Rohit Prajapati
Researcher, Shell R&D · PhD Candidate, IIT Jodhpur
I work on high-performance computing: designing parallel and distributed systems that make large-scale computation fast, scalable, and efficient. Building on that, I develop dynamic graph algorithms for real-time workloads on distributed and parallel systems.
At Shell R&D, I build production agentic RAG systems over multi-collection vector stores and optimise high-performance computing for large-scale AI workloads.
- High-performance computing
- AI workload optimisation
- Dynamic graph algorithms
- Model compression
Lately
-
Paper accepted at HiPC 2026 — LayComp: Layer-by-Layer Compression for Transformers.New
-
Presented SAGA at HPDC 2026 in Cleveland, OH.
-
Paper published at EAGE 2026 — E-DALE: End-to-End Domain Adaptation for Large Language Models in the Energy Sector.
-
Paper accepted at HPDC 2026 — SAGA: State-Aware Graph Analytics for Combinatorial Optimization on Dynamic Graphs.
-
Paper accepted at SIGMOD 2026 — PJsim: Towards Precise and Scalable Graph Similarity.
-
Paper accepted at ICDCN 2026 — A Precise and Closed-Form Solution for Edge-Ranking.
-
Joined Shell R&D as Researcher in the Digital & Scientific HPC team.
-
Started PhD at IIT Jodhpur, SPADE Research Lab.
Publications
-
HiPC 2026
LayComp: Layer-by-Layer Compression for Transformers
33rd IEEE International Conference on High Performance ComputingTo appear · Dec 2026 -
HPDC 2026
SAGA: State-Aware Graph Analytics for Combinatorial Optimization on Dynamic Graphs
ACM International Symposium on High-Performance Parallel and Distributed Computing@inproceedings{prajapati2026saga, author = {Prajapati, Rohit and Nijhara, Prajjwal and Banerjee, Dip Sankar}, title = {SAGA: State-Aware Graph Analytics for Combinatorial Optimization on Dynamic Graphs}, booktitle = {Proceedings of the 35th International Symposium on High-Performance Parallel and Distributed Computing}, series = {HPDC '26}, pages = {430--444}, year = {2026}, address = {Cleveland, OH, USA}, publisher = {ACM}, doi = {10.1145/3806645.3807595} } -
EAGE 2026
E-DALE: End-to-End Domain Adaptation for Large Language Models in the Energy Sector
87th EAGE Annual Conference & Exhibition@inproceedings{sarhan2026edale, author = {Sarhan, Injy and Singh, Avanindra and Vincent, Lalson and Nakhate, Yogesh and Sand, Mudit and Stamatiou, Eirini and Prajapati, Rohit and Ovcharenko, Oleg and Sudakov, Oleg and Broggini, Filippo and Desai, Sagar and Hohl, Detlef}, title = {E-DALE: End-to-End Domain Adaptation for Large Language Models in the Energy Sector}, booktitle = {87th EAGE Annual Conference \& Exhibition}, year = {2026}, address = {Aberdeen, UK}, publisher = {European Association of Geoscientists \& Engineers}, doi = {10.3997/2214-4609.2026101329} } -
SIGMOD 2026
PJsim: Towards Precise and Scalable Graph Similarity
Proceedings of the ACM on Management of Data, Vol. 4, No. 3@article{nijhara2026pjsim, author = {Nijhara, Prajjwal and Tandel, Jainan and Prajapati, Rohit and Banerjee, Dip Sankar}, title = {PJsim: Towards Precise and Scalable Graph Similarity}, journal = {Proceedings of the ACM on Management of Data}, volume = {4}, number = {3}, pages = {1--25}, year = {2026}, publisher = {ACM}, doi = {10.1145/3802100} } -
ICDCN 2026
A Precise and Closed-Form Solution for Edge-Ranking
International Conference on Distributed Computing and Networking@inproceedings{nijhara2026edgeranking, author = {Nijhara, Prajjwal and Tandel, Jainan and Prajapati, Rohit and Banerjee, Dip Sankar}, title = {A Precise and Closed-Form Solution for Edge-Ranking}, booktitle = {Proceedings of the 27th International Conference on Distributed Computing and Networking}, series = {ICDCN '26}, pages = {138--142}, year = {2026}, address = {Nara, Japan}, publisher = {ACM}, doi = {10.1145/3772290.3772316} }