PhD researcher at Queen Mary University of London (School of Biological and Behavioural Sciences), supervised by Prof. Axel Rossberg. I apply generative AI and machine learning to ecology, predicting species distributions and community dynamics for IUCN Red List assessments.
Research interests: generative AI, diffusion models, machine learning, spatio-temporal modelling, scientific computing, individual-based models (IBM), probabilistic-stochastic-deterministic (PSD) models, and biodiversity modelling.
ORCID: https://orcid.org/0009-0000-7847-6242
Languages & Frameworks
DevOps & Tools
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IBM / ODE / PSD Framework Multi-patch individual-based model with infinite-pool assembly, ODE and PSD baselines, dispersal kernels, and invasion tracking. Highlights:
Key finding: PSD replicates IBM/ODE qualitative dynamics across body-mass regimes.
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Wildlife Biometrics & Re-identification Self-supervised features + metric learning for camera-trap individual identification. Highlights:
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Attention-UNet & Adversarial Defenses Ultrasound segmentation with robustness testing under noise and adversarial perturbations. Results:
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🎙️ NART GradingSpeech Analysis for Clinical Assessment Automated grading of National Adult Reading Test pronunciations. Features:
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Vision-Language Fusion CNN (image) + BERT (text) with late fusion classification. Results:
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Some repositories are private during active research. |
1. MetaDiffusion: A process-aware conditional diffusion model for multi-species spatial range reconstruction from sparse observations
Sara Shahin, Axel G. Rossberg Poster B-S.B.31 · ECCB (European Conference on Computational Biology) · 2026
Sara Shahin, Jacob D. O'Sullivan, Axel G. Rossberg Submitted to Ecology Letters · bioRxiv preprint · 2026
DOI: https://doi.org/10.64898/2026.04.21.719942
3. Evaluation of Ensemble Learning for Mitigating Adversarial Attacks in Industrial Object Detection
Shashank Pulijala, Sara Shahin, Tapadhir Das, Raj Mani Shukla
Conference Paper · IEEE · 2024
DOI: 10.36227/techrxiv.171561173.31420188/v1
Preprint DOI: https://doi.org/10.36227/techrxiv.171561173.31420188/v1
💡 Note: Most of my active development happens in private repositories for ongoing PhD research. Public contributions don't reflect the full scope of my work.
self.phd_focus = "Generative AI for spatio-temporal biodiversity prediction" self.methods = [ "MetaDiffusion: conditional diffusion model trained on simulated communities", "Individual-based models (IBM), ODE and PSD simulation", "GPU-accelerated simulation", "Uncertainty quantification from sparse observations" ] self.applications = [ "Species distribution prediction", "IUCN Red List metrics (area of occupancy, extent of occurrence)", "Conservation science" ]
