Publications - Theses

    2025

  1. Sparse representations in artificial and biological neural networks. Trenton Bricken. Harvard University (2025). PDF

  2. Beyond modalities: robust neural representation of language in the brain. Shreyas Krishnan. Birla Institute of Science and Technology (2025). PDF

  3. Mitigating catastrophic forgetting and mode collapse in text-to-image diffusion via latent replay. Aoi Otani. Harvard University (2025). PDF

  4. 2024

  5. Out-of-distribution generalization in biological and artificial intelligence. Spandan Madan. Harvard University (2024). PDF

  6. Robust and multimodal signals for language in the brain. Pranav Misra. Harvard University (2024). PDF

  7. Adding to and building up very small nervous systems. Chenguang Li. Harvard University (2024). PDF

  8. Testing the alignment of multimodal neural networks models to human brain areas. Narek Alvandian. Ecole Polytechnique Federale de Laussane (EPFL) (2024). PDF

  9. The pen and the processor: A Turing-like test to gauge GPT-generated poetry. Deni Bechard. Harvard University (2024). PDF

  10. Robust convolutional neural networks as models of primate vision. Bastien LeLan. EPFL (2024). PDF

  11. Alignment of large language models and brain activity: exploring language processing through sEEG in a multimodal syntactic task. Victor Gillioz. ETH (2024). PDF

  12. Classifying Ragams in Carnatic Music with Machine Learning Models: A Shazam for South Indican Classical Music. Hari Narayanan. Harvard University (2024). PDF

  13. Towards Characterizing Curriculum Reinforcement Learning in Sparse Robotics Tasks. Thomas Kaminsky. Harvard University (2024). PDF

  14. 2023

  15. Hebbian attractor to model working memory in complex human behavior. Ravi Srinivasan. ETH (2023). PDF

  16. Bridging artificial and primate vision: the impact of visual angle, scene context, and IT-alignment. Sara Djambazovska. Ecole Polytechnique Federale de Laussane (EPFL) (2023). PDF

  17. A data-driven description of sleep using intracranial EEG recordings. Alexander Luster. Ecole Polytechnique Federale de Laussane (EPFL) (2023). PDF

  18. Unveiling Principles of Neural Computations: From Biological to Artificial Intelligence, and Back. Giorgia Dellaferrera. ETH (2023). PDF

  19. Synaptic failure is a flat minima optimizer. Deepak Singh. Harvard University (2023). PDF

  20. Less than reckless: assessing the role of consciousness in the moral appraisal of risky action. Ilai Gavish. Harvard University (2023). PDF

  21. 2022

  22. Seeing context: macaque ventral visual responses to diverse stimuli and during natural vision. Wu Xiao. Harvard University (2022). PDF

  23. Neural mechanisms underlying human cognitive control and working memory. Yuchen Xiao. Harvard University (2022). PDF

  24. On structured domain generation for generalization in reinforcement learning. Serena Bono. ETH (2022). PDF

  25. An intracranial EEG study on human short-term memory. Paula Lopez Sanchez. Ecole Polytechnique Federale de Lausanne (EPFL) (2022). PDF

  26. Dynamically Decoding Human Physiological Behviors from Intracranial Field Potentials. Manana Hakobyan. Harvard University (2022). PDF

  27. Neuronal correlates of rapid learning in a human visual memory task. Camille Gollety. Ecole Polytechnique Federale de Lausanne (EPFL) (2022). PDF

  28. Biologically-inspired deep predictive learning for episodic memory event segmentation. Zergham Ahmed. Harvard University (2022). PDF

  29. Classification of Continuous Natural Human Behavior Using Intracranial Field Potential. Jay Chandra. Harvard University (2022). PDF

  30. Comparing neural responses between action execution and action perception. Yael Porte. Ecole Polytechnique Federale de Laussanne (EPFL) (2022). PDF 

  31. An integrated computational models of visual search combining eccentricity, bottom-up, and top-down cues. Shashi Kant Gupta. India Institute of Technology Kanpur (2021). PDF

