Nawaf Alampara

I am second-year PhD student, working with Dr. Kevin Maik Jablonka. I'm building machine learning systems to speed up scientific research, and I love projects that involve both research and building the tooling that enables and accelerates that research. Lately, I’ve been analyzing general-purpose AI models/systems to understand their limitations in scientific applications—where they fail—and interpreting them to uncover why they fail. My goal is to use these insights to design AI systems that aren’t just impressive on benchmarks but truly impactful for advancing science and research.

Experience

Publications

AI4Mat-Vienna 2024 2024

⭐ spotlight (oral)

MatText: Do Language Models Need More than Text & Scale for Materials Modeling?

Nawaf Alampara, Santiago Miret, Kevin Maik Jablonka

PaperCode

Revealing Transformer models' (IFT and trained from scratch) limitations in capturing 3D geometric information crucial for materials modeling.

2024

Are large language models superhuman chemists?

Adrian Mirza, Nawaf Alampara, et al.

PaperCodeLeaderboard

First comprehensive benchmark for chemistry-specific AI capabilities, evaluating chemical knowledge, intuition, and reasoning of LLMs against human chemists.

AI4Mat-NeurIPS 2024 2024

⭐ spotlight (oral)

Probing the limitations of multimodal language models for chemistry and materials research

Nawaf Alampara, et al.

PaperLeaderboard

Multimodal benchmark for chemistry/materials science for AI with ablations to interpret the limitations

Journal of Physics D: Applied Physics 2024

Formation of an extended defect cluster in cuprous oxide

G Aggarwal, S Chawla, AJ Singh, Nawaf Alampara, et al.

Paper

Characterization of intrinsic defects and dopants in Cu₂O, leading to discovery and experimental validation of new defect formation.

Education

Portfolio