Bimal Gaudel
Research Engineer | Scientific Systems & Runtimes
Designing the computational engines that power scientific discovery.
I specialize in the architecture of scientific software. My passion lies in solving the “hard parts” of research computing—designing domain-specific compilers, distributed runtimes, and type-safe abstractions—to bridge the gap between abstract theory and massive parallelism. I thrive in roles that require deep architectural thought and exploratory programming to solve problems standard tools cannot.
Technical Expertise
- Language Design & Architecture: Expert in Modern C++ (17/20/23) for building type-safe, distributed runtimes. Grounded in functional and logic programming principles to create robust, expressive abstractions.
- High-Performance Computing: Designing distributed-memory systems using MPI and TiledArray. Specialized in tensor contraction engines, cache management, and heterogeneous execution models.
- Scientific Software Development: Full-lifecycle development of research software, from Symbolic Algebra engines to Production-grade Runtimes. Proficient in the build orchestration and automation pipelines required for reproducible research software.
Research & Systems Architecture
SeQuant: A Domain-Specific Compiler for Many-Body Physics
SeQuant is a three-stage compiler and runtime system I architected to automate the implementation of advanced quantum chemistry methods. It bridges the gap between abstract mathematical derivations and massively parallel execution, solving the semantic gap in generic frameworks for high-dimensional tensor operations.
- Front-End: Designed a domain-specific mini-language for researcher-driven expression injection, interoperating with core symbolic modules.
- Middle-End: Developed a bespoke Tree-Based IR and graph-theoretic optimization passes (TNCO, CSE) to minimize computational complexity before execution.
- Back-End: Engineered a type-erased result system and reference-counted cache manager for distributed-memory execution via TiledArray.
Impact: SeQuant abstracts hardware-specific complexities, reducing development time from months to days (Gaudel et al., 2025) and enabling the discovery of new physical theories.
Experience
Research Assistant | Virginia Tech 2018 - Present
Architecting high-performance tensor runtimes and automating many-body methods.
Lecturer in Physical Chemistry 2016 - 2018
Taught advanced physical chemistry with a focus on first-principles reasoning.
Education
PhD in Theoretical & Computational Chemistry | Virginia Tech 2018 - 2025
Dissertation: Automated implementation of advanced electronic structure methods
Master of Science in Physical Chemistry | Tribhuvan University 2014 - 2016
Publications
SeQuant (Gaudel et al., 2025)
Introduces a novel color-graph based tensor-network canonicalization approach for the symbolic transformation and runtime evaluation of many-body methods.
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 effective theories compared to complex counterparts (Teke et al., 2024).
- Identification and correction of errors in previously published works (Masteran et al., 2023).