Research output per year
Research output per year
Personal profile
Qualifications
2014, PhD, Purdue University, Electrical and Computer Engineering
Biography
Siddharth N. (Sid) is a Reader in Explainable AI in the School of Informatics at the University of Edinburgh. Prior to this, he was a Senior Researcher in Engineering at the University of Oxford and a Postdoctoral Scholar in Psychology at Stanford. He obtained his PhD from Purdue University in Electrical and Computer Engineering. His research broadly involves the confluence of machine learning, computer vision, natural-language processing, cognitive science, robotics, and elements of cognitive neuroscience, leading towards a central research goal to better understand perception and cognition with a view to enabling human-intelligible machine intelligence.
Explainable AI; Interpretable ML; Probabilistic Programming; Approximate Inference; Human-Machine Interaction; Neural-Symbolic Systems; Computer Vision; NLP
External positions
Safe and Ethical AI Research Fellow, The Alan Turing Institute
22 Nov 2019 → …
Fingerprint
Dive into the research topics where Siddharth N is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
Lessons from reinforcement learning for biological representations of space
Muryy, A., Siddharth, N., Nardelli, N., Glennerster, A. & Torr, P. H. S., 30 Sept 2020, In: Vision Research. 174, p. 79 - 93 15 p.Research output: Contribution to journal › Article › peer-review
-
Multitask Soft Option Learning
Igl, M., Gambardell, A., Nardelli, N., He, J., Siddharth, N., Böhmer, W. & Whiteson, S., 6 Aug 2020, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI). PMLR, p. 969-978 10 p. (Proceedings of Machine Learning Research; vol. 124).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access -
Simulation-Based Inference for Global Health Decisions
de Witt, C. S., Gram-Hansen, B., Nardelli, N., Gambardella, A., Zinkov, R., Dokania, P., Siddharth, N., Espinosa-Gonzalez, A. B., Darzi, A., Torr, P. & Gunes Baydin, A., 18 Jul 2020. 6 p.Research output: Contribution to conference › Paper › peer-review
-
Learning Generative Models from Classifier Uncertainties
Siddharth, N. & Paige, B., 17 Jul 2020. 9 p.Research output: Contribution to conference › Paper › peer-review
-
DGPose: Deep Generative Models for Human Body Analysis
de Bem, R., Ghosh, A., Ajanthan, T., Miksik, O., Boukhayma, A., Siddharth, N. & Torr, P., 1 Jul 2020, In: International Journal of Computer Vision. 128, 5, p. 1537-1563 27 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile
-
Learning Structured Decompositions of Data for Interpretability
Non-EU industry, commerce and public corporations
1/01/22 → 30/06/25
Project: Research
-
Enabling advanced autonomy through human-AI collaboration
Fisher, B., Bilen, H., Keller, F., Lascarides, A., Mac Aodha, O., Mollica, F., N, S., Ramamoorthy, R., Rovatsos, M. & Sevilla-Lara, L.
1/10/21 → 30/06/22
Project: Research