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J.P. Lewis · Housam Khalifa Bashier Babiker · Zhongang Qi · Laura Rieger · Ning Xie · Filip Dabek · Koushik Nagasubramanian · Bolei Zhou · Dieuwke Hupkes · CHUN-HAO CHANG · Pamela K Douglas · Enea Ceolini · Derek Doran · Yan Liu · Fuxin Li · Randolph Goebel

Sat Dec 09 11:45 AM -- 12:15 PM (PST) @
in Interpreting, Explaining and Visualizing Deep Learning - Now what ? »

Author Information

J.P. Lewis (SEED and Victoria University)
Housam Khalifa Bashier Babiker (University of Alberta)
Zhongang Qi (Oregon State University)
Laura Rieger (Denmark Technical University)
Ning Xie (Wright State University)

I’m a second year PhD student of Computer Science & Engineering at Wright State University, Dayton OH. My research interests are broadly in **data science**, with a focus on deep learning, computer vision, and web systems modeling. I possess industry experience in neural and kernel learning methods for image processing and sequence prediction. My academic research studies deep neural network mechanisms toward interpretability, via convolutional neural network(CNN) visualization and other techniques. I have also applied Recurrent Neural Networks to reveal latent behavioral patterns in classes of automated traffic faced by web systems. **Actively seeking a summer internship.**

Filip Dabek (National Intrepid Center of Excellence (NICoE), Walter Reed National Military Medical Center Bethesda, MD)

Data Scientist at NICoE, Walter Reed Bethesda. PhD Student at UMBC. Interested in machine learning and visualization.

Koushik Nagasubramanian (Iowa State University)
Bolei Zhou (Massachusetts Institute of Technology)
Dieuwke Hupkes (ILLC, University of Amsterdam)
CHUN-HAO CHANG (University of Toronto, Vector Institute)
Pamela K Douglas (UCF/UCLA)

Computational neuroscientist interested in causal modeling of mutlimodal data, predictive coding, and attention.

Enea Ceolini (ETH Zurich, University Zurich)
Derek Doran (Wright State University)
Yan Liu (DiDi/University of Southern California)
Fuxin Li (Oregon State University)
Randolph Goebel (University of Alberta, Alberta Machine Intelligence Institute)

R.G. (Randy) Goebel is currently professor and chair in the Department of Computing Science at the University of Alberta He received the B.Sc. (Computer Science), M.Sc. (Computing Science), and Ph.D. (Computer Science) from the Universities of Regina, Alberta, and British Columbia, respectively. Professor Goebel's research is focused on the theory and application of intelligent systems. His theoretical work on abduction, hypothetical reasoning and belief revision is internationally well know, and his recent application of practical belief revision and constraint programming to scheduling, layout, and web mining is now having industrial impact. He is one of the founders of the Alberta Ingenuity Centre for Machine Learning (AICML), and is now working on applications of machine learning to various problems, including web visualization and scheduling. Randy has previously held faculty appointments at the University of Waterloo and the University of Tokyo, and is actively involved in academic and industrial collaborative research projects in Canada, Australia, Malaysia, Europe and Japan.

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