Neil Lawrence
Neil Lawrence | |
|---|---|
| Born | Neil David Lawrence |
| Nationality | British |
| Alma mater |
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| Scientific career | |
| Fields | Machine learning Gaussian processes[1] |
| Institutions | |
| Thesis | Variational Inference in Probabilistic Models (2000) |
| Doctoral advisor | Christopher Bishop |
| Website | inverseprobability |
Neil David Lawrence is the DeepMind Professor of Machine Learning at the University of Cambridge in the Department of Computer Science and Technology,[2] senior AI fellow at the Alan Turing Institute and visiting Professor at the University of Sheffield.[3]
Education
Lawrence obtained a Bachelors in Engineering degree in mechanical engineering at the University of Southampton, and a PhD from the University of Cambridge, with a thesis on variational inference in probabilistic models, supervised by Christopher Bishop.[4]
Career and research
Lawrence spent a year at Microsoft Research before serving as a senior lecturer in machine learning and computational biology at the University of Sheffield for six years. From 2007 to 2010, Lawrence was research fellow at the University of Manchester's Department of Computer Science, returning to the University of Sheffield in 2010 as the collaborative chair of neuro and computer science.[5]
In 2016, he was appointed director of machine learning at Amazon in Cambridge, where worked he collaborated with Ralf Herbrich, who is director of machine learning at Amazon in Berlin.[6]
Upon his appointment as the inaugural DeepMind Professor Machine Learning at the University of Cambridge in September 2019, Ann Copestake stated Lawrence' addition would have a "transformative effect".[7]
Lawrence' research interests are in machine learning, gaussian processes,[1] and probabilistic models with applications in computational biology, personalised health and developing economies.[2]
Ambassadorship
Lawrence has advocated for data transparency and privacy, writing several prominent articles in The Guardian discussing issues ranging from the privacy implications of Machine Learning algorithms deployed on citizens,[8][9][10][11][12][excessive citations] the current "state of the art" in the field,[13] the importance of data-sharing[14][15] and academic transparency,[16] to the possibilities for Machine Learning to advance developing nations such as African nations.[17] These efforts have been called "commendable" by Demis Hassabis.[18]
More recently he has been solicited for his opinion on the absence of Machine Learning algorithms during the COVID-19 pandemic, to which he stated
"This is showing what bulls—t most AI hype is. It’s great and it will be useful one day but it’s not surprising in a pandemic that we fall back on tried and tested techniques."[19]
Lawrence hosts a podcast with Katherine Gorman called Talking Machines.[20]
References
- ^ a b Neil Lawrence publications indexed by Google Scholar
- ^ a b "Cambridge appoints first DeepMind Professor of Machine Learning". University of Cambridge. 18 September 2019.
- ^ Neil Lawrence publications indexed by the Scopus bibliographic database. (subscription required)
- ^ Lawrence, Neil David (2000). Variational Inference in Probabilistic Models (PDF) (PhD thesis). University of Cambridge. OCLC 894596569. EThOS uk.bl.ethos.621104.
- ^ "Prof. Neil Lawrence". University of Sheffield. 15 August 2022.
- ^ "Amazon beefs up machine learning presence in UK with new team of researchers". GeekWire. 2 September 2016.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Amazon ML ace spearheads historic DeepMind Cambridge venture". Business Weekly. 18 September 2019.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Beware the rise of the Digital Oligarchy". The Guardian. 5 March 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Let's learn the rules of the digital road before talking about a web Magna Carta". The Guardian. 2 April 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "How to prevent creeping artificial intelligence from becoming creepy". The Guardian. 12 June 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "The data-driven economy will help marketers exploit us". The Guardian. 23 July 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^
"The information barons threaten our privacy and our autonomy". The Guardian. 16 November 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Google AI versus the GO Grandmaster--who is the real winner?". The Guardian. 28 January 2016.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Google's NHS deal does not bode well for the future of data-sharing". The Guardian. 5 May 2016.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Data trusts could allay our privacy fears". The Guardian. 3 June 2016.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Why thousands of AI researchers are boycotting the new Nature journal". The Guardian. 29 May 2018.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "How Africa can benefit from the Data Revolution". The Guardian. 25 August 2015.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "Amazon ML Chief departs to take up DeepMind professorship at Cambridge". New Statesman. 19 September 2019.
{{cite news}}: Cite uses deprecated parameter|authors=(help) - ^ "A.I. can't solve this: The coronavirus could be highlighting just how overhyped the industry is". CNBC. 29 April 2020.
{{cite web}}: Cite uses deprecated parameter|authors=(help) - ^ "About Talking Machines".
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