AI News, Ruslan Salakhutdinov

Ruslan Salakhutdinov

He received his PhD in computer science from the University of Toronto in 2009.

Ruslan’s primary interests lie in deep learning, machine learning, and large-scale optimization.

He is an action editor of the Journal of Machine Learning Research and served on the senior programmer committee of several top-tier learning conferences including NIPS and ICML.

The explosion of interest in KDD and other Data Science/Machine Learning/AI conferences is just one of the many signs that these technologies are no longer confined to the realms of academia and a handfull of tech companies.

As our daily lives seamlessly integrate more and more data-driven applications, people’s excitement is tempered by worry about the technologies’ potential to disrupt their existence.

Having worked for almost 30 years to design and develop these technologies, the KDD community now should examine and debate the impact of Machine Learning &

Can we unleash the incredible responsiveness of the KDD community toward longer-term more impactful projects across sectors that are essential for social good, such as Health, Environmental Sustainability, and Public Welfare.

Professor Provost studies data mining, machine learning, social network analysis and their alignment with business problems.

He has won several awards, including the 2009 INFORMS Design Science award for social network-based marketing, IBM Faculty Awards for outstanding research in data mining and machine learning, a President’s Award from NYNEX Science and Technology, Best Paper Awards from the ACM SIGKDD conference, and awards in SIGKDD’s annual KDDCUP data mining competition.

He advises businesses and U.S. government agencies on policy and investments in data mining research, and on practical issues in applying data mining and machine learning.

Professor Provost studies data mining, machine learning, social network analysis and their alignment with business problems.

He has won several awards, including the 2009 INFORMS Design Science award for social network-based marketing, IBM Faculty Awards for outstanding research in data mining and machine learning, a President’s Award from NYNEX Science and Technology, Best Paper Awards from the ACM SIGKDD conference, and awards in SIGKDD’s annual KDDCUP data mining competition.

He advises businesses and U.S. government agencies on policy and investments in data mining research, and on practical issues in applying data mining and machine learning.

He created several high profile events for the AI, data science, non-profit, and policy communities such as the KDD Data Mining for Social Good Conference in August of 2014.

Jeannette’s seminal essay, titled “Computational Thinking,” was published more than a decade ago and is credited with helping to establish the centrality of computer science to problem-solving in fields where previously it had not been embraced.

Her work, which includes more than 100 peer-reviewed publications with over 5000 citations, focuses on developing data mining and machine learning techniques for complex relational and network domains, including social, information, and physical networks.

Machine Learning | Carnegie Mellon University

Fellowship Carl Doersch, 2014 IBM FellowshipChun-Liang Li, 2018Mrinmaya Sachan, 2016Kumar Avinava Dubey, 2014 Xi Chen, 2011-2012 Yi Zhang, 2009-2011 Microsoft FellowshipEdith Law, 2009-2012 NDSEG Fellowship Benjamin Cowley, 2013-2016 Calvin Murdock, 2013-2016 William Bishop, 2012-2015 Carl Doersch, 2011-2014 Michael Spece Ibanez, 2011-2014 NSERC Fellowship Alona Fyshe, 2010-2012 Jing Xiang, 2011-2013 NSF FellowshipLisa Lee, 2018William Herlands, 2014-2017 Micol Marchetti-Bowick, 2013-2016 Nicole Rafidi, 2013-2016 Ankur Parikh, 2011-2014 George Montanez, 2012, 2014-2016 Robert Fisher, 2010-2012, 2013-2014 Benjamin Cowley, 2012-2013 Joseph Gonzalez, 2010-2013 Joseph Bradley, 2008-2010 Presidential Fellows in the Life Sciences Award Suyash Shringarpure, 2008 Richard King Mellon Foundation Presidential FellowshipNicole Rafidi, 2016-2017Emmanouil Antonios Platanios, 2016-2017Kirthevasan Kandasamy, 2015-2016 Rothberg Research Award in Human Brain Imaging Alona Fyshe, 2011 Leila Wehbe, 2011 Samsung Fellowship Wooyoung Lee, 2007-2011 Symantec Research Lab Fellowship Duen Horng (Polo) Chau, 2008-2010 Yahoo!

EECS at UC Berkeley

His research interests bridge the computational, statistical, cognitive and

biological sciences, and have focused in recent years on Bayesian nonparametric

analysis, probabilistic graphical models, spectral methods,

kernel machines and applications to problems in distributed computing systems,

natural language processing, signal processing and statistical genetics.

Sciences, a member of the National Academy of Engineering and a member

Leslie P. Kaelbling

In the spring of 2000, she and two-thirds of the editorial board of the Kluwer-owned journal Machine Learning resigned in protest to its pay-to-access archives with simultaneously limited financial compensation for authors.[10]

Kaelbling co-founded and served as the first editor-in-chief of the Journal of Machine Learning Research, a peer-reviewed open access journal on the same topics which allows researchers to publish articles for free and retain copyright with its archives freely available online.[11]

Kaelbling responded that this policy was reasonable and would have made the creation of an alternative journal unnecessary, but the editorial board members had made it clear they wanted such a policy and it was only after the threat of resignations and the actual founding of JMLR that the publishing policy finally changed.[12]

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