2018 Open AIR: Industry Open House

Friday, October 12, 2018, 9:00AM – 5:30PM
Boston University Photonics Center, Colloquium Room
8 St. Mary’s Street, 9th floor
Boston, MA 02215

Open AIR is an industry open house hosted by the Boston University AI Research Initiative and the Hariri Institute for Computing that aims to bring together AI researchers at BU with industry groups interested in AI research. The day will include research presentations, posters and demos by AIR faculty, affiliates, and their lab members, as well as invited talks by industry research labs and networking plus breakfast and lunch. The main goals of Open AIR are to showcase AI research at Boston University, increase interaction between the AIR community and industry labs, and potentially lead to future collaborations and/or internship opportunities.

Organizers
Kate Saenko (Associate Professor of Computer Science, Director of the Computer Vision and Learning Group), Stan Sclaroff (Professor of Computer Science, Interim Dean of the College and Graduate School of Arts & Sciences).

Registration
Registration closed on October 11th at 9:00am. If you have not yet registered for the event, you are still welcome to attend, however, seating is limited.

Dietary restrictions may not be accommodated after Friday, October 5th. If you have been asked to present a poster at OpenAir Day, you should bring printed posters that do not exceed the size of the foam posters at the event. Posters should be 30 inches (width) by 40 inches (height).

Friday, October 12

9:00 am – 9:30 am Breakfast
9:30 am – 9:40 am Welcome
9:40 am – 10:00 am “Adaptable and Explainable AI”

Kate Saenko, Associate Professor, Boston University

10:00 am – 10:20 am “Bilingual lexicon induction using related languages and images”

Derry Wijaya, Assistant Professor, Boston University

10:20 am – 10:40 am
“Learning to Embed while Learning to Rank”
Stan Sclaroff, Interim Dean of Arts and Sciences & Professor, Boston University
10:40 am – 11:00 am Break
11:00 am – 11:20 am Overview of Recent Research on Machine Learning

Brian Kulis, Assistant Professor, Boston University

11:30 am – 12:00 pm Panel Discussion: Kate Saenko, Derry Wijaya, Stan Sclaroff, Brian Kulis, Francesco Orabona
12:00 pm – 1:00 pm Lunch
1:00 pm – 1:20 pm “Performance isn’t Enough: Privacy and Fairness in Machine Learning”

Adam Smith, Professor, Boston University

1:20 pm – 1:40 pm “Building Alexa”

Shiv Vitaladevuni, Senior Machine Learning Manager in Alexa Speech, Amazon

1:40 pm – 2:40 pm Short Talks

  • Lei Guo, Assistant Professor: “How machine learning informs journalism research”
  • Sarah Bargal, Ph.D Candidate: “Explainable AI: Grounding and Improving Deep Learning Models”
  • Bryan Plummer: “Learning to separate categories in type-aware embedding networks”
  • Kwang-Sung Jun: Adapting to changing environments in online learning”
  • Xide Xia: “A Deep Unsupervised Method for Image Contour Detection”
2:40 pm – 3:40 pm Refreshments & Poster Presentations

  • Ali Siahkamar: “Conditioning Deep Generative Raw Audio Models for Structured Automatic Music”
  • Jiawei Chen: “VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition”
  • Jinyuan Zhao:  “Privacy-Preserving Indoor Localization via Active Scene Illumination”
  • Kuniaki Saito: “Discriminative Domain Adaptation by Classifier based Regularization”
  • Mona Jalal: “Large-scale Synthetic Domain Randomized 6DoF Object Pose Estimation Dataset for Deep Learning Applications”
  • Nataniel Ruiz: “Learning to Simulate”
  • Om Dipakbhai Thakkar: “Model-Agnostic Private Learning”
  • Ping Hu: “Motion Guided Cascaded Network for Video Object Segmentation”
  • Sarah Bargal: “Explainable AI: Grounding and Improving Deep Learning Models”
  • Siddharth Mysore: “Exploiting Environmental Variation to Improve Policy Robustness in Reinforcement Learning”
  • Vasili Ramanishka: “Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning”
  • Vijay Thakkar: “Conditioning Deep Generative Raw Audio Models for Structured Automatic Music”
  • Vitali Petsiuk: “Randomized Input Sampling for Explanations of Black-box Models”
  • Xiaoyu Li: “On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes”
  • Ximeng Sun: “Action-conditioned Video Generation”
  • Xingchao Peng: “Moment Matching for Multi-Source Domain Adaptation”
3:40 pm – 4:00 pm “Comprehensive Human State Modeling for Human Computer Interaction and Social Media Analytics”

Ajay Divakaran, Technical Director, SRI International

4:00 pm – 4:20 pm “Parameter-free Machine Learning”

Francesco Orabona, Assistant Professor, Boston University

4:20 pm – 4:40 pm “Question Answering R&D at Microsoft”

T.J. Hazen, Principal Research Manager, Microsoft

4:40 pm – 5:00 pm “Large Margin Deep Networks for Classification”

Dilip Krishnan, Senior Research Scientist, Google

5:00 pm – 5:30 pm Panel: Ajay Divakaran, Shiv Vitaladevuni, T.J. Hazen, Dilip Krishnan

Local Arrangements
Complimentary parking is available for those who will be driving. Please contact Katherine D’Angelo at ktd@bu.edu, and include your first and last name and what days you will be needing parking. The deadline to request a parking pass is Wednesday, October 10 at 3:00pm.

For more information, please contact Katherine D’Angelo, Programs & Events Manager, at ktd@bu.edu.

Event Sponsors:

     

For more information about the AI Research initiative, visit the AIR website.