Scholar

Moussa Koulako Bala Doumbouya

Google Scholar ID: PKYjYbcAAAAJ

Stanford University, GNCode

computational educationnatural language processingcomputer visiondeep learning

Citations & Impact

All-time

Citations

7,440

H-index

i10-index

Publications

Co-authors

list available

Contact

Publications

20 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Published several papers including 'Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity' (Under peer review at NeurIPS 2025), 'h4rm3l: A Dynamic Benchmark of Composable Jailbreak Attacks for LLM Safety Assessment' (ICLR 2025), 'Handwritten Code Recognition for Pen-and-Paper CS Education' (L@S 2024), 'Machine Translation for ߒߞߏ (NKo): Tools, Corpora, and Baseline Results' (WMT 2023).

Research Experience

Worked as a software engineer and research engineer at Libera, Agero, EBSCO, VideoIQ/Avigilon/Motorola, and Apple. Work ranged from enterprise software development and large-scale computer vision for video analytics to neural network interpretability research for low-power devices and autonomous navigation systems.

Education

Ph.D. student in Computer Science at Stanford University, advised by Christopher Manning and Dan Jurafsky.

Background

A fifth-year Computer Science Ph.D. student with research interests in Artificial Intelligence (AI), Natural Language Processing (NLP), and Computational Pedagogy. Focuses on how machine learning can augment pedagogy and how insights from psychology can guide the development of human-interpretable machine learning algorithms. Committed to advancing STEM education in West Africa and the inclusion of underserved languages in NLP.

Miscellany