I am a PhD candidate in Earth System Science at Stanford University.
I develop machine learning algorithms to measure forest health (how wet or dry the forests are) using remote sensing. I work in the Remote Sensing Ecohydrology Group with Prof. Alexandra Konings. I got my bachleors in Civil Engineering at the Indian Institute of Technology Madras and my masters in Environmental Fluid Mechanics and Hydrology at Stanford University. During my bachelors and masters, I worked on several independent studies which convinced me about the endless possibilities of impact-based research. My quest to develop technologies to measure forest health and help quantify climate change impacts on ecosystems is derived from that conviction.
For more details about my education and professional experience, view my CV.
My path viewed through a lens of sustainability.
My research interests include understanding forest hydraulic health dynamics towards charecterizing wildfire risk and drought impacts on vegetation. To do so, I work across several scales - from plot-scale measurements to landscape-scale estimations. To know more about my research, check out my publications or talks.
Since my research involves developing data-driven approaches, where required, I apply machine learning and deep learning. While learning skills related to data science in my coursework, I worked on several projects to gain hands-on experience. The projects tab includes such side projects.
For about 2 years between my bachelors and masters, I was a Wireline Field Engineer at Schlumberger in Northeast India. There, I designed, executed and delivered several projects for reservoir characterization (measuring quantity and quality of hydrocarbon payzones) and intervention (e.g., increase wellbore flow, plug old boreholes, etc.)
My hobbies include bicycle touring, and triathlons. I am passionate about them and devote my entire free time to them. You can read more about my hobbies on the blog section.