One of the great scientific challenges of this century is to understand what intelligence is and how it can be recreated. My bit is, on one hand, the evaluation and measurement of intelligent systems in general and machine learning in particular and, on the other hand, some more applied research on data science, data mining and inductive programming. However, I'm interested in many other things, and my publication profiles below can give a better account of what my research really looks like:
Here you also have a selection of some recent tutorials and presentations:
- Surveying Safety-Relevant AI Characteristics, SafeAI2019 AAAI Workshop, Honolulu, 27 January 2019.
- AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI, AAAI / ACM Conference on Artificial Intelligence, Ethics and Society, Honolulu, 27-28 January 2019.
- Artificial Intelligence : Present, Future and Beyond, [video], HUMAINT Winter school on AI and its ethical, social, legal and economic impact, JRC Seville, February 4-8th, 2019.
- The What and How of AI Evaluation, [video], HUMAINT Winter school on AI and its ethical, social, legal and economic impact, JRC Seville, February 4-8th, 2019.
- Artificial Intelligence and Data Science : Looking Ahead, Springer Nature Conference on Artificial Intelligence in Biomedicine, Madrid 7th February 2019.
- Diversity Unites Intelligence: Measuring Generality at Varieties of Minds 2018 in Cambridge, 2018
- Measuring A(G)I Right: Some Theoretical and Practical Considerations at DeepMind, London, 2018
- Natural and Artificial Intelligence: Measures, Maps and Taxonomies at Clare Hall, Cambridge, 2018
- The Mythical Human-Level Machine Intelligence at Philosophy and Theory of AI in Leeds, 2017
- FHI, Oxford, Aug 2016, or the very similar CSER, Cambridge, Aug 2016, about the measurement of natural and artificial intelligence
- Machine learning performance evaluation: tips and pitfalls at PAPIs Connect, 2016
- AGI 2015 Tutorial: Evaluation of Intelligent Systems
- Invited Talk at ECML Workshop on Learning over Multiple Contexts 2014
- Machine intelligence evaluation: from the Turing Test to the present Day (and beyond), for a Turing centenary celebration
Apart from the recent one on the Evaluation of Natural and Artificial Intelligence
, I've published several other books
on various topics.
I am collaborating in several national strategies for AI, in the editorial board of the Machine Learning Journal, and have served as area chair or senior PC of IJCAI, ECAI, KDD, ECML, and PC member for many others, ICML, NeurIPS, AAAI, CogSci, AGI, ICDM, UAI, ICLR, etc.
We have had projects, collaborations and visits with several companies in different areas: health, retailing, software development, automotive, ...
Recently, I've been managing two "Cátedras/Aulas de Empresa":
José Hernández-Orallo is Professor at the Universitat Politecnica de Valencia. He received a B.Sc. and a M.Sc. in Computer Science from UPV, partly completed at the École Nationale Supérieure de l'Électronique et de ses Applications (France), and a Ph.D. in Logic with a doctoral extraordinary prize from the University of Valencia.
His academic and research activities have spanned several areas of artificial intelligence, machine learning, data science and information systems. He has published five books and more than a hundred journal articles and conference papers on these topics. His research in the area of machine intelligence evaluation has been covered by several popular outlets, such as The Economist, New Scientist or Nature. His most recent book addresses an integrated view of the evaluation of natural and artificial intelligence (Cambridge University Press, 2017, PROSE Award 2018).