Pavithra Sripathanallur Murali

Senior Research Scientist @Symbotic

Boston, MA, US
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Apr 2026 — Present

Senior Research Scientist @Symbotic

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Wilmington, MA, US

EDUCATION

N/A

George Mason University

Doctor of Philosophy - PhD, Systems Engineering & Operations Research

2013 — 2017

Anna University Chennai

Bachelor of Engineering - BE, Bioengineering and Biomedical Engineering

2019

Loyola Marymount University

Master of Science - MS, Systems Engineering

2018 — 2018

Indian Institute of Technology, Kharagpur

Certificate, Embedded Systems Design

ABOUT PAVITHRA SRIPATHANALLUR MURALI

Pavithra Sripathanallur Murali is a Graduate Research Assistant and a 5th Year PhD Candidate in Systems Engineering & Operations Research at George Mason University. She has a MS degree in Systems Engineering from Loyola Marymount University. Her research focuses on applying reinforcement learning, and simulation-optimization to solve sequential decision making and optimization problems in city scale systems with stochasticity and data scarcity, such as multi-fleet and critical infrastructure systems. She has publications and honors in her field, including a best project award and a project sponsorship for developing a prototype to measure the peripheral perfusion index. Pavithra has also presented at esteemed conferences including IISE & INFORMS 2023. She won Best PhD Student Paper Award at Winter Simulation Conference 2024 for her paper titled \"Hybrid Simulation and Reinforcement Learning-Based Scheduling for Resilient Infrastructure Networks\".She also has industry experience as an intern at Micron Technology, Amazon Robotics, and Symbotic where she applied her skills in advanced algorithm development (optimization and metaheuristics), simulation, queuing theory, modeling, and system architecture to improve the efficiency and performance of semiconductor manufacturing and robotic warehouse fulfillment center processes. She is passionate about developing scalable and robust algorithms that can enhance the prediction and decision making capabilities of complex networked systems. She is looking for opportunities to contribute and add value to organizations that are working on cutting-edge and innovative solutions in her domain.

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