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I’m generally interested in building capable and useful machine learning models for scientific applications. Current projects include: (1) developing fully open large-scale datasets and generative models for systems neuroscience and (2) developing 3D/4D segmentation models for electron microscopy and light-sheet microscopy volumes. Some of my earlier work involved training self-supervised models on large-scale "human-like" visual and multimodal data in an effort to understand what modern self-supervised learning algorithms can learn from such data without strong inductive biases. Please feel free to reach out to me via email (find my email address from the author line here).
Orhan AE, Wang F (2025) The Neural Pile: 476 billion tokens of broad-coverage spiking neural activity data. Foundation Models for the Brain & Body Workshop @ NeurIPS 2025
Willeke KF, et al. (2025) OmniMouse: Scaling properties of multi-modal, multi-task brain models on 150B neural tokens. Under review
Orhan AE (2024) HVM-1: Large-scale video models pretrained with nearly 5000 hours of human-like video data. arXiv:2407.18067
Orhan AE, Wang W, Wang AN, Ren M, Lake BM (2024) Self-supervised learning of video representations from a child's perspective. CogSci 2024 (oral)
Vong WK, Wang W, Orhan AE, Lake BM (2024) Grounded language acquisition through the eyes and ears of a single child. Science, 383, 504-511. [pdf] [supp]
Orhan AE, Lake BM (2024) Learning high-level visual representations from a child's perspective without strong inductive biases. Nature Machine Intelligence. [preprint]
Davidson G, Orhan AE, Lake BM (2024) Spatial relation categorization in infants and deep neural networks. Cognition, 245, 105690. [preprint]
Orhan AE (2023) Scaling may be all you need for achieving human-level object recognition capacity with human-like visual experience. SSL Workshop @ NeurIPS 2023
Orhan AE (2023) Recognition, recall, and retention of few-shot memories in large language models. arXiv:2303.17557
Orhan AE (2022) Can deep learning match the efficiency of human visual long-term memory in storing object details? arXiv:2204.13061
Orhan AE (2021) How much human-like visual experience do current SSL algorithms need to achieve human-level object recognition? SVRHM Workshop @ NeurIPS 2022
Orhan AE (2021) Compositional generalization in semantic parsing with pretrained transformers. arXiv:2109.15101
Yoon K, Orhan AE, Kim J, Pitkow X (2021) Two-argument activation functions learn soft XOR operations like cortical neurons. arXiv:2110.06871
Orhan AE, Gupta VV, Lake BM (2020) Self-supervised learning through the eyes of a child. NeurIPS 2020 [Press 1] [Press 2] [3-minute summary] [1-hour talk]
Orhan AE, Pitkow X (2020) Improved memory in recurrent neural networks with sequential non-normal dynamics. ICLR 2020 [5-minute summary]
Orhan AE (2019) Robustness properties of Facebook's ResNeXt WSL models. arXiv:1907.07640
Orhan AE, Lake BM (2019) Improving the robustness of ImageNet classifiers using elements of human visual cognition. arXiv:1906.08416
Orhan AE, Ma WJ (2019) A diverse range of factors affect the nature of neural representations underlying short-term memory. Nature Neuroscience, 22, 275–283.
Orhan AE, Pitkow X (2018) Degeneracy, trainability, and generalization in deep neural networks. Integration of Deep Learning Theories Workshop @ NeurIPS 2018
Orhan AE (2018) A simple cache model for image recognition. NeurIPS 2018
Orhan AE, Pitkow X (2018) Skip connections eliminate singularities. ICLR 2018
Orhan AE, Ma WJ (2017) Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback. Nature Communications, 8, 138.
Orhan AE, Ma WJ (2015) Neural population coding of multiple stimuli. Journal of Neuroscience, 35(9), 3825-41.
Orhan AE, Jacobs RA (2014) Are performance limitations in visual short-term memory tasks due to capacity limitations or model mismatch? arXiv:1407.0644
Orhan AE, Jacobs RA (2014) Toward ecologically realistic theories in visual short-term memory research. Attention, Perception, & Psychophysics, 76, 2158-70.
Orhan* AE, Sims* CR, Jacobs RA, Knill DC (2014) The adaptive nature of visual working memory. Current Directions in Psychological Science, 23(3), 164-70.
Orhan AE, Jacobs RA (2013) A probabilistic clustering theory of the organization of visual short-term memory. Psychological Review, 120(2), 297-328.
Orhan AE, Jacobs RA (2011) Probabilistic modeling of dependencies among visual short-term memory representations. NIPS 2011
Orhan AE, Michel MM, Jacobs RA (2010) Visual learning with reliable and unreliable features. Journal of Vision, 10(2):2, 1-15.