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Sanjukta Krishnagopal
Applied physicist with research at the interface of network science, dynamical systems and machine learning
Sanjukta Krishnagopal is a prominent researcher currently pursuing her Ph.D. at the University of Maryland, College Park, where she has been engaged in advanced studies since 2016. Her academic background includes an Integrated M.Sc (Hons) in Physics from the Birla Institute of Technology and Science in India. She completed her Ph.D. in Physics in 2020, focusing on developing mathematical and computational methods in network dynamics and generalizable machine learning applied to complex data systems.26
Research Interests
Sanjukta's research spans several interdisciplinary areas, including:
- Network Science: Investigating dynamics within networks and their applications to real-world systems.
- Machine Learning: Developing algorithms that enhance understanding and prediction capabilities within complex datasets.
- Data Science: Utilizing computational tools to analyze and interpret large-scale data.145
Career Progression
After completing her Ph.D., Sanjukta became a UC Presidential Postdoctoral Fellow, with joint appointments at UC Berkeley and UCLA. Her work there involves applying her expertise in network dynamics to various fields, including personalized medicine and explainable AI.34
Contributions and Publications
Sanjukta has contributed significantly to the scientific community through her research publications, focusing on topics such as:
- Predictive Modeling: Utilizing machine learning techniques for disease subtyping.
- Network Dynamics: Exploring synchronization patterns and chaotic systems.27
In addition to her research, she is actively involved in community engagement through initiatives like hosting a podcast aimed at promoting women in science.1
Overall, Sanjukta Krishnagopal exemplifies a dedicated researcher at the intersection of physics, data science, and machine learning, contributing valuable insights into complex systems.