With a background in Electrical and Biomedical Engineering, I completed my PhD in Computational Neuroscience at Dartmouth College where I studied the computational and neural mechanisms of Reinforcement Learning in the brain. Later, I joined Flatiron Institute to study the connection between Biologically Inspired Neural Networks and Representation Learning in the brain. Currently, I am a Principal Machine Learning researcher at Harbinger Health, Inc. I develope Generative models, Multimodal Representation Learning methods, and scalable ML systems for biological data. You can find more about me here. Please contact me via:
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8. Farashahi S, Wu Y, Massaad E, Hantash F, Ashrafian H, Kashef D, Chacko K (2025). Denoising Models Enhance Detection of Tumor-Derived cfDNA fragments and Cancer Tissue signal in Liquid Biopsy. Clinical Cancer Research, 31, 13.
7. Farashahi S, Kia A, Kashef D, Brown E, Hantash F, Chacko K (2024). Transfer learning for accurate tissue of origin classification from cfDNA methylation. Clinical Cancer Research, 30, 19.
6. Qin S, Farashahi S, Lipshutz D, Sengupta A, Chklovskii D, Pehlevan C (2023). Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning. Nature Neuroscience, 1-11.
5. Farashahi S, & Soltani A (2021). Computational mechanisms of distributed value
representations and learning strategies. Nature
Communications 12, 7191.
4. Friedrich J, Golkar S, Farashahi S, Genkin A, Sengupta AM & Chklovskii D (2021). Neural optimal
feedback control with local learning rules. Advances in Neural Information Processing Systems 34.
3. Farashahi S, Rowe K, Aslami Z, Lee D, & Soltani A
(2017). Feature-based learning improves adaptability without
compromising precision. Nature Communications 8(1), 1-16.
2. Farashahi S, Donahue CH, Khorsand P, Seo
H, Lee D, & Soltani A (2017). Metaplasticity as a
neural substrate for adaptive learning and choice under uncertainty. Neuron 94(2), 401-414.
1. Soltani A, Khorsand P, Guo C, Farashahi S, & Liu J (2016). Neural Substrates of Cognitive Biases during
Probabilistic Inference. Nature Communications 7(1), 1-14.