Engineering Research & Investigations
An overview of active research tracks conducted by Harsh Sharma in collaboration with HMorix Press.
Active Research Domains
AI-Assisted Code Synthesis Guardrails
Evaluating how strict type systems (TypeScript) and compile-time feedback loops prevent hallucinations and regression in generative AI workflows.
OCR & Spatial Document Normalization
Developing spatial clustering algorithms to reconstruct multi-column tabular records from physical document scans with minimal latency.
Published Research Papers
View in Research Archive →Empirical Evaluation of AI-Assisted Workflows in Web Application Development
The integration of Large Language Models (LLMs) into modern web development pipelines presents significant opportunities for developer acceleration alongside novel challenges regarding code correctness, security boundaries, and runtime regressions. This paper explores the impact of strict type systems (TypeScript) acting as automated verification guardrails when paired with AI coding assistants. Through controlled benchmarks across common full-stack development scenarios, we analyze error rates, compilation pass percentages, and maintenance overhead.
High-Throughput Optical Character Recognition & Structural Data Ingestion
Extracting structured data from scanned and photographed physical documents remains a critical bottleneck in digital transformation workflows. This paper analyzes pipeline designs that combine image pre-processing (binarization, deskewing) with deep neural character recognition and post-processing semantic normalization. We propose an adaptive bounding-box cluster algorithm that enhances table structure recovery by 37% over baseline OCR implementations.