Hi there! I'm a 2nd year Ph.D. student at MIT. I'm focusing my research on child-proof machine learning. Coming to my Ph.D. program, I was curious and motivated to explore how to make the internet a safer place for children. I'm orienting my work towards that on its intersection with natural language processing.
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4. Saldias, B., & Roy, D. (July, 2020) Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types. Proceedings of the 2020 ACL Workshop on Narrative Understanding, Storylines, and Events (NUSE). ACL.
3. Bhargava, R.*, Chung, A.*, Gaikwad, N.*, Hope, A.*, Jen, D.*, Rubinovitz, J.*, Saldias, B.*, & Zuckerman, E.* (2019, November). Gobo: A System for Exploring User Control of Invisible Algorithms in Social Media. Proceedings of the 2019 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW). ACM. *All authors contributed equally to this research.
2. Saldias, B., & Picard, R. (2019, September). Tweet Moodifier: Towards Giving Emotional Awareness to Twitter Users. Proceedings of the 2019 International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE.
1. Saldias, B., Protopapas, P., & Pichara, K. (2019, May). A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. Proceedings of the 2019 SIAM International Conference on Data Mining (SDM) (pp. 756-764). SIAM.