  32. 2021

  33. Mesoscopic physiological interactions in the human brain reveal small-world properties and associations with behavior. Jiarui Wang. Harvard University (2021). PDF

  34. Efficient and insidious adversaries in deep reinforcement learning. Stephen Casper. Harvard University (2021). PDF

  35. Context-robust object recognition via object manipulation in a synthetic 3D environment. Dimitar Karev. Harvard University (2021). PDF

  36. Movies and Memory: How Film Editing Can Impact Episodic Memory Formation. Jake Schwencke. Harvard University (2021). PDF 

  37. Combining neurophysiology and computational modeling through VGG19. Leonardo Pollina. Ecole Polytechnique Federale de Lausanne (EPFL) (2021). PDF 

  38. 2020

  39. Recognition of minimal images in the human brain. Aurelie Cordier. Ecole Nationale Superieure de Physique, Electronique, Materieux (2020). PDF

  40. 2019

  41. Plasticity and Firing Rate Dynamics in Leaky Integrate-and-Fire Models of Cortical Circuits. Joseph Olson. Harvard University (2019). PDF

  42. Computational Models of Bottom-up and Top-down Attention. Mengmi Zhang. National University of Singapore (2019). PDF

  43. Turing's Child Machine: A Deep Learning Model of Neural Development. Duncan Stothers. Harvard University (2019). PDF

  44. Movement-Related Characteristics of Mirror Neuron Activity in Humans and Monkeys. Alice Motschi. Ecole Polytechnique Federale de Lausanne (EPFL) (2019). PDF

  45. Human vision versus computer vision to classify simple actions. Vincent Jacquot. Ecole Polytechnique Federale de Lausanne (EPFL) (2019). PDF

  46. 2018

  47. Neural circuits of visual pattern completion. Matthias Tsai. Ecole Polytechnique Federale de Lausanne (EPFL) (2018). PDF

  48. Learning Scene Gist to Improve Object Recognition in Convolutional Neural Networks. Kevin Wu. Department of Engineering and Applied Sciences, Harvard University, (2018). PDF

  49. Spike-field coherence reveals complex cortical interactions in human visual memory task. Stephan Grzelkowski. University of Amsterdam (2018). PDF

  50. Twenty-Four Hours in the Human Brain. Eleonora Iaselli. Ecole Polytechnique Federale de Lausanne (EPFL) (2018). PDF

  51. 2017

  52. Prediction as a Rule for Unsupervised Learning in Deep Neural Networks. William Lotter. Harvard University (2017). PDF

  53. Behavioral and computational study on the recognition of novel occluded objects. Charlotte Moerman. Ecole Polytechnique Federale de Lausanne (EPFL) (2017). PDF

  54. 2016

  55. The Volitional (In)significance of Neuroscience: What Libetian Investigations Can and Cannot Do for Free Will. Garrett Lam. Harvard University (2016). PDF

  56. Brain-inspired Recurrent Neural Algorithms for Advanced Object Recognition. Martin Schrimpf. Tehnische Universitat Munchen (2016). PDF

  57. Quantifying episodic memories from real-world experience. Alyssa Marconi. Emmanuel College, (2016). PDF

  58. 2015

  59. Role of recurrent computations in object completion. Hanlin Tang. Harvard University (2015). PDF

  60. Predicting episodic memories for movie events. Sarah Dowcett. Emmanuel College, (2015). PDF

  61. 2014

  62. The functional neuroanatomy of speech perception. Philipp Kunhnke. University of Osnabruk, Germany, (2014). PDF

  63. 2001

  64. On the neuronal activity in the human brain during visual recognition, imagery and binocular rivalry. Gabriel Kreiman. Department of Biology, California Institute of Technology (2001). ABSTRACT PDF

  65. Neural coding and feature extraction of time varying signals. Gabriel Kreiman. Computation and Neural Systems Program, California Institute of Technology (2001). ABSTRACT PDF

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