Novi Quadrianto

Adjunct Professor, Data Science

E: novi.quadrianto@monash.edu n.quadrianto@sussex.ac.uk

Novi Quadrianto is a machine learning scientist and an Adjunct Professor (Data Science) at Monash University Indonesia. He is also a Professor of Machine Learning at the University of Sussex, UK, leads a BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning in Spain, and is a scholar at the ELLIS Human-centric Machine Learning programme.

Novi received his Ph.D. in Machine Learning from the Australian National University, Canberra, Australia in 2012. From 2012-2014, Novi was a Newton International Fellow of the Royal Society and the British Academy at the Machine Learning Group in the Department of Engineering, University of Cambridge. He joined the University of Sussex in 2014. In 2019, Novi was awarded a €1.5 million grant by the European Research Council ERC for a 5-year project on developing Bayesian machine learning models and algorithms for fairness and transparency (BayesianGDPR).

Novi is offering an office hour to organisations who have questions on scientific and algorithmic aspects of machine learning but do not have in-house expertise. There will be no fee associated with office hours. He speaks English and Indonesian. Please feel free to contact him.

Novi Quadrianto Monash University Indonesia

More information

Check Novi Quadrianto's Google Scholar in this link.

Selected publications:

  • Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto. Okapi: Generalising Better by Making Statistical Matches Match. Neural Information Processing Systems NeurIPS, New Orleans, Louisiana, US, 2022.
  • Gergely Dániel Németh, Miguel Ángel Lozano, Novi Quadrianto, Nuria Oliver. A Snapshot of the Frontiers of Client Selection in Federated Learning. Transactions on Machine Learning Research TMLR, ISSN, 2022.
  • Bradley Butcher, Vincent Huang, Christopher Robinson, Jeremy Reffin, Sema Sgaier, Grace Charles, Novi Quadrianto. Causal datasheet for datasets - An evaluation guide for real-world data analysis and data collection design using Bayesian Networks. Frontiers in Artificial Intelligence, p. 18. ISSN 2624-8212, 2021.
  • Jonathan Dolley, Fiona Marshall, Bradley Butcher, Jeremy Reffin, James Alexander Robinson, Baris and Novi Quadrianto. Analysing trade-offs and synergies between SDGs for urban development, food security and poverty alleviation in rapidly changing peri-urban areas: a tool to support inclusive urban planning. Sustainability Science, ISSN 1862-4065, 2020.
  • Novi Quadrianto, Viktoriia Sharmanska and Oliver Thomas. Discovering Fair Representations in the Data Domain. IEEE Conference on Computer Vision and Pattern Recognition CVPR, Long Beach, California, 2019.
  • Novi Quadrianto and Viktoriia Sharmanska. Recycling Privileged Learning and Distribution Matching for Fairness. Neural Information Processing Systems NeurIPS, Long Beach, California, USA, 2017.

Research Interests

His research lies in the area of machine learning, with an emphasis in:

  1. ethical and trustworthy machine learning (auditing/mitigating inappropriate bias against protected subgroups, and improving interpretability of algorithmic systems);
  2. safe and robust machine learning (ensuring reliably good performance even when encountering extreme situations); and
  3. interactive machine learning (facilitating an understanding between a user and an algorithmic system).

Novi and his research group have also performed inter and transdisciplinary collaborations and have developed, among others:

  1. a causality toolbox and applied it to design evidence based, effective, and acceptable interventions in post-natal care; and
  2. an AI landscape modelling tool and used it to analyze the trade-offs between development, food security, and poverty and trade-offs in peri-urban agriculture systems, and so informed urban sustainability policy.

For more information, please check https://wearepal.ai/

Teaching

Novi has been a guest lecturer in summer schools in Ukraine and Germany on topics such as algorithmic fairness and bias, and causal machine learning.

In Aug-Sep 2022, Novi was teaching Statistical Data Modelling (ITI5197) for the Term 4 (6 weeks) of Monash University, Indonesia.

In Jan 2023, Novi was teaching part (on fairness in machine learning) of Ethics, Privacy, AI in Society (70052-97125) at Imperial College London.

At Sussex, his previous teaching responsibilities include Machine Learning (undergraduate and postgraduate) and Computer Vision (undergraduate).

Selected distinctions

  • 2023 Guarantor Researcher for BCAM Severo Ochoa Excellence Accreditation
  • 2020 European Lab for Learning and Intelligent Systems (ELLIS) Scholar
  • 2019 European Research Council ERC Starting Grant
  • 2012 Newton International Fellowship
  • 2009 Microsoft Research Asia Fellowship

Journal editor and conference organising committee

  • Action Editor, 2022 - present Transactions on Machine Learning Research (TMLR).
  • Associate Editor, 2018 - present Frontiers in Big Data Journal (Machine Learning and Artificial Intelligence Section).
  • Associate Editor, 2016 - present IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Journal. TPAMI's 2021 impact factor is 24.31.
  • Area Chair, Neural Information Processing Systems NeurIPS, International Conference on Machine Learning ICML, Association for the Advancement of Artificial Intelligence AAAI, International Conference on Artificial Intelligence and Statistics AISTATS, and International Conference on Learning Representations ICLR.