I am currently working on a new ventures. Previously, I Co-Founded Robust.AI and served as Chief Science Officer. Prior to Robust.AI, I was a Senior Technical Manager at the Center for Vision Technologies, SRI International, where I received $20M+ in DARPA funding as a principal investigator on AI and ML projects including Machine Common Sense, Communicating with Computers, and Explainable Artificial Intelligence. I received my PhD from Oregon State University, where my research focus was on generative hierarchical graphical models appled to computer vision problems such as monocular extraction of 2.1D sketch, multi-view 3D reconstruction and activity recognition in large scale videos.
Download Full C.V.LinkedInContact MeScholarBlogThe current focus of my research are deep generative models and graph networks applied to language and vision problems such as: generative ranking, visual storytelling, commonsense grounding and visual question answering. The main idea is to visualize textual information and use it to search, animate, or communicate.
- Understanding Attention and Generalization in Graph Neural Networks, accepted at NeurIPS2019.
- Image Classification with Hierarchical Multigraph Networks, accepted at BMVC2019.
- Data-Efficient Mutual Information Neural Estimator, on arXiv.
- Understanding Attention in Graph Neural Networks, accepted at ICLR-W2019
- Aesop: A Visual Storytelling Platform for Conversational AI and Common Sense Grounding, accepted at AI Communication 2019
- Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules, paper accepted at NeurIPS-W2018
- Learn, Generate, Rank: Generative Ranking of Motion Capture, demo accepted at ECCV2018
- Aesop: A Visual Storytelling Platform for Conversational AI awarded best demo award at IJCAI2018
B. Knyazev, G. W. Taylor, M. R. Amer. Understanding Attention and Generalization in Graph Neural Networks. NeurIPS, 2019. PDF
B. Knyazev, X. Lin M. R. Amer, G. W. Taylor. Image Classification with Hierarchical Multigraph Networks. BMVC, 2019. PDF
X. Lin, I. Sur, S. Nastase, A. Divakaran, U. Hasson, M. R. Amer. Data-Efficient Mutual Information Neural Estimator. arXiv, 2019. PDF
B. Knyazev, G. W. Taylor, M. R. Amer. Understanding Attention in Graph Neural Networks. International Conference on Learning Representations, 2019. Oral presentation. PDF
T. J. Meo, C. Kim, A. Raghavan, A. Tozzo, D. A. Salter, A. Tamrakar, M. R. Amer. Aesop: A Visual Storytelling Platform for Conversational AI and Common Sense Grounding. AI Communications, 2019 Pre-Print.
X. Lin, M. R. Amer. Human Motion Generation from Text using Dense Validation Adversarial Networks. arXiv, 2018. PDF
B. Knyazev, G. W. Taylor, X. Lin, M. R. Amer. Discovering and Fusing Relations in Molecules with Spectral Graph Networks. Neural Information Processing Systems Workshops, 2018. PDF
T. Meo, A. Raghavan, D. Salter, A. Tozzo, A. Tamrakar, and M. R. Amer. Aesop: A Visual Storytelling Platform for Conversational AI, International Joint Conference on Artificial Intelligence, 2018. Best demo award. PDF
X. Lin, C. Kim, T. Meo, and M. R. Amer. Learn, Generate, Rank: Generative Ranking of Motion Capture. European Conference on Computer Vision, 2018. PDF
D. Ramachandram, M Lisicki, TJ Shields, M.R. Amer, GW Taylor. Bayesian optimization on graph-structured search spaces: Optimizing deep multimodal fusion architectures. Neurocomputing, 2018. PDF
M. Ehrlich, T. J. Shields, T. Almaev, M. R. Amer. Facial Attributes Classification using Multi-Task Representation Learning. IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016. PDF
M. R. Amer and S. Todorovic. Sum Product Networks for Activity Recognition in Videos. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016. PDF
M. R. Amer, S. Yousefi, R. Raich, and S. Todorovic. Monocular Extraction of 2.1D Sketch using Constrained Convex Optimization. International Journal of Computer Vision, 2015. PDF
M. R. Amer, A. Fern, S. Todorovic, S. Zhu. Monte Carlo Tree Search for Scheduling Activity Recognition. International Conference on Computer Vision, 2013. PDF
Full Publication List ...
- ACM-MM Workshop on Computational Models of Social Interactions and Behaviors: Human-Computer-Media Communication, 2015
- CVPR Workshop on Computational Models of Social Interactions and Behaviors: Grounding, Sensing, and Applications, 2014
- ICCV Workshop on Understanding Human Activities: Context and Interactions, 2013
- Publications Chair: CVPR'19
- Program Comittee: CVPR’14-19, ECCV’16-18, ICCV’15-17, NIPS’14-18, ICML’15-19, ICLR’17-18, PAMI'15, IJCV'15-16
- 07/2018 IJCAI - Best Demo Award
- 12/2017 SRI - Most Creative Talk
- 06/2010 OSU - EECS Teaching Assistant of the year
- 08/2010 INRIA - Best Poster Award
- 12/2017 SRI - Generative Adversarial Networks for Vision
- 12/2016 SRI - Unified framework for machine learning
- 12/2015 SRI - Social interaction modeling using dynamic hybrid models
- 03/2014 Amazon - Hybrid models for event detection in time-series data at
- 06/2013 SRI - Sum-Product networks for activity recognition in videos
- 11/2012 ECCV - Cost-Sensitive inference for multi-scale activity recognition
Why The Military And Corporate America Want To Make AI Explain Itself, Fast Company Magazine, 06/2017
Teaching bots how the world works, AXIOS 06/2019
5 of the smartest people in AI teamed up to make awesome robots, TNW, 06/2019
Robust.AI launches to build an industrial-grade cognitive platform for robots, TechCrunch, 06/2019