We are delighted to announce that Dr Carl Henrik Ek,
Dr Ferenc Huszár and Dr Nicholas Lane are joining the Department of Computer Science and Technology

The Department of Computer Science and Technology is further expanding research in machine learning with the appointment of three new faculty members. Last year Professor Neil Lawrence was appointed as the inaugural Deepmind Professor of Machine Learning, and we are delighted to announce that three further academics will join the Department this year, bringing a wealth of experience in research, teaching and industry engagement.

Dr Carl Henrik Ek, PhD, Oxford Brookes, 2009
Dr Ek is currently Senior Lecturer in the Faculty of Engineering at the University of Bristol. His research is in core machine learning - he has exceptional teaching experience and a strong engagement with industry.

Dr Ferenc Huszár, PhD, University of Cambridge, 2012
Since completing his PhD, Dr Huszár has worked in industry and is currently a Senior Machine Learning Researcher at Twitter.  Dr Huszár has an outstanding academic record and is a highly creative researcher with broad interests in many areas of machine learning. He is known for his popular machine learning research blog https://www.inference.vc/.

Dr Nicholas Lane, PhD, Dartmouth College, 2011
Dr Nicholas Lane is currently an Associate Professor in the Computer Science Department, University of Oxford and Fellow of Kellogg College.  Dr Lane's research interests are in efficient and scalable machine learning systems - with a focus on machine learning for embedded systems.  He will be especially important in bridging machine learning with other areas of the Department.  In 2019, he was awarded an ERC Starting Grant and an ACM SIGMOBILE Test-of-Time Award.  He is also the 2020 recipient of the ACM SIGMOBILE Rockstar Award.

Dr Carl Henrik Ek

Dr Carl Henrik Ek

Dr Ferenc Huszár

Dr Ferenc Huszár

Dr Nicholas Lane

Dr Nicholas Lane

We are delighted to announce that Dr Carl Henrik Ek, Dr Ferenc Huszár and Dr Nicholas Lane are joining the Department of Computer Science and Technology