Adrián Bazaga's Homepage
AI Research Scientist
Welcome to my website!
Research Interests:
My research is centered around advancing the capabilities of AI, particularly in the realms of multimodality and large language models. I aim to develop innovative architectures that can seamlessly integrate diverse data modalities to address both fundamental challenges and real-world problems 🧪. My current focus is on enhancing generative models, expanding their multimodal capabilities, refining new training methodologies, improving inference efficiency, and ensuring robustness and alignment. I am passionate about using AI to contribute to scientific discovery and am always open to collaborations that push the boundaries of what AI can achieve 👐.
Background:
I am a final-year Ph.D. student at the University of Cambridge, under the supervision of Prof. Pietro Liò and Prof. Gos Micklem. My academic journey began with a Bachelor’s in Computer Science, followed by a Master’s in Machine Learning. I have honed my research skills through internships at leading organizations like Microsoft Research and Amazon Science, where I worked in areas such as reasoning with Large Language Models and novel training schemes to improve few-step generation for diffusion models. Previously, I spent ∼5 years in various start-ups, working at the intersection of AI and medicine.
Beyond Research:
In addition to my core research, I am exploring how advancements in natural language processing, particularly generative models, can revolutionize education and governance. I am deeply committed to conducting research with a significant impact and am eager to engage in discussions and collaborations that align with these goals.
News
| Sep 20, 2024 | [Paper] Our paper “HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs” has been accepted at EMNLP 2024 🎉 |
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| Aug 15, 2024 | I joined Amazon Science AGI team as a Research Scientist Intern. Excited to work on reasoning with LLMs with Bill Byrne, Rexhina Blloshmi and Adrià de Gispert, in Berlin, Germany. ⭐ |
| Aug 13, 2024 | I have accepted to serve as Reviewer for the International Conference on Learning Representations (ICLR). 👍 |
| Jun 16, 2024 | Our paper “FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models” is now on arXiv. 📋 |
| Jun 5, 2024 | [Paper] Our paper “TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting” has been accepted at ICML 2024 🎉 |
| Jun 1, 2024 | I received a PhD Student Award by the Cambridge Society for the Application of Research in recognition of outstanding research with real world application, for my work on language-graph modality alignment for evidence retrieval. 🏅 |
| May 1, 2024 | I joined Microsoft Research as a Research Scientist Intern. Thrilled to work on generative modeling (improved few-step generation for diffusion models) with Javier Zazo, Richard Turner and Ted Meeds, in Cambridge, UK. ⭐ |
| Mar 16, 2024 | [Paper] Our paper “Language Model Knowledge Distillation for Efficient Question Answering in Spanish” has been accepted at ICLR 2024 🎉 |
| Mar 6, 2024 | [Paper] Our paper “Unsupervised Pretraining for Fact Verification by Language Model Distillation” has been accepted at ICLR 2024 🎉 |
| Feb 15, 2024 | I was granted “Visiting Student” status in the Computer Science & Technology department under Pietro Liò’s group. I’m working on tabular LLMs to improve small tabular classification problems and LLMs for modeling partial differential equations 🚀 |