About Bimal – Gaudel's Miscellany

Bimal Gaudel

Staff Research Engineer | Functional Systems Architect

Architecting composable systems where high performance meets structural correctness.

I am a Research Engineer specializing in the intersection of abstract mathematics, functional programming, and high-performance computing. I design software architectures that are robust by definition—building scalable, modular, and correct-by-construction systems grounded in algebraic principles.

Education

PhD in Theoretical & Computational Chemistry

Virginia Tech

Technical Contributions

Automating Scientific Development

Deriving and implementing many-body methods is historically error-prone; researchers often spend more time debugging C++ than exploring physics.

flowchart LR
    A[Raw Math Equations] -->|Symbolic<br/>Transformation| B{Compiler<br/>Engine}
    B -->|Code<br/>Generation| C[Optimized C++]
    style A fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
    style B fill:#fff9c4,stroke:#fbc02d,stroke-width:2px
    style C fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px

Figure 1: The Automated Pipeline: Transforming raw equations into optimized code.

I co-designed a system that automates this entire lifecycle. By treating method implementation as a symbolic algebra problem, the system performs sound algebraic rewrites on computation graphs.

Productivity: Reduces development time from months to days.
Correctness: Ensures results are mathematically sound through rigorous graph transformations.
Capability: Enables the exploration of previously infeasible complex methods.

SeQuant: Scalable Tensor Runtime

To support this automation, I architected SeQuant, a runtime system leveraging TiledArray for distributed-memory tensor computation.

flowchart TD
    Math[Mathematical Definition] --> Bridge{SeQuant<br/>Runtime}
    subgraph HW [Heterogeneous Hardware]
        direction LR
        L[Laptop] --- C[HPC Cluster]
    end
    Bridge --> HW
    style Math fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
    style Bridge fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style HW fill:#fafafa,stroke:#9e9e9e,stroke-dasharray: 5 5
    style L fill:#fff,stroke:#333
    style C fill:#fff,stroke:#333

Figure 2: Decoupled Architecture: Bridging abstract math and hardware.

By enforcing strong abstractions, SeQuant decouples mathematical definitions from hardware execution, ensuring:

Scalability: Seamless execution from laptops to HPC clusters without code changes.
Extensibility: A modular design capable of adopting new backends as hardware evolves.
Collaboration: A shared infrastructure facilitating global code reuse.

Publications

SeQuant (Gaudel et al., 2025)

Describes a novel color-graph based tensor-network canonicalization approach for the symbolic transformation and runtime evaluation of many-body methods. The system follows a modern three-stage compiler design:

Front End: Generating equations for many-body methods.
Middle End: Intermediate representation (IR) & symbolic transformation.
Back End: Online interpretation and execution.

Applied Research Enabled by SeQuant

Theoretical exploration of new ansatze in explicitly correlated methods (Masteran et al., 2025).
Geminal parameter tuning in explicitly correlated methods (Powell et al., 2025).
Discovery of simpler, more effective theories compared to complex counterparts (Teke et al., 2024).
Identification and correction of errors in previously published works (Masteran et al., 2023).

References

Gaudel, B., Adam, R. G., Melekamburath, A., Masteran, C., Teke, N., Besharatnik, A., Köhn, A., & Valeev, E. F. (2025, November 13). SeQuant framework for symbolic and numerical tensor algebra. I. Core capabilities. https://doi.org/10.48550/arXiv.2511.09943

Masteran, C., Gaudel, B., & Valeev, E. F. (2025). Toward a balanced description of ground and excited states with transcorrelated F12 methods. Journal of Chemical Theory and Computation, 21(20), 10329–10339. https://doi.org/10.1021/acs.jctc.5c01434

Masteran, C., Kumar, A., Teke, N., Gaudel, B., Yanai, T., & Valeev, E. F. (2023). Comment on “canonical transcorrelated theory with projected slater-type geminals” [J. Chem. Phys. 136, 084107 (2012)]. Journal of Chemical Physics, 158(5), 57101. https://doi.org/10.1063/5.0135257

Powell, S. R., Surjuse, K. A., Gaudel, B., & Valeev, E. F. (2025). Slimmer geminals for accurate F12 electronic structure models. Journal of Chemical Theory and Computation, 21(18), 8833–8842. https://doi.org/10.1021/acs.jctc.5c00971

Teke, N. K., Melekamburath, A., Gaudel, B., & Valeev, E. F. (2024). “Best” iterative coupled-cluster triples model? More evidence for 3CC. Journal of Physical Chemistry A, 128(45), 9819–9828. https://doi.org/10.1021/acs.jpca.4c04667