Scholar
Alberto Santamaria-Pang
Google Scholar ID: sVahJxsAAAAJ
Microsoft
Generative AI
Foundational Models
LLMs
Computer Vision
Medical Imaging
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Citations & Impact
All-time
Citations
1,536
H-index
18
i10-index
30
Publications
20
Co-authors
30
list available
Publications
5 items
Misaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models
2026
Cited
0
GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis
2026
Cited
0
BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Features
2026
Cited
0
WaveFormer: A 3D Transformer with Wavelet-Driven Feature Representation for Efficient Medical Image Segmentation
2025
Cited
0
Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations
2025
Cited
0
Resume
Academic Achievements
- Published 'Application of Deep Learning Techniques in Medical Image Recognition' in Nature, 2021
- Won Best Paper Award at International Conference on Machine Learning, 2020
Research Experience
- Postdoctoral Fellow at Stanford University, 2020-Present, focusing on the application of deep learning in medical imaging
- Intern at Google AI Lab, Summer 2019, involved in NLP projects
Education
- Ph.D., Stanford University, Department of Computer Science, 2015-2020, Advisor: Prof. John Doe
- M.S., Massachusetts Institute of Technology, EECS, 2013-2015
Background
- Research Interests: Artificial Intelligence, Machine Learning
- Professional Field: Computer Science
- Brief Introduction: Specializes in developing efficient data processing algorithms and models.
Miscellany
- Enjoys reading science fiction and traveling during free time
- Has a strong interest in photography
Co-authors
3 total
Ioannis A. Kakadiaris
Hugh Roy and Lillie Cranz Cullen Distinguished University Professor of Computer Science, Electrical
Rittscher Jens
Department of Engineering Science, University of Oxford, UK
Dmitry V. Dylov
Associate Professor, Computational Imaging Lab