Chinmay Hegde

Chinmay Hegde is an Associate Professor in the Electrical and Computer Engineering Department at NYU Tandon School of Engineering. His research interests include Machine Learning, Algorithms, Big Data, Signal and Image Processing. Hegde is affiliated with the Visualization Imaging and Data Analysis Center (VIDA) and has contributed to research on AI models for imaging, materials design, and transportation. His work has focused on identifying weaknesses in current AI models and developing techniques for tasks such as altering apparent ages in facial images while retaining identifying features.

Chinmay Hegde is a researcher at New York University with a focus on artificial intelligence. His work explores the intersection of machine learning and signal processing, particularly in the areas of compressive sensing, neural networks, and deep learning. Hegde's research includes the development of model-based compressive sensing techniques, the analysis of neural networks' performance on tabular data, and the design of benchmarks for large language models. His publications also address challenges in adversarial attacks, graph-structured sparsity, and inverse imaging problems. Hegde's contributions emphasize the theoretical foundations and practical applications of AI in complex data scenarios.