Journey across continents for machine learning specialist

29 September 2021
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Fairness and transparency is important in many fields.  Novi Quadrianto explores how to achieve it in machine learning. Originally from Indonesia, this well-travelled researcher has moved between Singapore, Australia, Austria and the UK (and more!) during his career.  

© Novi Quadrianto

Novi Quadrianto is currently a Reader in Machine Learning at the University of Sussex, UK. Prior to Sussex, 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. Novi received his Ph.D. in Computer Science from the Australian National University, Canberra, Australia in July 2012. In 2019, Novi was awarded an ERC Starting Grant for a project on developing Bayesian models and algorithms for fairness and transparency (BayesianGDPR). Since March 2021, Novi also leads a BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning in Spain.

During the course of your academic and research career, you moved between many countries. What was motivated you to travel?

My main drive is to meet interesting people and learn from the best researchers worldwide. I was born in Indonesia and moved to Singapore to obtain my first degree. My journey in Machine Learning research started in Australia. While there, I came to understand the importance of building both academic and industry networks. That is what led me to visit universities and companies in five different countries during my PhD studies. Austria was one of these countries and I was happy to learn about European Research Council grants while there.

What are the challenges and opportunities to working in an international environment?

Members of my Predictive Analytics Lab PAL research team at the University of Sussex, UK, come from at least eight different countries. Time zone difference is a challenge. At this pandemic time, some of our team members are working remotely from their home country, and one is currently in Malaysia! Most importantly, diversity, multi-culturalism and multiple nationalities in the team provide an opportunity for out-of-the-box thinking and solutions. This is particularly important to us as we aim to address research questions to do with algorithmic fairness and bias.

Could you briefly describe your research?

I am a Machine Learning researcher and work on building prediction models based on historical data. Machine Learning systems are increasingly being used to inform, support and even make decisions within consequential domains - potentially affecting millions of lives, for example, in the allocation of healthcare, education and credit. It is therefore necessary to consider how notions of fair processes and outcomes translate into algorithmic decision support frameworks. It is also important so we can challenge and understand algorithmic decisions. My ERC research project BayesianGDPR aims to understand the interdependence between algorithmic fairness and transparency in order to build robust, reliable and trustworthy Machine Learning systems.  

To what extent does your ERC grant help your research plans?

With ERC funding, I can strengthen research collaborations with other Machine Learning groups in top European institutions. My lab in the UK is turning into a borderless research lab as I co-supervise several PhD students from Spain and Germany under the European Lab for Learning and Intelligent Systems ELLIS and BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning programmes. With long-term support and a generous budget granted by the ERC to perform ground-breaking research, I also aim to improve diversity and inclusion in the Machine Learning field. We have been offering research opportunities, including studentships and internships, to underrepresented groups in the Machine Learning community. We are happy to report a recent success as a result of this initiative - one alumna has just won a 3-year Early Career Fellowship to conduct her own independent research in Machine Learning. 

From Indonesia, you initially studied in Singapore. Do you maintain research ties and would you encourage researchers from the region to apply for an ERC grant?

I do not currently collaborate with research groups in the South East Asia region but I am working on it! I am having active discussions with a new research-intensive University in Indonesia. I sincerely hope this can be a catalyst for creating research ties with Indonesia, Singapore and other countries in the region. I would highly encourage researchers from the South East Asia region to apply for an ERC grant. It is worth the effort!

What advice would you give to researchers who are considering applying for ERC grants?

First, you need to understand what ERC grants are about before applying. Early planning is essential to help you build your research portfolios and the profiles needed to meet the scientific excellence criterion of the ERC. My advice would also be to watch the series of instructional videos called 'ERC Classes'. The videos explain in an entertaining and practical way all you need to know about the application and evaluation process of ERC grants. I wish I had had access to these videos or seen them when I was applying back in 2018!

In addition, more recently the ERC and the Euraxess Worldwide Network have organised a series of webinars to introduce ERC grants to researchers in different parts of the world. These webinars are a great opportunity to ask questions to grantees and Scientific Officers working at the ERCEA. And a really great way to learn about the different ERC funding schemes!

If you would like to ask Novi Quadrianto about his career path, or learn more about ERC funding opportunities for researchers in Singapore, Japan, or Korea, you can watch a dedicated webinar  that took place on 1 October 2021. This information session is organised in conjunction with EURAXESS ASEAN, an EU backed initiative supporting researchers working outside of Europe who wish to connect with Europe.