Statements (96)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Person
|
| gptkbp:bfsLayer |
3
|
| gptkbp:bfsParent |
gptkb:Robert_Oppenheimer
gptkb:Arthur_H._Compton gptkb:Breakthrough_Prize_in_Fundamental_Physics |
| gptkbp:alma_mater |
gptkb:University_of_Cambridge
gptkb:University_of_Oxford |
| gptkbp:awards |
gptkb:IEEE_Fellow
Royal Society Fellow |
| gptkbp:birth_date |
1967-12-24
1967-12-12 |
| gptkbp:children |
2
not publicly disclosed |
| gptkbp:contribution |
developed algorithms for data compression
explored the impact of technology on society engaged in public outreach for science contributed to the understanding of human-computer interaction explored applications of machine learning in various fields explored the role of AI in climate change solutions advocated for the importance of data-driven decision making explored the relationship between information theory and machine learning advocated for ethical considerations in AI advocated for responsible AI development advocated for the use of Bayesian inference advocated for transparency in AI systems analyzed the challenges of AI regulation analyzed the efficiency of algorithms analyzed the impact of AI on employment analyzed the role of data in modern research analyzed the challenges of implementing AI in practice contributed to discussions on AI governance developed frameworks for evaluating AI systems developed techniques for model selection engaged in collaborative research projects explored the foundations of neural networks explored the future of human-AI collaboration explored the future of machine learning explored the implications of entropy in learning explored the role of AI in creative industries explored the role of AI in education explored the role of AI in social good. explored the societal impacts of machine learning promoted interdisciplinary approaches in research promoted open-source software in research published a textbook on machine learning published extensively in academic journals published papers on the philosophy of science served as a mentor to many students studied the ethical implications of data privacy studied the implications of AI in finance studied the implications of AI in public policy studied the implications of big data studied the intersection of AI and ethics studied the role of uncertainty in decision making taught at the University of Cambridge studied the implications of AI in national security contributed to the understanding of causal inference contributed to the field of computational neuroscience developed educational resources for machine learning contributed to the understanding of overfitting in models analyzed the implications of Bayesian methods in AI analyzed the potential of AI in scientific discovery studied the implications of machine learning in healthcare contributed to the development of open-source tools contributed to the understanding of algorithmic bias |
| gptkbp:death_date |
2016-04-15
|
| gptkbp:field |
gptkb:Artificial_Intelligence
gptkb:computer_science gptkb:software_framework statistics information theory statistical physics |
| https://www.w3.org/2000/01/rdf-schema#label |
David J. C. Mac Kay
|
| gptkbp:influenced |
many researchers in machine learning
|
| gptkbp:influenced_by |
gptkb:Thomas_Bayes
gptkb:Richard_Feynman gptkb:David_H._Wolpert |
| gptkbp:known_for |
gptkb:software_framework
information theory Bayesian methods sparse coding Bayesian methods in machine learning the book ' Information Theory, Inference, and Learning Algorithms' |
| gptkbp:nationality |
gptkb:British
|
| gptkbp:notable_work |
gptkb:Information_Theory,_Inference,_and_Learning_Algorithms
|
| gptkbp:occupation |
gptkb:physicist
gptkb:Author |
| gptkbp:research_focus |
probabilistic models
|
| gptkbp:research_interest |
gptkb:microprocessor
gptkb:physicist gptkb:quantum_computing data compression |
| gptkbp:residence |
gptkb:Cambridge,_England
|
| gptkbp:spouse |
not publicly disclosed
Catherine Mac Kay |
| gptkbp:website |
http://www.inference.phy.cam.ac.uk/mackay/
|