Biography
Siddharth N. (Sid) is a Reader (Associate Professor) 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.
Most Recent Publications
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Shi Y, Paige B, Torr PHS & Siddharth N (2020)
Capturing Label Characteristics in VAEs
Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)
Simulation-Based Inference for Global Health Decisions
Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)
DGPose: Deep Generative Models for Human Body Analysis
de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563
A Revised Generative Evaluation of Visual Dialogue
Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)
Research Interests
- Explainable AI
- Human-Like Learning
- Unsupervised Representation Learning
- Approximate Probabilistic Inference
- Probabilistic Programming
Research Groups
Related Academics
Most Recent Publications
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Shi Y, Paige B, Torr PHS & Siddharth N (2020)
Capturing Label Characteristics in VAEs
Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)
Simulation-Based Inference for Global Health Decisions
Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)
DGPose: Deep Generative Models for Human Body Analysis
de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563
A Revised Generative Evaluation of Visual Dialogue
Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)
Publications
Most Recent Publications
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Shi Y, Paige B, Torr PHS & Siddharth N (2020)
Capturing Label Characteristics in VAEs
Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)
Simulation-Based Inference for Global Health Decisions
Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)
DGPose: Deep Generative Models for Human Body Analysis
de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563
A Revised Generative Evaluation of Visual Dialogue
Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)
DPhil Opportunities
I take on 1-2 PhD students each year. Projects will broadly be on learning/using structured representations of perceptual data, and developing cutting-edge probabilistic inference tools to facilitate this.
Most Recent Publications
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Shi Y, Paige B, Torr PHS & Siddharth N (2020)
Capturing Label Characteristics in VAEs
Joy T, Schmon SM, Torr PHS, Siddharth N & Rainforth T (2020)
Simulation-Based Inference for Global Health Decisions
Witt CSD, Gram-Hansen B, Nardelli N, Gambardella A, Zinkov R et al. (2020), ICML Workshop on Machine Learning for Global Health, Thirty-Seventh International Conference on Machine Learning (ICML 2020)
DGPose: Deep Generative Models for Human Body Analysis
de Bem R, Ghosh A, Ajanthan T, Miksik O, Boukhayma A et al. (2020), International Journal of Computer Vision, 128(2020), 1537-1563
A Revised Generative Evaluation of Visual Dialogue
Massiceti D, Kulharia V, Dokania PK, Siddharth N & Torr PHS (2020)
