Romila Pradhan

Romila Pradhan specializes in cutting-edge techniques for data management and data science, with a strong focus on creating trustworthy and responsible decision-making systems. Her research is particularly centered on the principles of explainability, fairness, and accountability, aiming to enhance the transparency and reliability of machine learning models. As an Assistant Professor in the Department of Computer & Information Technology at Purdue University, she is dedicated to advancing the field through innovative research and teaching. Before joining Purdue University as a faculty member, Dr. Pradhan was a Postdoctoral Researcher at the University of California San Diego, where she contributed to significant projects in data science and machine learning. Her academic journey also includes a tenure as a Visiting Assistant Professor at Purdue University, where she honed her teaching and research skills. Dr. Pradhan's educational background is rooted in a strong foundation in mathematics and computing. She earned her Ph.D. in Computer Science from Purdue University, where she developed her expertise in data management and responsible AI. Her academic pursuits began at the Indian Institute of Technology (IIT) Kharagpur, India, where she completed her B.S. and M.S. in Mathematics and Computing, laying the groundwork for her future research endeavors. Her work is driven by a passion for ensuring that data-driven systems are not only efficient but also ethical and transparent. She is actively involved in projects that address the challenges of bias and accountability in AI, striving to make these technologies more equitable and understandable for all users. In addition to her research, Dr. Pradhan is committed to mentoring the next generation of computer scientists. She is involved in various academic and professional activities that promote diversity and inclusion in the field of technology, encouraging students from diverse backgrounds to pursue careers in data science and AI. Dr. Pradhan's contributions to the field have been recognized through numerous publications in prestigious journals and conferences. Her work continues to influence the development of responsible AI systems, making significant strides towards a more fair and accountable technological future.