SGSikao Guo
Contact

Computational biophysics × scientific computing

I develop computational methods and reusable software for understanding biomolecular systems across scales.

Computational biophysicist developing methods for protein conformational sampling, biomolecular self-assembly, structural bioinformatics, and scalable simulation.

Protein sampling · Molecular simulation · HPC · Scientific software

Explore research GitHub CV

U.S. Permanent Resident · Open to Research Scientist / Research Engineer opportunities

Sampled protein backbone conformations.01 / Current researchProtein conformational samplingInverse kinematics · SE(3) · all-atom validation

Research vision

How can we explore biomolecular conformational space efficiently, scalably, and reproducibly?

My long-term goal is to develop fast algorithms and reusable computational infrastructure that connect molecular geometry, statistical mechanics, structural data, and scalable simulation.

01

Efficient conformational sampling

Explore flexible proteins, loops, and disordered regions without relying exclusively on long-timescale molecular dynamics.

Inverse kinematics · SE(3) · geometric sampling · OpenMM
02

Multiscale molecular modeling

Connect atomic structure, conformational ensembles, intermolecular interactions, and emergent mesoscale assembly.

Reaction–diffusion · stochastic simulation · self-assembly
03

Research infrastructure

Turn new algorithms into validated, scalable, reusable systems rather than one-off research code.

C++ · Python · MPI · reproducible workflows

Selected work

One research direction, developed across methods, models, and software.

Four case studies trace the path from scientific question to validated algorithm, scalable simulation, and reusable infrastructure.

Sampled protein backbone conformations.Ongoing work
Research2026 – Present

Protein backbone sampling

Algorithms · C++ · structural validation

An extension of tripeptide loop-closure sampling that releases terminal constraints, introduces SE(3) motions and shifted sampling frames, and couples broad backbone geometric exploration to all-atom structural validation.

ContributionExtended and optimized the C++ sampler and built its all-atom validation workflow.

  • C++
  • Inverse kinematics
  • SE(3)
  • Hit-and-Run
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Conceptual path from particle-based reaction–diffusion models to parallel NERDSS simulation.Open source
Research infrastructure2022 – 2025

NERDSS + ioNERDSS infrastructure

Structure → simulation → scalable HPC

A connected software stack that transforms PDB or mmCIF structures into simulation-ready coarse-grained models and runs explicit particle-based reaction-diffusion and self-assembly at larger spatial and computational scales.

ContributionCo-developed ioNERDSS and led the MPI design, implementation, validation, and benchmarking for NERDSS.

PaperioNERDSS preprintPaperMPI paperCodeioNERDSS repository
  • C++
  • Python
  • MPI
  • PDB/mmCIF
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Eight simulation snapshots showing membrane-associated assemblies growing as molecular concentration increases, above a stylized membrane.Published
Research2020 – 2024

Biomolecular assembly models

Clathrin · HIV Gag · dynamin

Structure-resolved stochastic and kinetic models of clathrin lattices, HIV-1 Gag assembly, and dynamin recruitment that integrate experimental constraints and produce testable system-level predictions.

ContributionDesigned and analyzed the clathrin and HIV-1 models and contributed quantitative modeling to collaborative studies.

PaperClathrin assembly paperPaperHIV-1 lattice paperPaperDynamin nanocluster paper
  • NERDSS
  • Stochastic simulation
  • Kinetic modeling
  • Membranes
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Diagram showing a Qt interface and CLI metadata transformed into JSON and then into VMD, PyMOL, and web applications.Open source
Software2025 – 2026

Cross-platform GUI generation

Interfaces · code generation · scientific software

A Python framework that converts a designed interface and CLI metadata into a validated, platform-independent JSON specification, then generates consistent scientific applications for desktop molecular viewers and web environments.

ContributionDesigned the framework architecture and implemented the specification, validation, and platform generators.

PaperFramework preprintCodeAutoCLIP repositoryDocumentationDocumentation
  • Python
  • Qt
  • JSON Schema
  • VMD
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Explore research and software

Measured impact

Results that hold up beyond the prototype.

≈90× speedup

MPI NERDSS on 96 CPUs

44,000+ structures

ioNERDSS benchmarking across the PDB

9 applications · 3 platforms

One specification to VMD, PyMOL, and web

Selected publications

Evidence across molecular modeling and scientific computing.

Selected work is ordered by research relevance; the full publication page remains chronologically filterable.

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About

Physics → computational biophysics → scientific computing.

I develop quantitative models of molecular systems, then build the algorithms and software required to test, scale, and share them.

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Now

Research Engineer · Inria

Protein conformational sampling and reusable cross-platform scientific interfaces.

2020–25

Johns Hopkins University

Biomolecular self-assembly, NERDSS-MPI, and structure-to-simulation workflows.

Foundation

Ph.D. in Physics

Quantitative molecular models connecting microscopic transitions to emergent motion.

Collaborate

Interested in computational molecular science?

I am interested in collaborations and research opportunities involving molecular modeling, conformational sampling, scientific computing, and reusable research infrastructure.

Email me View CV