Gal Mishne
Associate Professor
Develops graph-based and manifold learning methods for high-dimensional data, with applications to neuroscience imaging.
Gal Mishne's lab at UCSD works on learning theory & optimization, computational neuroscience & cognition and neuroscience & brain-computer interfaces. 46 papers since 2023, 13 at top venues, mostly ICML and AISTATS. 4 PhD students. 20 alumni, most often to Google. Applications close .
At a glance
- papers, 2023–2026
- 12/ year
- at T1 venues
- 28%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 20
Papers by yearfrom the lab homepage, 2023–2026
- 11 papers2026 · T1 1 · collecting
- 13 papers2025 · T1 6
- 13 papers2024 · T1 4
- 9 papers2023 · T1 2
T1 venuesOtherVenues: ICML, AISTATS, ICCV, ICLR, Interspeech
Research focuspaper titles that use each topic's words
- Learning theory & optimization10 papers
- Neuroscience & brain-computer interfaces4 papers
- manifold3 papers
- Computational neuroscience & cognition1 paper
- manifold learning1 paper
Paper list
From the lab homepage.
202611 papers
- UAI (T1)ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis
- Accepted to IEEE EMBCCompositional decoding of neural activity enhances generalization in handwriting BCIs
- Accepted to ICLRCoupled Transformer Autoencoder for Disentangling Multi-Region Neural Latent Dynamics
- [Software]Fast and accessible morphology-free functional fluorescence imaging analysis
- TAG-DSLocal Manifold Explanations with Tangent Space Regression
- Accepted to ICMLMulti-Integration of Labels across Categories for Component Identification (MILCCI)
- Accepted to TMLRMultiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
- SIAM Journal on OptimizationNon-degenerate Rigid Alignment in a Patch Framework
- TAG-DSReassessing Muon for Matrix Factorization
- Nature NeuroscienceThe neurovascular impulse response function differentially reflects intrinsic neuromodulation across cortical regions
- Accepted to AAAIUnsupervised Feature Selection Through Group Discovery
202513 papers
- NeurIPS- workshop on Data on the Brain & Mind FindingsBEHAVE: Behavioral Ethology for Human Assessment via Variational Encoding
- ICML (T1)Elucidating Flow Matching ODE Dynamics with respect to Data Geometries
- KDD (T1)Explaining GNN Explanations with Edge Gradientss
- [code]Graph Laplacian Learning with Exponential Family Noise
- NeurIPS (T1)Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
- Learning on Graphs ConferenceLearning Kronecker-Structured Graphs from Smooth Signals
- NeurIPS- workshop on New Perspectives in Graph Machine LearningMINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning
- SIAM Journal on Scientific ComputingOn a Generalization of Wasserstein Distance and the Beckmann Problem to Connection Graphs
- NeurIPS- workshop on Data on the Brain & Mind FindingsPrototyping Co-Control Brain–Computer Interfaces Through Brain-to-Text
- ICCV (T1)RnGCam: High-speed video from rolling and global shutter measurements
- NeurIPS- workshop on New Perspectives in Graph Machine LearningRobust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
- ICLR (T1)Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
202413 papers
- [psyarxiv]Better together: A systematic review of studies combining magnetic resonance imaging with ecological momentary assessment
- ICML (T1)Comparing Graph Transformers via Positional Encodings
- [code]Contextual Feature Selection with Conditional Stochastic Gates
- [code]Continuous Partitioning for Graph-Based Semi-Supervised Learning
- —Deep and shallow data science for multi-scale optical neuroscience
- IEEE EMBCGuiding Brain-to-Vocalization Decoder Design Using Structured Generalization Error
- AISTATS (T1)Learning Cartesian Product Graphs with Laplacian Constraints
- Neuron (T1)Long-wavelength traveling waves of vasomotion modulate the perfusion of cortex
- Learning on Graphs Conference (LOGOut-of-Sample Extension of Spectral Embeddings: An Optimization Perspective
- SIAM Journal on Matrix Analysis and ApplicationsRandom Walks, Conductance, and Resistance for the Connection Graph Laplacian
- ICML (T1)SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
- —SiBBlINGS: Similarity-driven Building-Block Inference using Neural-Graphs across States
20239 papers
- —Dissection of inter-area interactions of motor circuits
- ICML (T1)Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
- [code]Implicit Graphon Neural Representation
- ICML WorkshopProduct Manifold Learning with Independent Coordinate Selection
- Nature NeuroscienceRapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior
- —Rapid fluctuations in multi-scale correlations of cortical networks encode spontaneous behavior
- —Reliable neural manifold decoding using low-distortion alignment of tangent spaces
- —Semi-supervised quantification and interpretation of undirected human behavior
- ICML (T1)The Numerical Stability of Hyperbolic Representation Learning
Where alumni went20 listed, 33% to industry
Industry 1Academia 2
Most often to
Also to
- Princeton University
- University of Missouri
Apply to UCSDFall 2027
UCSD CSE Computer Science PhD
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- Opens
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- GRE
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- English
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- Fee
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Not yet confirmed for this intake.
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