Machine Learning Seminars

The Machine Learning Seminar is a regular event that aims to promote machine learning research. It provides a forum to present recent advancements, share ideas and discuss new research directions in machine learning. In the seminars, we host international and New Zealand-based experts from industry and academia. They are open for anyone with an interest in theoretical and applied machine learning. The seminars are both hosted at the University of Auckland and virtually.

Machine Learning Seminar by Prof. Christian S. Jensen – New Vehicle Routing Paradigms Enabled by Big Vehicle Trajectory Data

Short Bio Christian S. Jensen is Professor of Computer Science at Aalborg University, Denmark. His research concerns primarily analytics, including machine learning, data mining, and query processing, and data management,...

Machine Learning Seminar by Dr. Xia Ning – Deep Generative Models for Molecule Optimization

Short Bio Dr. Xia Ning is an Associate Professor in the Biomedical Informatics Department, and the Computer Science and Engineering Department, The Ohio State University. She received her Ph.D. in Computer Science and...

Machine Learning Seminar by Alex Gavryushkin – Online Algorithms for Evolutionary and Systems Biology

Short Bio Alex Gavryushkin is an associate professor and Rutherford Discovery Fellow at the University of Canterbury, where he leads the Biological Data Science lab, which he founded in 2017. The lab is primarily interested...

Machine Learning Seminar by Pat Langley – Computational Scientific Discovery: Heuristic Search for Communicable Laws and Models

Short Bio Dr. Pat Langley serves as Director of the Institute for the Study of Learning and Expertise and as a Research Scientist at Stanford University's Center for Design Research. He has contributed to AI and cognitive...

Machine Learning Seminar by Zachary Lipton – RATT: Leveraging Unlabeled Data to Guarantee Generalization

Short Bio Zachary Chase Lipton is the BP Junior Chair Assistant Professor of Operations Research and Machine Learning at Carnegie Mellon University and a Visiting Scientist at Amazon AI. He directs the Approximately Correct...

Machine Learning Seminar by Harris Lin – Beyond accuracy: what should you ask from a predictive model?

Short Bio Harris Lin is a data scientist from Plant and Food Research, whose team has expertise in computer vision technologies, signal processing from smart sensors, natural language processing, data-driven consumer...

Machine Learning Seminar by Mengjie Zhang – Evolutionary Machine Learning: Research, Applications and Challenges

Short Bio Mengjie Zhang is a Fellow of Royal Society of New Zealand, a Fellow of IEEE, an IEEE Distinguished Lecturer, currently Professor of Computer Science at Victoria University of Wellington, where he heads the...

Machine Learning Seminar by Dr. Alexandre Benoit – Analyzing gamma-ray astronomy data with deep learning and first steps towards explainability

Short Bio Alexandre received PhD degree in electronics and computer science from the University of Grenoble, INP in 2007 (France). Starting 2008, he has been an associate professor at Université Savoie Mont Blanc at LISTIC lab....

Machine Learning Seminar by Jan N. van Rijn – Automating the Data Science Pipeline: AutoML, Meta-learning and OpenML

RSVP If you want to join us for this seminar, please leave your name and email below and indicate if you plan to join on campus or via Zoom.