Silvio Amir
(he/him/his)
Assistant Professor
Research interests
- Natural language processing
- Machine learning
- Information retrieval
- Social media analysis
Education
- Postdoctoral Fellow, Center for Language and Speech Processing, Johns Hopkins University
- PhD in Information Systems and Computer Engineering, Instituto Superior Tecnico, Universidade de Lisboa — Portugal
- MS in Computer Science and Engineering, Faculdade de Ciencias da Universidade de Lisboa — Portugal
Biography
Silvio Amir is an assistant professor in the Khoury College of Computer Sciences at Northeastern University, based in Boston. He is a core faculty member in Northeastern's Institute for Experiential AI and the NULab for Texts, Maps, and Networks.
Amir's research develops natural language processing, machine learning, and information retrieval methods for personal and user-generated text, such as social media and clinical notes from electronic health records. He is primarily interested in methods for tasks involving subjective, personalized or user-level inferences (e.g. opinion mining and digital phenotyping). Through his work, Amir aims to improve the reliability, interpretability, and fairness of predictive models and analytics derived from personal and user-generated data — all part of efforts to develop human-centered AI for social good. To achieve these goals, he collaborates with domain experts on multidisciplinary projects to address real-world problems in the social sciences, medicine, and epidemiology.
After completing his doctorate at the University of Lisbon — conducting part of his research as a visiting researcher at the University of Texas at Austin and at Northeastern University — Amir moved to John Hopkins University, where he researched at the Center for Language and Speech Processing and served as a lecturer at the Whiting School of Engineering.
Recent publications
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On-the-fly Definition Augmentation of LLMs for Biomedical NER
Citation: Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik. (2024). On-the-fly Definition Augmentation of LLMs for Biomedical NER CoRR, abs/2404.00152. https://doi.org/10.48550/arXiv.2404.00152 -
SemEval-2023 Task 8: Causal Medical Claim Identification and Related PIO Frame Extraction from Social Media Posts
Citation: Vivek Khetan, Somin Wadhwa, Byron C. Wallace, Silvio Amir. (2023). SemEval-2023 Task 8: Causal Medical Claim Identification and Related PIO Frame Extraction from Social Media Posts SemEval@ACL, 2266-2274. https://aclanthology.org/2023.semeval-1.311 -
An Example of (Too Much) Hyper-Parameter Tuning In Suicide Ideation Detection
Citation: Annika Marie Schoene, John E. Ortega, Silvio Amir, Kenneth Church . (2023). An Example of (Too Much) Hyper-Parameter Tuning In Suicide Ideation Detection ICWSM, 1158-1162. https://doi.org/10.1609/icwsm.v17i1.22227 -
Revisiting Relation Extraction in the era of Large Language Models
Citation: Somin Wadhwa, Silvio Amir, Byron C. Wallace. (2023). Revisiting Relation Extraction in the era of Large Language Models CoRR, abs/2305.05003. https://doi.org/10.48550/arXiv.2305.05003 -
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs
Citation: Somin Wadhwa, Jay DeYoung, Benjamin E. Nye, Silvio Amir, Byron C. Wallace. (2023). Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs CoRR, abs/2305.03642. https://doi.org/10.48550/arXiv.2305.03642 -
RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media
Citation: Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron C. Wallace. (2022). RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media CoRR, abs/2210.06331. https://doi.org/10.48550/arXiv.2210.06331 -
UserNLP’22: 2022 International Workshop on User-centered Natural Language Processing
Citation: Xiaolei Huang , Lucie Flek, Franck Dernoncourt, Charles Welch, Silvio Amir, Ramit Sawhney, Diyi Yang. (2022). UserNLP'22: 2022 International Workshop on User-centered Natural Language Processing WWW (Companion Volume), 1176-1177. https://doi.org/10.1145/3487553.3524879 -
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement
Citation: Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia Lynn Nobles. (2021). Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement Proc. ACM Hum. Comput. Interact., 5, 107:1-107:28. https://doi.org/10.1145/3449181 -
On the Impact of Random Seeds on the Fairness of Clinical Classifiers
Citation: Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace. (2021). On the Impact of Random Seeds on the Fairness of Clinical Classifiers NAACL-HLT, 3808-3823. https://doi.org/10.18653/v1/2021.naacl-main.299
