Anmol Wadhwa

Applied agile methodologies and coding standards for efficient code development. Led the end-to-end production of AI solutions, translating business needs into data-driven models. Enhanced data pipeline efficiency using PySpark, SQL, and Azure Dataflow.

Expertise in diverse ML algorithms, specializing in Image Detection, NLP, Anomaly Detection in Timeseries. Proficient in end-to-end data processing using tools like Pytorch, Pyspark, Hugging face Libraries. Hands on fine-tuning of large language models (BERT, Roberta, GPT) and experience in NLP applications like Semantic Web Analysis, Sentiment Analysis, Text to Text conversion etc, contributing to impactful solutions. Key responsibilities: Developed a graph-based recommendation system utilizing linked prediction techniques, optimizing user engagement with personalized content suggestions. Contributed to driver safety with an advanced drowsiness detection solution, using machine learning for real-time monitoring, and engaged in cross-disciplinary collaboration to align project objectives with data-driven strategies.

Published my Research work on Driver Drowsiness Detection in Elsevier. Published a research paper on a Graph-based Recommendation system at the SITE conference held at VIT.