International School in Artificial Intelligence and its Applications in Computer Science (ISAAC)
International School in Artificial Intelligence and its Applications in Computer Science (ISAAC)
Enhancing access to cutting-edge topics in AI and Computer Science
Rated ‘five out of five’ for AI in Australia (ERA National Report), Monash University is proud to host ISAAC, the most exciting graduate school on AI in Australia.
This school gives PhD, Masters and Honours students as well as ECRs across the globe a greater opportunity to engage with state-of-the-art advancements in AI, and computer science more broadly.
During this multi-day academic forum, attendees will enjoy:
- lectures delivered by globally-renowned experts in AI and computer science;
- learning about core theories, tools and techniques in different subfields of AI, such as, machine learning, optimisation, planning, knowledge representation, data science, and more;
- getting insights into innovative research developments and their real-world applications;
- having the opportunity to meet world experts in different areas of AI, and access to a growing network of academics, researchers, and graduate students interested in many aspects of AI.
For ECRs and current PhD students, ISAAC will enrich their education by deep diving into topics ranging from traditional research in AI all the way to new applications in other computer science disciplines. Future PhD students will also benefit from early exposure to graduate research as well as the modern topics and developments in AI and Computer Science that will be explored during this event.
Because ISAAC is an in-person fully funded event, it has a limited number of available places. A link to submit applications to attend the event is below. Notification of the outcome of applications will be sent by 16 October 2023. The deadline to submit applications to attend the Summer school is 30 September 2023.
If you are a Masters or Honours student who does not live in Melbourne, and is interested in both attending ISAAC and doing a PhD in AI or Computer Science, you are eligible for a travel ISAAC scholarship to help cover flights or accommodation. Notification of applications will be sent by 16 October 2023. The deadline to submit applications to apply for an ISAAC travel scholarship is 30 September 2023.
Dr. Gupta graduated with a PhD in computer science from Curtin University in Jan 2012. He completed his PhD in a period of 2.5 years receiving the Chancellor's Commendation for excellence for his exceptional doctoral work in Machine Learning and AI. Prior to his PhD, he completed a Master of Engineering degree in Signal Processing from Indian Institute of Science, Bangalore. Since completing his PhD, Dr. Gupta has been at Deakin University. He currently works as a Professor and the Head of AI Optimisation and Materials Discovery at the Applied Artificial Intelligence Institute (A2I2). His research interests lie in broad areas of machine learning and artificial intelligence.
Title: AI for Optimal Experimental Design and Decision-Making under Uncertainty.
Australian National University
Hanna Kurniawati is a Professor at the ANU School of Computing and holds the SmartSat CRC Chair for System Autonomy, Intelligence & Decision-Making. Hanna’s research spans robotics, planning under uncertainty, motion planning, computational geometry applications, integrated planning and learning, and reinforcement learning. She aims to endow robots with the ability to work with and leverage uncertainty, rather than avoiding them. To this end, together with students and collaborators, she has developed computational methods that enable the Partially Observable Markov Decision Processes (POMDPs) to become practical for robotics. Her work has received multiple recognitions, including a best paper award at ICAPS 2015, a finalist for the best paper award at ICRA 2015, a keynote talk at IROS 2018, and the Robotics: Science and Systems 2021 Test of Time Award. Hanna is actively involved in the robotics community, including as a Program Co-Chair for ICRA 2022.
Title: Decision-making in the Partially Observable World.
University of Technology Sydney
Distinguished Professor Jie Lu is a world-renowned scientist in the field of computational intelligence, primarily known for her work in fuzzy transfer learning, concept drift, recommender systems, and decision support systems. She is an IEEE Fellow, IFSA Fellow, and Australian Laureate Fellow. Currently, Prof Lu is the Director of the Australian Artificial Intelligence Institute (AAII) at University of Technology Sydney (UTS), Australia. She has published over 500 papers in leading journals and conferences; won 10 Australian Research Council (ARC) Discovery Projects as first chief investigator, and over 20 industry projects; and supervised 50 doctoral students to completion. Prof Lu serves as Editor-In-Chief for Knowledge-Based Systems and International Journal of Computational Intelligence Systems. She is a recognized keynote speaker, delivering over 40 keynote speeches at international conferences. She is the recipient of two IEEE Transactions on Fuzzy Systems Outstanding Paper Awards (2019 and 2022), NeurIPS2022 Outstanding Paper Award, Australia’s Most Innovative Engineer Award (2019), Australasian Artificial Intelligence Distinguished Research Contribution Award (2022), and the Officer of the Order of Australia (AO) in Australia Day 2023.
Title: Autonomous Machine Learning for Decision Support in Complex Environments.
