Xerox Engineering Research Fellows
2020 Research Opportunities
Research Projects: Human-Computer Interaction (HCI) and Artificial Intelligence (AI)
The Bai Lab (https://zhenbai.io), as part of the ROCHCI group (https://roc-hci.com/), focuses on making HumanComputer Interaction (HCI) and Artificial Intelligence (AI) coevolve. We seek students with experience or interest in one or more of the following areas: AR/VR, AI reasoning, Natural Language Processing, Computer Vision, Data Mining and system design and development (e.g. web, mobile).
One of the Xerox summer interns will join the AI4K12 research project, which aims to provide a highly interactive and accessible learning environment that supports AI literacy for K12 students and teachers in STEM contexts. There is an emerging presence of AI technologies in our everyday life from voice assistants such as Echo and Google home to smart life systems such as Fitbit and Spotify music suggestion. It is becoming more and more important for people without an AI background to understand the fundamentals of how a machine thinks and behaves, in order to better interact and collaborate with our increasingly intelligent work and life environment. To address the above challenges for students and teachers in formal and informal learning settings, and deepen our understanding of AI-empowered STEM learning, we are looking for one student with an interest in playful learning interfaces, AR/VR, intelligent social agents, and CS and STEM education to join our project. 2.
The other Xerox summer intern will join the TIPs project, which aims to provide a novel AR system that supports hearing parent-deaf child interaction to enhance early sign language exposure and communication skills. Parent-child interaction provides a linguistic and socially-rich environment for critical language, cognitive, and social emotional development. Over 90 percent of DHH children in the United States, however, are born to hearing parents with little knowledge of American Sign Language (ASL), which leaves the majority of deaf children at risk of language deprivation from limited access to linguistic communication. In this new project, we are aiming to develop theoretical and computational models of parent-child interaction in sign language during face-to-face interaction, and develop adaptive AR and multimodal 3D technologies to support real-time communication in ASL between hearing parents and deaf children. We are looking for one student with an interest in multimodal behavior analysis, AR/VR interfaces, and assistive technology to join our project.
Research Projects: Human-Computer Interaction Projects Related to Machine Learning, Speech Analysis, Web Programming, UX Design, Signal Processing
How do we develop technologies that understand and respond to human emotion? Can a computer reliably understand facial expressions, spoken words, body language, intonation and make a prediction about the mental state of the human participant?
In addition to the recognition of the human mental state, what new possibilities can this technology enable?
In our ongoing work, we show that using the technology, we can improve the lives of disadvantaged, ill, disabled, and other individuals who struggle with socio-emotional communication, such as those with autism, severe anxiety, neurodegenerative disease, and terminal illness. Other applications include public speaking, job interviews, music training, negotiations, collaborations, and credibility. Check out the projects page for more details.
We welcome students with an interest and expertise in machine learning, speech analysis, web programming, UX design, signal processing, and running experiments with human participants.
To learn more about the group, visit roc-hci.com, or follow us @rochci on twitter.
Research Projects: Data Mining and Computer Vision
- Social media data mining: prediction, forecasting, profiling, and recommendation using open-source data;
- Biomedical informatics: healthcare and wellness analytics using text and visual data;
- Computer vision: recognition of objects, scenes, people, locations, actions and events from images and video;
- Vision and language: description and explanation of visual content; language-based search and retrieval;
- Machine learning: learning with large scale loosely labeled web data, cross-domain learning, few-shot learning;
- Mobile / Pervasive computing: context-aware applications; multimodal inference from multiple sensors.