Andreas Bedorf
We are now accepting applications for fully-funded PhD studentships (2023 start). Find out more here.
The van der Schaar Lab will add 5 new PhD students to its team of researchers this month, capping a year of highly impactful projects and unprecedented recognition at the major conferences in machine learning.
Heading into the 2022/2023 academic year, Alan Jeffares, Nicholas Huyn, Paulius Rauba, Tennison Liu, and Yangming Li will join the Cambridge-based lab. Each of them will bring a new perspective, fresh ideas, and an exceptional academic record to the lab’s ongoing development of world-leading techniques in the field of machine learning for healthcare. The lab’s 5 new researchers are introduced below.
Alan Jeffares
Alan Jeffares graduated from University College Dublin with a BSc in Statistics and from University College London with an MSc in Machine Learning. He also spent two years in industry working in applied machine learning.
During his time in industry, Alan helped develop technologies that enabled same-day postal delivery for some of the world’s biggest postal services. He and his team presented their work at the World AI Summit in Amsterdam and the Conference of Applied Statisticians Ireland (CASI).
Alan decided to pursue a career in research upon completing his master’s thesis at UCL, which he found to be a rewarding experience. His work during this thesis also resulted in a paper which was published as a spotlight at ICLR 2022.
As a Ph.D. student with the van der Schaar Lab, Alan is delighted to have the opportunity to conduct machine learning research that can contribute towards better healthcare outcomes. As he explains, “I am particularly excited by having the academic freedom to dive into new and exciting areas of machine learning research and further develop these methods towards healthcare applications.”
Nicholas Huyn
Nicholas joins us freshly graduated with a Diplôme d’Ingénieur from Ecole Polytechnique (France) and an MSc in Machine Learning from Ecole Normale Supérieure Paris-Saclay.
During his studies, Nicholas focused on a wide array of ML topics, such as cost-aware Bayesian optimisation, reward learning, and combining natural language processing with graphs.
Equipped with experience in a broad range of topics and a cemented passion for his field of research, Nicholas is excited to join the van der Schaar lab. In his words, “the exceptional combination of brilliant minds making up the lab, the immense impact of the lab’s research, and its expositions” make the lab the ideal place to pursue a meaningful PhD.
For his PhD, Nicholas aspires to work on various topics such as representation learning, causality, and data-centric ML to further translate their huge potential into the challenging domain of healthcare.
When he is not working on his research, he enjoys watching and playing football with friends, be it on the pitch or with a controller in his hands.
Nicholas’ research is supported by funding from Illumina.
Paulius Rauba
Paulius’ path to the van der Schaar Lab is a particularly interesting one.
Although he only recently graduated as Shirley Scholar with an MSc in Social Data Science from Oxford University, he comes with years of work experience at the intersection of academia, business, and international organisations.
Paulius has previously worked very practically as an AI expert for the European Commission and the National Education Agency in Lithuania, evaluating proposals on the implementation of AI and advising on how to best build robust AI systems.
However, he also gathered experience in teaching as visiting lecturer at ISM University, instructing on econometrics and statistical learning, and as a lecturer at private coding academies introducing newcomers to Python for data science and statistics.
While working as a data scientist in a large corporate bank, Paulius acquired further know-how by building end-to-end data science and machine learning pipelines, implementing causal inference models, and developing propensity models. Before that, he worked as a data analyst in a company offering big data predictive analytics solutions and as an analyst in a management consulting firm.
Paulius joins us for his Ph.D. hoping to contribute his statistical and deep learning knowledge and to help build a new generation of causal deep learning tools to transparently and quantifiably solve practical problems faced by clinicians.
During his free time, you might find Paulius scuba diving with manta rays, snowboarding, kitesurfing, jogging, playing tennis, or (occasionally) running from orangutans in the jungle.
Paulius’ research is supported by funding from AstraZeneca.
Tennison Liu
Tennison is a Ph.D. student in the Cambridge Centre for AI in Medicine as well as the van der Schaar Lab.
Tennison graduated from the University of Sydney with a B.Eng in Electrical Engineering, receiving the University Medal (highest mark), and then continued to an M.Phil. in Machine Learning and Machine Intelligence at the University of Cambridge, where he first worked with Prof. van der Schaar and was awarded the John CB Chau Prize for highest M.Phil. mark.
Tennison has held research data scientist roles at Cochlear, IBM, and Macquarie Group in Australia, but felt drawn to the intellectual stimulation of machine learning research. In his own words, he opted to join the lab for its “great resources that are rarely found in other institutions, in terms of research collaborations, faculty, and brilliant students.”
Tennison currently expects his work with the van der Schaar lab and the Cambridge Centre for AI in Medicine to focus on areas such as synthetic data, discovery using machine learning, and deep self-supervision.
In his spare time, Tennison enjoys rowing with the St Edmund’s College Boat Club, playing basketball, and working out in the gym. He also enjoys photography and (in the right mood) will play the piano and trumpet.
Tennison’s research is supported by funding from AstraZeneca.
Yangming Li
Yangming comes to us with the practical experience he gathered working as a researcher at Tencent AI Lab, focusing on natural language processing (NLP). During his time in the industry, he participated in developing a spoken dialogue system for the Alibaba Group supporting oral and real-time negotiations with human debtors. Other projects included abstracting engineering challenges into research problems and working on solving them.
Yangming left Tencent with a number of publications at impactful conferences like ACL and ICLR under his belt.
Previously, he graduated with a bachelor’s degree in computer science from Harbin Institute of Technology.
Now, Yangming is joining the van der Schaar lab with a great interest in our vision for ML for healthcare. His future research will focus on time-series modelling, representation learning, and neural differential equations.
I’m thrilled to be welcoming 5 extraordinarily talented PhD students to our lab this year. They will be working on a wide range of new and exciting topics at the cutting edge of machine learning, with the aim of transforming healthcare.
– Mihaela van der Schaar
To find out more about the van der Schaar Lab’s research team, click here. Our publications are available here.
To inquire about PhD studentships, visit this page.
Nabeel Seedat
Mihaela van der Schaar
Jeroen Berrevoets
