Rishabh
Lingam

Jan 2026 — Present

• —Built real-time object detection and spatial awareness pipeline for robotic prototypes using OpenCV and MediaPipe, supporting field trial deployments.
• —Designed and delivered hands-on AI engineering labs covering computer vision, sensor integration, and applied ML for student cohorts.
• —Mentored students through full engineering cycles from problem scoping, prototyping, testing, and iteration within a professional workflow environment.

Oct 2025 — Dec 2025

• —Evaluated LLM agent outputs for factual accuracy, contextual relevance, and safety compliance. Contributed structured feedback to model improvement cycles.
• —Engineered domain-specific prompts to improve LLM accuracy across specialized tasks, applying NLP grounded strategies that measurably reduced hallucination rates.
• —Designed evaluation rubrics and automated workflows to detect hallucinations, rogue behaviors, and factual inconsistencies at scale.

Apr 2024 — Apr 2025

• —Identified that 17.6% of newly diagnosed HIV patients nationally fail to link to care within 30 days, built an LLM based contrastive learning framework to predict ED patient testing refusal before care opportunities are missed.
• —Normalized 63,874 noisy ICD-based diagnosis descriptions using LLM-assisted text standardization, reducing lexical variability and improving minority-class model robustness.
• —Trained BioClinicalBERT with supervised contrastive pretraining to cluster outcome-similar encounters, outperformed Random Forest and fine-tuning baselines by up to 9.7% accuracy.
• —Validated model via stratified 10-fold cross-validation across 6 hospitals, producing deployment-ready refusal risk scores to prioritize patients for care navigator intervention.
• —Collected and annotated 5,064 student essay sentences across 7 argumentation categories, developed context aided, POS-augmented, and distribution-aware hierarchical BERT models that improved F1 for severely underrepresented minority classes (Reasoning: 0 to 0.366, Thesis: 0 to 0.307).

Jul 2022 — Jun 2023

• —Automated SQL-based reporting workflows via Python scripts, integrating output into production data pipelines and reducing recurring analyst workload.
• —Performed EDA on client datasets using Pandas and NumPy, surfaced data quality issues and communicated statistical findings to stakeholders for downstream reporting validation.
• —Deployed analytics workflows using Docker and Kubernetes orchestration, supporting reliable and reproducible delivery of data pipeline outputs in production.

2025

GPA: 3.96

M.S. · Artificial Intelligence

Florida Atlantic University

2022

GPA: 7.28

B.Tech. · Electronics and Communication Engineering

Malaviya National Institute of Technology