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Merge pull request #3 from OzGitelson/main
add projects
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_includes/header.html

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<header class="site-header" style="border-top: 0px;">
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<div class="wrapper">
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{%- assign default_paths = site.pages | map: "path" -%}
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{%- assign page_paths = site.header_pages | default: default_paths -%}
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{%- assign titles_size = site.pages | map: 'title' | join: '' | size -%}
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<a class="site-title" rel="author" href="{{ "/" | relative_url }}">{{ site.title | escape }}</a>
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{%- if titles_size > 0 -%}
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<nav class="site-nav">
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<input type="checkbox" id="nav-trigger" class="nav-trigger" />
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<div class="trigger">
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{%- for path in page_paths -%}
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{%- assign my_page = site.pages | where: "path", path | first -%}
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{%- if my_page.title -%}
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<a class="page-link" href="{{ my_page.url | relative_url }}">{{ my_page.title | escape }}</a>
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{%- endif -%}
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{%- endfor -%}
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</div>
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</nav>
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{%- endif -%}
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</header>

assets/images/course_feedback.png

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assets/images/mas_dataset.png

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assets/images/ommie.png

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assets/images/stress_detector.png

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projects.md

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layout: page
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title: Projects
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---
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coming soon...
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## MAS Dataset
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![MAS Dataset](assets/images/mas_dataset.png)
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<br><br>
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I curated a dataset of 353 short clips of people in monologue scenarios experiencing stress. Each clip is annotated for stress across four audio-visual modalities. Labels are high quality, with an inter-rater reliability of 0.85--significantly higher than comparable datasets.
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<br>
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<br>
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## Multimodal Stress Detector
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![Multimodal Stress Detector](assets/images/stress_detector.png)
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<br><br>
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I designed an audio-visual stress detector that uses late fusion to interpret expressions of stress across multiple modalities. This approach allows the system to combine the strength of multiple modalities while maintaining robust performance even when some are unavailable. This system achieved an F1 score of 0.85 on the MAS dataset and is currently being investigated for use in detecting and correcting implicit bias
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<br>
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<br>
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## Ommie
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![Ommie](assets/images/ommie.png)
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<br><br>
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I helped write the control architecture of Ommie, a therapy robot being deployed in hospitals, wellness clinics, schools, and in the home. My changes to the high-level behavior loops and lower-level hardware drivers drastically improved Ommie's maximum continuous runtime, uncapping it from less than five minutes to virtually unlimited
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<br>
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<br>
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## Real-Time Course Feedback
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![Course Feedback](assets/images/course_feedback.png)
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<br><br>
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I led a team of undergrads to design a system that allowed students to give feedback on a class in real-time using a Kinect body-tracking system installed outside the lecture hall. Out of 36 teams, our project won the class choice award for CPSC 484: Human-Computer Interaction.

publications.md

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*indicates equal contribution
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## Integrating Multimodal Affective Signals for Stress Detection from Audio-Visual Data
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![Stress Detection](assets/images/stress%20detection.png) <br><br>
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![Stress Detection](assets/images/icmi2024.png) <br><br>
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Debasmita Ghose\*, __Oz Gitelson__\*, Brian Scassellati
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ACM International Conference on Multimodal Interaction, 2024 (__ICMI 2024__), San Jose, Costa Rica

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