Ankit Agrawal

Graph Neural Network, Hybrid Quantum Machine Learning, Quantum Computing. Large Language Models, Natural Language Processing. Delivered precise and efficient models (Mesh Graph Networks, GCN, GAT, Quantum‐ML) to TRUMPF GmbH + Co. for heat simulation, aiding in the identification of critical samples and reducing their error rate. • Addressed challenges in heat transfer simulations by generating synthetic data for laser‐cutting through Finite Element Methods (FEM), enhancing data‐driven modeling.

• Built a Business model recommendation system to help companies improve their products and underlying business model, along with identifying potential threats. • Developed a novel aspect‑based sentiment analysis model and zero‑shot multilingual RoBERTa classification model for analysis of customer reviews extracted from various e‑commerce websites and Twitter. • Implemented end‑to‑end prototype including crawlers, models training, deployment to production, back‑end APIs and database server hosting.

• Research on efficient and adaptive dense correspondence matching module for detection & segmentation of objects in videos. • Achieved state‑of‑the‑art results in YOUTUBE‑VOS, DAVIS and TAO‑VOS benchmarks for Video Object Segmentation task. • End‑to‑end implementation of distributed GPU training pipeline for self‑supervised learning methods and evaluation against state‑of‑the‑art models.

• Ownership of design and development, whilst leading the team of a new intelligent trade booking life‑cycle platform which assisted stakeholders to book trade 5x faster and increased performance by 30%. • Enhanced trade forecasting systems performance to optimize the report generation time by 60% using efficient data structures and SQL queries to remove redundancy and time complexity. • Mentored 15 graduates and interns and coordinated various workshops on Agile Methodologies, Clean Coding Practice, Git.

Led the design & development of a new trade booking life‐cycle platform, enabling stakeholders to book trades 5x faster & achieving a 30% performance enhancement. Optimized trade forecasting systems, reducing report generation time by 60% by leveraging efficient data structures & refining SQL queries to minimize redundancy & time complexity. Mentored 6 new graduates and interns, & organized workshops on Agile Methodologies, Clean Coding Practice, Code Reviews, and Git, enhancing team skills and productivity

• Research Area: Deep Learning, Machine Learning, Computer Vision, Image/Video Understanding, Natural Language Processing.

• Courses: Data Structures and Algorithms, Database Management Systems, Computer Programming, Artificial Intelligence.