Resmi Ramachandranpillai is a Postdoctoral Research Associate at the Institute for Experiential AI. With a background in privacy-preserving synthetic data generation that considers dimensions such as fairness, explainability, utility, and privacy, her research has been applied to bias and discrimination problems in healthcare, computer vision, and more. Resmi’s research revolves around the development of responsible, cutting-edge deep-learning techniques that tackle complex challenges in generative AI. One of her primary focuses lies in designing syntax-agnostic models using Generative Adversarial Networks (GANs) and diffusion models in generating fair synthetic data. Additionally, she specializes in detecting and correcting various biases and ensuring fairness and accuracy in machine learning models.

Prior to joining EAI, she was a postdoctoral fellow in artificial intelligence and integrated computer systems at Linkoping University in Sweden. During that time, she was an active member of TAILOR, the largest network in Europe for Trustworthy Artificial Intelligence, and has contributed to collaborative publications including the Encyclopedia of Trustworthy AI under “Fairness and Equity by Design”. Furthermore, she has demonstrated her commitment to fostering knowledge and skill development by participating in various workshops, summer schools, poster sessions, and international collaborations. She has also guided master’s as well as doctoral students.

Resmi did her Ph.D. in Spiking Neural Optimization at the National Institute of Technology in Tiruchirappalli. Following that, she held a role as an assistant professor at the Indian Institute of Information Technology (IIIT) in Kottayam, India. In that capacity, she instructed graduate, industrial masters, and doctoral students in the fields of machine learning and deep learning.