I am a Research Scientist at J. P. Morgan AI Research. My areas of interest include neuro-symbolic AI, integration of planning and acting, scheduling with uncertainty, and applications of AI in finance.
I have worked as a PostDoctoral Researcher in the Department of Computer Science, University of Maryland, College Park. I defended my PhD in Summer 2020. My PhD advisor was Prof. Dana Nau. Prior to this, I did my undergraduate studies at Indian Institute of Technology, Kharagpur and worked as a Software Engineer at Microsoft.
My Ph.D. thesis topic was 'Acting, planning and learning with hierarchical operational models' [link]. It addresses the challenges faced by hierarchically organized actors (that do continual online planning and acting) in dynamic environments. We have developed integrated algorithms that incorporate all three: acting, planning, and learning using a unified representation of hierarchical operational models.
Here is a link to my résumé.
(For full list, please see this link)
 Sunandita Patra, Mark Cavolowsky, Onur Kulaksizoglu, Ruoxi Li, Laura Hiatt, Mark Roberts, Dana Nau. A Hierarchical Goal-Biased Curriculum for Training Reinforcement Learning. FLAIRS. 2022. [paper]
 Sunandita Patra, James Mason, Malik Ghallab, Paolo Traverso, Dana Nau. Deliberative Acting, Online Planning and Learning with Hierarchical Operational Models. Artificial Intelligence (AIJ). 2021. [paper]
 Ruoxi Li, Sunandita Patra, Dana Nau. Decentralized Refinement Planning and Acting. Accepted for publication at ICAPS-21. [paper]
 Sunandita Patra, James Mason, Amit Kumar, Malik Ghallab, Dana Nau, Paolo Traverso. Integrating Acting, Planning, and Learning in Hierarchical Operational Models. ICAPS 2020. Best Student Paper Honorable Mention Award. [paper][poster]
 Sunandita Patra, Malik Ghallab, Dana Nau and Paolo Traverso. APE: An Acting and Planning Engine. Journal of Advances in Cognitive Systems, 2018. [paper]
 Sunandita Patra, Satya Gautam Vadlamudi, and Partha Pratim Chakrabarti. Anytime contract search. SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence 2013. [paper]