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Explore university research

Explore university research.
Learn the science behind it.

Discover labs, professors, papers and research questions across universities. Then follow short adaptive learning paths that give you the background to understand their work.

Neural circuits Regenerative medicine Computational neuroscience Cortical organoids Tissue engineering

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Universities

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Labs & professors

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Research questions

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5 university · 10 labs currently mapped
An independent educational collection

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California Institute of Technology

1 research group · 1 research series currently mapped

Active matter Allostery Bacteriophages Biological fidelity Biological numeracy

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Harvard University

1 research group · 1 research series currently mapped

Black-hole entropy BPS states Calabi–Yau manifolds Cosmology Dark dimension

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Stanford University

6 research groups · 6 research series currently mapped

Adaptation Adaptive DBS Angiogenesis B-cell repertoire Basal ganglia

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University of California, Berkeley

1 research group · 1 research series currently mapped

Action chunking Autonomous robot learning Behavioral cloning Cross-embodiment learning Deep reinforcement learning

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Weizmann Institute of Science

1 research group · 1 research series currently mapped

Biological design principles Bistability Diabetes Dynamical compensation Dynamical systems

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Questions worth exploring

Featured labs

Stanford University

Bronte-Stewart Lab

Helen Bronte-Stewart

Human Motor Control and Neuromodulation Laboratory: linking quantitative movement measurements with implanted subthalamic local field potentials and neuromodulation to understand Parkinson’s disease and develop personalized adaptive therapies.

Adaptive DBS Parkinson’s disease Basal ganglia Beta bursts Beta oscillations

5 lessons · ~27 minutes

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Harvard University

Cumrun Vafa Research Group

Research using string theory, geometry, duality, black-hole physics and quantum-gravity consistency to understand which effective theories can arise from quantum gravity and what those constraints might imply for particle physics and cosmology.

Dark dimension Quantum gravity String theory Swampland Black-hole entropy

7 lessons · ~37 minutes

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Stanford University

Karl Deisseroth Lab

Karl Deisseroth

Controlling, mapping and modeling neural circuits across cell types, space and behavior.

Neural circuits Optogenetics Calcium imaging CLARITY Cortical organoids

9 lessons · ~48 minutes

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Stanford University

Michelle Monje Lab

Research at the intersection of neurodevelopment, glioma biology, neural activity, tumor microenvironment signaling, cancer neuroscience, and mechanism-guided therapies.

Cancer biology Cancer neuroscience Cancer-treatment-related cognitive impairment CAR T-cell therapy Cholinergic signaling

9 lessons · ~50 minutes

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Stanford University

Ngan F. Huang Lab

Cells, matrices and engineered environments for vascular and muscle regeneration.

Regenerative medicine Angiogenesis Biomaterials Endothelial cells Extracellular matrix

6 lessons · ~46 minutes

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California Institute of Technology

Rob Phillips Physical Biology Laboratory

Research using quantitative experiments, statistical mechanics, information theory, nonequilibrium physics, and large-scale biological measurements to discover predictive principles in gene regulation, biological fidelity, active matter, and viral ecology.

Active matter Allostery Bacteriophages Biological fidelity Biological numeracy

6 lessons · ~29 minutes

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Explore by topic

Action chunking Active matter Adaptation Adaptive DBS Allostery Angiogenesis Autonomous robot learning B-cell repertoire Bacteriophages Basal ganglia Behavioral cloning Beta bursts Beta oscillations Bioengineering Biological design principles Biological fidelity Biological numeracy Biomaterials Biophysics Bistability Black-hole entropy BPS states Bradykinesia Calabi–Yau manifolds Calcium imaging Cancer biology Cancer neuroscience Cancer-treatment-related cognitive impairment CAR T-cell therapy Cell atlases Cell-free DNA Cell-free RNA Cholinergic signaling CLARITY Coarse-graining Collective dynamics Computational neuroscience Cortical organoids Cosmology Cross-embodiment learning CSPG4 Cytoskeleton Dark dimension Dark energy Dark matter Deconvolution Deep brain stimulation Deep reinforcement learning Diabetes Diffuse midline glioma Diffusion models DIPG Distance Conjecture DNA sequencing Duality Dynamical compensation Dynamical systems Effective field theory Electroencephalography Electrophysiology Embodied AI Endothelial cells Error correction Extra dimensions Extracellular matrix F-theory Feed-forward loops Feedback control Fiber photometry Fibrosis Flow matching Freezing of gait GABAergic signaling Gait GD2 Gene regulation Gene regulatory networks Generative policies Genomic diagnostics Genomics Glial biology Glioma Glutamatergic signaling Goal-conditioned reinforcement learning Gompertz law Grand unification H3K27 alteration Hallmarks of Cancer Hierarchical robot control Hormone regulation Human virome Imitation learning Immune repertoire sequencing Inertial measurement units Inflammation Information theory Interpretable machine learning Kaluza–Klein theory Kinematics Kinetic proofreading Liquid biopsy Local field potentials Machine learning Massively parallel reporter assays Mechanobiology Mechanotransduction Metagenomics Microbial ecology Microbiome Microfluidics Microgravity Microtubules Moduli space Molecular counting Molecular motors Movement disorders Multielectrode arrays Network motifs Neural biomarkers Neural circuits Neural coding Neural decoding Neural network models Neural population dynamics Neurodevelopment Neuroligin-3 Neuromodulation Neuron-to-glioma synapses Nonequilibrium biology Noninvasive prenatal testing Object motion Offline reinforcement learning Offline-to-online learning Oligodendrocyte precursor cells Optogenetics Parkinson’s disease Patch clamp Pediatric brain cancer Periodic Table of Diseases Personalized neuromodulation Physical biology Physiological circuits PIEZO1 Predictive coding Predictive medicine Prenatal genomics Promoters Quantitative biology Quantitative digitography Quantum gravity Quantum-gravity phenomenology Real-world reinforcement learning Reg-Seq Regenerative medicine Regulatory DNA Regulatory genomics Reinforcement learning Representation learning Retina RNA sequencing Robot foundation models Robot learning Robot manipulation Robot planning Robotics Robustness Saturated removal model Senescence Simple repression Single-cell genomics Single-cell RNA sequencing Single-molecule measurement Skeletal muscle engineering Spatial proteomics Spatial transcriptomics Species scale STARmap Statistical evidence Statistical mechanics Stem-cell-derived vascular cells String compactification String landscape String theory Subthalamic nucleus Supersymmetry Swampland Synaptic plasticity Systems aging Systems biology Systems medicine Systems neuroscience T-cell receptor repertoire Tabula Sapiens Tissue clearing Tissue dynamics Tissue engineering Topological string theory Transcription factors Transcriptomics Transplant monitoring Tumor evolution Tumor heterogeneity Tumor microenvironment Ultrasound neurostimulation UV completion Vascular regeneration Viral ecology Viral genomics Vision-language models Vision-language-action models Visual neuroscience Visuomotor learning Xenocortication Xenotransplantation

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Decode Life: AI & Computational Biology

Build Python, data-analysis and biological-modeling skills used across research fields.

35 lessons · Skills used across many research fields

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How Socratic Learn works

Don't just finish a lesson. Understand it.

Research gives your learning a direction. Concept checks reveal what needs another pass, and targeted remediation helps you build understanding before moving on.

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Test your understanding
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Socratic Learn is an independent educational resource. The universities and labs described here have not endorsed these primers or project ideas.