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Research Opportunities

The MultiComp Lab has a great tradition of including undergraduate and professional masters students in our research. The opportunities listed at the left are single-term, unfunded research appointments that may be extended to additional semesters. Each also includes a brief description, required skills, and contact information. Please email Nicki Siverling with any questions.

Opportunities for the 2021 Fall Term include:

Benchmarking and Analyzing Multimodal Models
Mentor: Paul Liang
Description: Innovations in multimodal models have enabled large-scale representation learning from heterogeneous sources (e.g., images, videos, text, speech, audio, time-series, and sensor data) across a variety of real-world applications. However, there remains challenges in benchmarking the generalization of methods across domains and their robustness to noisy and missing modalities. This project will build large-scale environments that rigorously test multimodal models under real-world scenarios and eventually improve their capabilities for real-world applications.
Contact: Interested students should send an email to (Paul Liang) with their CV.

Towards Socially Intelligent AI
Mentor: Paul Liang
Description: As intelligent systems increasingly blend into our everyday lives, building AI systems that display social intelligence has become one of the next grand challenges in the field. Socially intelligent AI should comprehend human social cues, intents, and affective states, engage in social conversation, and understand social norms and commonsense in order to maintain a rich level of interpersonal interaction with humans. This project will tackle this long-term research goal from multiple dimensions such as building better simulation environments reflecting socially intelligent behaviors, developing multimodal models of human communication, and designing models of social interaction.
Contact: Interested students should send an email to (Paul Liang) with their CV.