Scholar
Jacqueline R. M. A. Maasch
Google Scholar ID: 5l9n9J8AAAAJ
Cornell Tech | Department of Computer Science
Citations & Impact
Citations
621
H-index
9
i10-index
8
Publications
19
Co-authors
0
Publications
Resume
Academic Achievements
- CausalARC: Abstract Reasoning with Causal World Models – NeurIPS LAW 2025
- Compositional Causal Reasoning Evaluation in Language Models – ICML 2025
- Local Causal Discovery for Structural Evidence of Direct Discrimination – AAAI 2025
- Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs – UAI 2024
- Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning – Cell Host & Microbe 2023
- Co-authored Probabilistic Graphical Models: A Concise Tutorial (200-page review, under review)
- Multiple papers accepted at top venues including ICLR 2025 (oral, top 1.8%), NeurIPS 2024, NeurIPS LAW 2025
- Work featured in NPR, Nature News, CNN, and Vox
Background
- Fifth-year PhD candidate in Computer Science at Cornell Tech and the Weill Cornell Medicine Institute of AI for Digital Health
- Research focuses on open problems in AI reasoning: building reasoning machines, theoretical and practical requirements, and societal implications
- Interested in using machine learning to support human reasoning and decision-making under uncertainty
- Approaches problems primarily through probabilistic and causal graphical modeling
- Motivated by urgent societal challenges such as drug discovery and fairness in healthcare