CV
A PDF version of my CV is available here.
Education
Ph.D., Computer Science, University of California, Irvine, 2021–Present- Advisors: Sameer Singh, Padhraic Smyth
- Expected Graduation: December 2026
M.Sc., Computer Science and Engineering, Instituto Superior Técnico, University of Lisbon, 2016–2019- Thesis: Optimization of Time-Consuming Objective Functions: Derivative-Free Approaches and their Application in Architecture
B.Sc., Computer Science and Engineering, Instituto Superior Técnico, University of Lisbon, 2013–2016
Research Experience
Applied Research Intern — Apple (Summer 2026)- Applying post-training recipes to improve the question-answering system powering Siri.
Applied Research Intern — Capital One, New York (Jun–Sep 2025)- Investigated controllability and style transfer of LLMs for readable and accurate outputs.
- Proposed and implemented a reinforcement learning customization approach (GRPO via TRL).
- Authored 2 papers: workshop paper at EMNLP 2025 TSAR; working towards a conference paper on RL-based readability/accuracy alignment.
Research Intern — Megagon Labs, Mountain View (Jun–Sep 2024)- Analyzed hallucinations in multi-document summarization across 5 popular LLMs.
- Proposed a taxonomy of error types through large-scale human annotation; evaluated adversarial robustness and mitigation strategies.
- Resulted in a publication at NAACL 2025 Findings.
Graduate Student Researcher — University of California, Irvine (2021–Present)- Uncertainty in LLMs: Studying LLM calibration and linguistic uncertainty and its effects on human-AI decision-making and alignment with human perceptions.
- Constrained Decoding: Proposed a method leveraging an attribute verifier’s gradient to efficiently steer LM generations by reweighting the next-token distribution.
- Fair NLP: Developed an evaluation benchmark to uncover gender bias in non-stereotypical contexts (ICLR 2024).
- NLG Evaluation: Applied PEFT and ICL for automatic evaluation of generative LLMs with few labeled examples.
Research Data Scientist — Feedzai, Lisbon, Portugal (2019–2021)- Algorithmic Fairness: Developed bias mitigation methods for model selection and training via constrained optimization and hyperparameter selection. Authored 2 patents and 2 top-tier papers (ICDM 2021, ICLR 2023).
- Explainable AI: Evaluated the impact of explanations on human decision-making. Implemented concept-based explanations for fraud detection. Authored 3 patents and 3 papers (NeurIPS’20 WS, FAccT’21, ICLR’21 WS).
Graduate Student Researcher — INESC-ID, Lisbon, Portugal (2017–2019)- Investigated gradient-free methods (genetic algorithms, ML) for multi-objective optimization of time-consuming objective functions in architectural design.
Publications
Talks
Perceptions of Linguistic Uncertainty by Language Models and Humans Permalink
Talk at Mila/McGill NLP Reading Group, Montreal, QC, Canada (remote)
Can Language Models Perceive Verbalized Uncertainty?
Talk at TrustNLP Workshop at NAACL 2024, Mexico City, Mexico
An Introduction to RLHF (Preference Learning)
Invited Talk at Cognitive Science Department, University of California Irvine, Irvine, CA, USA
On the Calibration of Generative Question-Answering Models
Invited Talk at Priberam Machine Learning Lunch Seminars, Lisbon, Portugal (remote)
Concept-based Explainability: Challenges and Applications to Fraud Detection
Talk at Deep Learning Sessions Portugal Meetup, Lisbon, Portugal (remote)
Teaching
- Projects in AI (Winter 2026)
- Statistical NLP (Spring 2023)
- Machine Learning for NLP (Summer 2022)
- Advanced Programming (Spring 2019)
- Advanced Programming (Spring 2018)
- Programming Languages (Spring 2018)
Skills
- Programming Languages: Python, Java, Julia
- ML Frameworks: PyTorch, HuggingFace Transformers, scikit-learn, Apache Spark
- Data Analysis: NumPy, Pandas
- Other: Docker, PostgreSQL, SLURM
Awards & Fellowships
- ICS Steckler Family Endowed Fellowship (Sep 2024 – Jun 2025)
- Fulbright Scholar (Sep 2021 – Jun 2025)
- Grace Hopper Celebration Scholarship (2022)
- CS Department Excellence Fellowship (2021)
- Maria de Lourdes Pintasilgo Award — Young Alumna (2019)
- Teaching Excellency Award (2019)
Service
- 2026 — Conferences: ICML (Top Reviewer), ICLR, ARR (Jan, Mar, May), NeurIPS; Journal: CHBAH
- 2025 — Conferences: ICLR, NeurIPS (Top Reviewer)
- 2024 — Conferences: CoLM, ARR (Jun, Aug Top Reviewer, Oct Top Reviewer, Dec Top Reviewer); Journal: IEEE TNNLS; Workshops: XAI @ NeurIPS, RBFM @ NeurIPS, SeT LLM @ ICLR
Community Involvement
- Mentored an Undergraduate Honors Thesis on measuring gender-occupation bias amplification (Sep 2023 – Jun 2024)
- Mentorship in Machine Learning to a high school student (Jun 2023 – Sep 2023)
- Jury at World Data League Competition (2021, 2022)
- Organizer and host at Deep Learning Sessions Portugal (Mar 2021 – Jun 2023)
