I hail from Jakarta, Indonesia. I received my PhD in Machine Learning from the Australian National University (ANU), Canberra, Australia in 2012. I earned BEng degree in Electrical and Electronics Engineering at Nanyang Technological University (NTU), Singapore. During PhD studies, I have several overseas research exposures, among others, at HIIT-Finland, Yahoo! Research-US, University of Alberta-Canada, Fraunhofer IAIS-Germany, and IST Austria. From 2012-2014, I was a Newton International Fellow of the Royal Society at Department of Engineering of University of Cambridge, a Junior Member of the Isaac Newton Institute for Mathematical Sciences, and a Junior Fellow of the Wolfson College. I joined University of Sussex as a Lecturer in February 2014. Since May 2017 I am a Senior Lecturer. I am now a Reader (since May 2019).
Selected Distinctions 2020 European Lab for Learning and Intelligent Systems (ELLIS) Scholar/Fellow 2019 European Research Council ERC Starting Grant 2012 Newton International Fellowship 2009 Microsoft Research Asia Fellowship
Selected Roles Strategic Lab Leader, 2021 - present BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning, Spain Co-Director, 2017 - present Predictive Analytics Lab (WearePAL.ai), University of Sussex, UK Academic Mentor, 2017 - present School of Artificial Intelligence, Pi School, Italy Academic Supervisor, 2017 - 2019 Centre of Deep Learning and Bayesian Methods, HSE University, Russia Associate Editor, 2016 - present IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Journal, 2018 - present Frontiers in Big Data Journal (Machine Learning and Artificial Intelligence Section). TPAMI’s 2019 impact factor is 17.861 — the second-highest impact factor of all IEEE publications. Area Chair/Senior Area Chair, NIPS/NeurIPS 2021, 2020, 2019, 2018, 2017, 2015, ICML 2021, AAAI 2022, 2021, 2020, AISTATS 2022, 2021, 2020, ICLR 2022, 2021. The NeurIPS/NIPS and ICML conferences are the two most prestigious and competitive meetings in Machine Learning worldwide, publishing cutting-edge research on all aspects of machine learning and in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics.