Rodriques, Samuel G.

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Rodriques, S. G., Stickels, R. R., Goeva, A., Martin, C. A., Murray, E., Vanderburg, C. R., Welch, J., Chen, L. M., Chen, F., & Macosko, E. Z. (2019) · Science

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 2,424

14 examples of how LLMs can transform materials science and chemistry: A reflection on a large language model hackathon

Jablonka, K. M., Ai, Q., Al-Feghali, A., Badhwar, S., Bocarsly, J. D., Bran, A. M., Bringuier, S., Brinson, L. C., Choudhary, K., Circi, D., et al. (2023) · Digital Discovery

Machine Learning in Materials ScienceArtificial Intelligence Applications

Cited by 218

PaperQA: Retrieval-Augmented Generative Agent for Scientific Research

Lála, J., O'Donoghue, O., Shtedritski, A., Cox, S., Rodriques, S. G., & White, A. D. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 55

Language agents achieve superhuman synthesis of scientific knowledge

Skarlinski, M. D., Cox, S., Laurent, J. M., Braza, J. D., Hinks, M., Hammerling, M. J., Ponnapati, M., Rodriques, S. G., & White, A. D. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 49

LAB-Bench: Measuring Capabilities of Language Models for Biology Research

Laurent, J. M., Janizek, J. D., Ruzo, M., Hinks, M. M., Hammerling, M. J., Narayanan, S., Ponnapati, M., White, A. D., & Rodriques, S. G. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 21

Robin: A multi-agent system for automating scientific discovery

Ghareeb, A. E., Chang, B., Mitchener, L., Yiu, A., Szostkiewicz, C. J., Laurent, J. M., Razzak, M. T., White, A. D., Hinks, M. M., & Rodriques, S. G. (2025) · arXiv

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 9