University of Adelaide
Professor Javen Qinfeng Shi is the Founding Director of Causal AI Group (previously known as Probabilistic Graphical Model Group) at the University of Adelaide, and Director in Advanced Reasoning and Learning of Australian Institute for Machine Learning (AIML). He is a leader in machine learning in both high-end AI research and also real world applications with impacts. His main research interests include Causality, Reinforcement Learning, Metaphysics and ways to help and heal the world. He has published over 100 peer reviewed papers, over 80% are at ERA [A/A*]. He has over 9500 Google Scholar citations with h-index 43. Google Scholar ranks him 7th globally in Probabilistic Graphical Models. He has transferred his research to diverse industries including agriculture, mining, sport, manufacturing, bushfire, water utility, health and education. Recent awards include 1) 2nd place from a global mining competition OZ Minerals Explorer Challenge 2019 (over 1000 participants from 62 countries), 2) Golden prize (1st place) from Volkswagen in 2019 (digital factory powered by AI), 3) Finalist of SA Department of Energy and Mining’s Gawler Challenge 2020 (over 2k participants from 100+ countries) with his team’s work being considered as “The most innovative modelling” by the judge panel, 4) the top winning team (in collaboration with USC and CSIRO) in AUS/NZ Bushfire Data Quest 2020 using AI to predict fire scar and spread that led to their winning Citizen Science Grant in 2021 and subsequent NOBURN app release in August 2023 receiving extensive media coverage: Daily Mail, Yahoo News Australia&NZ, West Australian, Channel 7, Triple M, Hit FM, Canberra Times, Perth Now, Bendigo Advertiser, Newcastle Herald, The Examiner, Illawarra Mercury (+71 more).
Title: Causality - The Way of Change.
University of New South Wales
Toby Walsh is an ARC Laureate Fellow and Scientia Professor of AI at UNSW and CSIRO Data61. He is Chief Scientist of UNSW.AI, UNSW's new AI Institute. He is a strong advocate for limits to ensure AI is used to improve our lives, having spoken at the UN, and to heads of state, parliamentary bodies, company boards and many others on this topic. This advocacy has led to him being "banned indefinitely" from Russia. He is a Fellow of the Australia Academy of Science, and was named on the international "Who's Who in AI" list of influencers. He has written four books on AI for a general audience, the most recent is "Faking It! Artificial Intelligence in a Human World".
Title: Faking It! Artificial Intelligence in a Human World.
Professor Geoff Webb is an eminent and highly-cited data scientist. He was editor in chief of the Data Mining and Knowledge Discovery journal, from 2005 to 2014. He has been Program Committee Chair of both ACM SIGKDD and IEEE ICDM, as well as General Chair of ICDM and member of the ACM SIGKDD Executive. He is a Technical Advisor to machine learning as a service startup BigML Inc and to recommender systems startup FROOMLE. He developed many of the key mechanisms of support-confidence association discovery in the 1980s. His OPUS search algorithm remains the state-of-the-art in rule search. He pioneered multiple research areas as diverse as black-box user modelling, interactive data analytics and statistically-sound pattern discovery. He has developed many useful machine learning algorithms that are widely deployed. His many awards include IEEE Fellow, the inaugural Eureka Prize for Excellence in Data Science (2017) and the Pacific-Asia Conference on Knowledge Discovery and Data Mining Distinguished Research Contributions Award (2022).
Title: Data Science for Time Series
Program and topics
Run across four days, ISAAC will involve a registration period, a welcome event, a number of events organised by the Faculty of Information Technology (FIT events), and a variety of teaching sessions ranging from introductory, intermediate and advanced, that fall within three main tracks: Foundations, Logic, and Automated Reasoning; Machine Learning and Data Science; AI for Systems' Quality and Design.
|10.00 - 11.00||Webb||Webb||Webb|
|11.00 - 11.30||Break||Break||Break|
|11.30 - 12.30||Registration||Gupta||Gupta||Gupta|
|12.30 - 13.30||Lunch||Lunch||Lunch||Lunch|
|13.30 - 14.30||Opening||Shi||Kurniawati||Lu|
|14.30 - 15.00||Break||Break||Break||Break|
|15.00 - 16.00||Walsh||Shi||Kurniawati||Lu|
|16.00 - 16.15||Break||Break||Break||Break|
|16.15 - 17.00||FIT event||Shi||Kurniawati||Lu|
ISAAC is proudly sponsored by the Monash Faculty of Information Technology, the Department of Data Science and Artificial Intelligence, and the Monash Data Futures Institute.
ISAAC is organised by the Monash Faculty of Information Technology: