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Harshverdhan SoniHS
Open to opportunities

Harshverdhan Soni

@harshverdhansoni

I build generative AI and full-stack systems—delivering multimodal, multilingual RAG and agentic AI for government-scale impact.

India
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What I'm looking for

I’m looking to join teams that build deployable generative AI for public-sector impact—combining multilingual RAG/GraphRAG and agentic systems with strong engineering ownership and measurable real-world outcomes.

I’m an applied AI researcher and full-stack engineer with “12+ years” across AI/ML research, “government digital transformation,” and “Java full-stack development.” As a PhD Scholar in Generative AI at NIT Silchar and a Technical Assistant at C-DAC Silchar (MeitY, Government of India), I specialise in multimodal-multilingual Retrieval-Augmented Generation and agentic AI for Indian-language and public-sector systems.

My research includes “GCP-GraphRAG: A Multimodal Multilingual Graph-Based RAG with Graph Context Pruning” (accepted at GCON 2026, IEEE) and “GNN-driven relevance propagation” for token-efficient, provenance-aware generation in low-resource Indian languages. I also led real deployments—coordinating HMIS rollout across Arunachal Pradesh and Sikkim, scaling from “93 to 132+ healthcare facilities,” and building integration APIs for HMIS (including stock-position, patient-details, and EDL pipelines). Alongside AI, I delivered end-to-end Java full-stack modules (Spring Boot, ReactJS) across eHRMIS/DVDMS and other government platforms, while automating workflows using MCP Server, n8n, and Make to accelerate delivery.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

National Institute of Technology Silchar logoNS

National Institute of Technology Silchar

Doctor of Philosophy (PhD), Artificial Intelligence / Machine Learning (Generative AI)

Grade: GPA 7.5

Activities and societies: Focus: Multimodal-Multilingual RAG, GCP-GraphRAG, GNN, Explainable AI.

PhD scholar in AI/ML (Generative AI) focusing on multimodal-multilingual RAG and GCP-GraphRAG with explainable AI. Research includes agentic AI for Indian-language and public-sector systems.

National Institute of Technology Calicut logoNC

National Institute of Technology Calicut

Master of Technology (M.Tech), Computer Science & Engineering

Grade: GPA 7.0

M.Tech in Computer Science & Engineering with research interests in AI/ML foundations. GPA noted as 7.0.

SR

Shri Sai Institute of Technology, Ratlam

Master of Computer Applications (MCA), Computer Applications

Grade: GPA 8.01

MCA (Master of Computer Applications) from Shri Sai Institute of Technology, Ratlam. GPA noted as 8.01.

RR

Royal Institute of Technology & Mgmt, Ratlam

Bachelor of Computer Applications (BCA), Computer Applications

Grade: 70.6%

BCA (Bachelor of Computer Applications) from Royal Institute of Technology & Management, Ratlam. Graduation score noted as 70.6%.

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