen 
Tin Pham  
Romero de Morais 
Hung Le 
Tung Hoang 
Kien Do  

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 Trang Pham  
Tu Dinh Nguyen  
Shiva Gopakumar  

Truyen Tran (Trần Thế Truyền) Associate Professor, Applied Artificial Intelligence Institute (A2I2) & School of IT, Deakin University. 75 Pigdons Rd, Waurn Ponds, Vic 3216, Australia truyen.tran {__AT__} deakin.edu.au

Research thrusts Deep learning and beyond Cognitive architectures Learning to reason Graph & relation Deep generative models Machine learning for biomedicine Drug design Algebraic structure of care Personalized medicine Learning over structured data Structured input/output Multiway data Multirelational Machine learning for science Computational chemistry Materials science Quantum machine learning Machine learning for a better world Automated software engineering Anomaly detection Process analytics Recommender systems

News/Media (06/2019) PhD scholarships available for late 2019 intake. Areas: deep learning, machine reasoning, reinforcement learning, Bayesian optimization. (06/2019) I gave an invited talk at Genomic Medicine, Hanoi June 2019. (06/2019) I gave an invited talk at AI Day, Hanoi June 2019. (05/2019) I gave an invited talk on Empirical AI Research at International University, HCM City, May 2019. (04/2019) I will speak at Southeast Asia Machine Learning (SEA ML) School in July 2019. Hope to see you in Depok, Greater Jakarta, Indonesia. (02/2019) I will give a keynote speech at MAPR in HCM City, Vietnam in May. The topic will be about representation learning of graphs. (01/2019) I gave a talk on "AI for matters" at Phenikaa University, Hanoi, VN. (01/2019) I gave a talk on "Deep learning for biomedicine: Genomics and drug design" at Vin's Big Data Insitute, Hanoi, VN. (01/2019) TechXplore covers the upcoming ICSE'19 paper on AI for agile project management. (11/2018) A postdoc wanted to work on Deep Learning and Beyond. Requirements: PhD + proven track record in machine learning and related areas. (10/2018) More PhD students wanted for early 2019 intake. Areas: Deep learning & Bayesian optimization.  Update (01/11/2018): Xuan-Duc Nguyen (from VNU, Hanoi) is joining the team! [Older news]

• Lecture on Deep learning for biomedicine, Southeast Asia Machine Learning (SEA ML) School, Depok, Greater Jakarta, Indonesia, July 2019.
• Deep learning for genomics: Present and future, Genomic Medicine 2019, Hanoi, Vietnam, June 2019.
• Memory advances in Neural Turing Machines, AI Day, Hanoi, Vietnam, June 2019.
• Empirical AI Research , @International University, HCM City, Vietnam, May 2019.
  
• Representation learning on graphs, Keynote at MAPR, HCM City, Vietnam, May 2019.
  
• AI that/for matters, @Phenikaa University, Hanoi, Vietnam, Jan 2019.
• Deep learning for biomedicine: Genomics and Drug design, @Institute of Big Data, Hanoi, Vietnam, Jan 2019.
• Advances in Neural Turing Machines, @CafeDSL, University of Wollongong, Aug 2018.
• Deep learning for episodic interventional data, ISCB-ACS 2018, Melbourne, Aug 2018.
  
• Deep learning for astronomy at Harley Wood School for Astronomy, Ballarat, Australia, June 2018.
• Tutorial on Deep learning for biomedical discovery and data mining, PAKDD'18, Melbourne, Australia.
• Tutorial on Deep learning for biomedicine, ACML'17, Seoul, Korea.
• Deep neural nets for healthcare, @Amazon Seattle, Feb 2017.

• Deep learning for detecting anomalies and software vulnerabilities, @Academy of Cryptography Techniques, Hanoi, Vietnam, Jan 2017.
• Deep architecture engineering, @Hanoi Uni of Sci and Tech (HUST); and NU Uni of Eng and Tech (VNU-UET), Jan 2017
• Deep learning, @WEHI, Melbourne, Dec 2016.
  
• Tutorials on Deep learning: AusDM'16 in Canberra, AI'16 in Hobart.
• Deep learning for non-cognitive domains, @DSL, University of Wollongong, Aug 2016.
  

• When computing meets statistics, @Department of Statistics, Hanoi University of Science, VNU, 2009.
• On some optimisation problems in structured pattern recognition, OptiSciCom09, Ba Vi, Hanoi, Vietnam, 2009.
• RecSys: Recommender Systems, BarCamp Hanoi, 2009.

Patents

• Medical data processing for risk prediction, Truyen Tran, Santu Rana, Quoc-Dinh Phung, Wei Luo, and Svetha Venkatesh, Provisional patent, June 2013.