Stephan Eismann

Exploiting conformational dynamics to modulate the function of designed proteins

Optical magnetic detection of single-neuron action potentials using quantum defects in diamond

Recent Advances in Development of Genetically Encoded Fluorescent Sensors

De novo design of modular and tunable protein biosensors

Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution

Integration of optogenetics with complementary methodologies in systems neuroscience

Increasing the penetration depth of temporal focusing multiphoton microscopy for neurobiological applications

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

Chemogenetic Interrogation of a Brain-wide Fear Memory Network in Mice

Improving de novo protein binder design with deep learning

Genetically Encoded Voltage Indicators: Opportunities and Challenges

Multifunctional materials for implantable and wearable photonic healthcare devices

Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA

Time-tagged ticker tapes for intracellular recordings

MgNet: A unified framework of multigrid and convolutional neural network

On some neural network architectures that can represent viscosity solutions of certain high dimensional Hamilton–Jacobi partial differential equations

Genetically Encoded Fluorescent Biosensors Illuminate the Spatiotemporal Regulation of Signaling Networks

Neuropathic Pain: From Mechanisms to Treatment

Physics-informed machine learning

Anti-Stokes excitation of solid-state quantum emitters for nanoscale thermometry

Protein Design with Deep Learning

Photothermal Nanomaterials: A Powerful Light-to-Heat Converter

Geometric deep learning of RNA structure

Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes

Learning Neural PDE Solvers with Convergence Guarantees

High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor