WINNER, 2018 CORE JOHN MAKEPEACE BENNETT (AUSTRALASIAN DISTINGUISHED DOCTORAL DISSERTATION) AWARD
Before starting the postdoc appointment, he graduated as a PhD supervised by Prof. Yufei Tao in the School of ITEE at UQ in 2017. He obtained his bachelor and master degrees from School of Software, Sun Yat-Sen University, in 2011 and 2013, respectively.
His research interests are to design practical algorithms with non-trivial theoretical guarantees for solving problems on massive data. He has published several papers at SIGMOD and TODS. He also won the Best-Paper Award at SIGMOD 2015.
WINNER, 2018 CORE CHRIS WALLACE AWARD FOR OUTSTANDING RESEARCH
Lexing Xie is Associate Professor in the Research School of Computer Science at the Australian National University, she leads the ANU Computational Media lab (http://cm.cecs.anu.edu.au).
Her research interests are in machine learning, multimedia, social media. Of particular recent interest are stochastic time series models, neural network for sequences, and active learning, applied to diverse problems such as multimedia knowledge graphs, modeling popularity in social media, joint optimization and structured prediction problems, and social recommendation.
Her research is supported from the US Air Force Office of Scientific Research, Data61, Data to Decisions CRC and the Australian Research Council. Lexing’s research has received six best student paper and best paper awards in ACM and IEEE conferences between 2002 and 2015. She is IEEE Circuits and Systems Society Distinguished Lecturer 2016-2017.
She currently serves an associate editor of ACM Trans. MM, ACM TiiS and PeerJ Computer Science. Her service roles include the program and organizing committees of major multimedia, machine learning, web and social media conferences. She was research staff member at IBM T.J. Watson Research Center in New York from 2005 to 2010, and adjunct assistant professor at Columbia University 2007-2009. She received B.S. from Tsinghua University, Beijing, China, and M.S. and Ph.D. degrees from Columbia University, all in Electrical Engineering.
WINNER, 2018 CORE TEACHING AWARD
Dr Antonette Mendoza is a Senior Lecturer in the School of Computing and Information Systems at the University of Melbourne. She has received a citation for ‘Outstanding Contributions to Student Learning’ in the 2017 Australian Awards for University Teaching, a national-level recognition for her work. She is also the recipient of the 2017 University of Melbourne Edward Brown Teaching Award, 2018 CORE teaching award and three faculty and department wide teaching awards. Her work recognizes outstanding leadership and innovation in enhancing academic teaching, resulting in enriched student-learning experiences.
Antonette’s research and teaching impacts on two areas: disadvantaged socio-technical contexts and engineering education. Her research focuses on design and change behaviour methodologies in software engineering and information systems using emotional attachment pedagogies. She is currently involved in Australian Research Council (ARC) and Cooperative Research Council (CRC) grants to develop sustainable systems for both the homeless and educational training for low carbon living. Some of her prior work includes collaborations on a National Health and Medical Research Council (NHMRC) grant to design a predictive tool for depression care. Her current interests lie in the design and delivery of online programs using appropriation and emotional attachment pedagogies.
FACULTY OF INFORMATION TECHNOLOGY, MONASH UNIVERSITY
Ann Nicholson is a Professor in the Faculty of Information Technology at Monash University. After completing her BSc (Hons) and MSc in Computer Science at the University of Melbourne, she was awarded a Rhodes scholarship to Oxford, where she did her doctorate in the Robotics Research Group. After completing a post-doc at Brown University, she returned to Australia to take up a lecturing position at Monash.
Prof. Nicholson researches in the broad areas of Artificial Intelligence and machine learning. She is a leading international researcher in Bayesian networks, now the dominant technology for probabilistic causal modelling in intelligent systems. She has applied Bayesian Network technology to problem-solving in many domains including meteorology, epidemiology, medicine, education and environmental science.