
During September 2025, Tarun Kaushik expanded the Stress and Anxiety Response Dataset for the Chameleon-company/MOP-Code repository, enhancing the mental health chatbot’s ability to deliver broader coping strategies and more consistent guidance. He focused on data curation and natural language processing using Python, augmenting the chatbot’s support for users in crisis. Tarun also streamlined the data submission pipeline by decoupling large video file handling, which reduced upload bottlenecks and enabled faster dataset updates. His work improved dataset governance and documentation, supporting maintainability and future enhancements. The project demonstrated depth in chatbot development, data augmentation, and cross-functional collaboration within a safety-focused context.

September 2025 — Chameleon-company/MOP-Code: Mental Health Chatbot dataset expansion and lightweight submission flow enhancements. Key outcomes: - Delivered expanded Stress and Anxiety Response Dataset for the Mental Health Chatbot, broadening coping strategies and scenarios to improve user support and guidance consistency. Commit: 82b70733049a8a82528a1f23c2491976889aef87 (Add submission without large video files). - Streamlined data submission: decoupled handling of large video attachments to reduce upload bottlenecks and enable submissions without large files. Technologies/skills demonstrated: - Data curation and NLP dataset expansion for mental health support - Lightweight asset handling and data pipeline improvements - Version control discipline and cross-functional collaboration Business impact: - More reliable, scalable, and empathetic chatbot guidance for users in crisis, contributing to higher user satisfaction and reduced escalation risk. - Faster data contribution cycles enabling timely updates to guidance and response strategies.
September 2025 — Chameleon-company/MOP-Code: Mental Health Chatbot dataset expansion and lightweight submission flow enhancements. Key outcomes: - Delivered expanded Stress and Anxiety Response Dataset for the Mental Health Chatbot, broadening coping strategies and scenarios to improve user support and guidance consistency. Commit: 82b70733049a8a82528a1f23c2491976889aef87 (Add submission without large video files). - Streamlined data submission: decoupled handling of large video attachments to reduce upload bottlenecks and enable submissions without large files. Technologies/skills demonstrated: - Data curation and NLP dataset expansion for mental health support - Lightweight asset handling and data pipeline improvements - Version control discipline and cross-functional collaboration Business impact: - More reliable, scalable, and empathetic chatbot guidance for users in crisis, contributing to higher user satisfaction and reduced escalation risk. - Faster data contribution cycles enabling timely updates to guidance and response strategies.
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