Research Intern: Multi-Modal Machine Learning in Affective Computing - Honda Research Institute USA

Research Intern: Multi-Modal Machine Learning in Affective Computing

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Research Intern: Multi-Modal Machine Learning in Affective Computing

Job Number: P25INT-13
Honda Research Institute USA (HRI-US) is seeking a research intern to advance group state sensing research. In human-only and human-AI teams, there are key characteristics such as group performance, team cohesion, leadership role, and theory-of-minds. The data consist of audio, video, gaze, body movement, and physiological signals. You are expected to build social signal processing pipelines to process these signals, focus on synchronized interaction features, and learn group states. The internship is in the intersection of machine learning, human-computer interaction, and social signal processing. The intern will contribute to building machine learning pipelines and models that capture group-level phenomena from individual-level signals, enabling new insights into team performance and human-AI collaboration.
San Jose, CA

 

Key Responsibilities

 
  • Pre-process, synchronize, and extract from heterogeneous data streams
  • Design neural network strucutres, and interpretable machine learning models
  • Fuse orgainizational psychology theories into machine learning model
  • Identify emerging behaviors in group state change, such as group-level synchrony and alignment

 

Minimum Qualifications

 
  • Strong M.S. or Ph.D. candidates in Computer Science, Electrical Engineering, Cognitive Science, Robotics, or related field
  • Strong background in mahcine learning, large language models (LLMs), and visual langugae model (VLM)
  • Familiarity with human social signal processing
  • Strong verbal and written communication skills

 

Bonus Qualifications​

  • Proven publication record in machine learning, especially in top AI conferneces such as Neurips, AAAI, ICLR.
  • Demonstrated skills in designing multimodal machine learning (e.g., transformers, fusion methods), and LLM-based architecture (e.g., LLM-tuning)
  • Knowledge of group interaction, especially human-AI interaction
  • Experiences with time-series signals, like eye gaze, and physiological signals
  • Experiences with human internal states

 

Years of Work Experience Required  0
Desired Start Date 5/4/2026
Internship Duration 3 Months
Position Keywords ​Multimodal Machine Learning, Human-AI Teaming, Collective Intelligence 

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- A cover letter highlighting relevant background (Optional)

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