Dr. Gowtam Valluri (he/him)

Space Physicist
Geospace Physics Laboratory (673)

How did you end up working at NASA Goddard?

I completed my Ph.D. at the Indian Institute of Geomagnetism (IIG) and the University of Mumbai, with a focus on space weather and ionosphere modeling. In 2021, I was seeking postdoctoral opportunities and came across an advertisement in the CEDAR/GEM newsletters for a position as a postdoctoral fellow in machine learning and space weather. This position, under Dr. Hyunju Connor, was part of the Machine Learning Algorithms for Geomagnetically Induced Currents in Alaska and New Hampshire (MAGICIAN) project at the University of Alaska Fairbanks (UAF), where she was an assistant professor at the time. I applied and was fortunate enough to secure the position. My research journey continued under Dr. Connor's mentorship at UAF. Later, Dr. Connor transitioned to NASA, and she advertised a postdoctoral position again. I applied once more and was offered the opportunity, allowing me to continue my research at NASA. One of the most significant milestones in my career to date has been the opportunity to join NASA. It represented a significant step forward in terms of both professional growth and the opportunity to contribute to projects with real global impact. It's a place where collaboration and innovation are part of the daily routine, and being part of that environment has been both challenging and rewarding.

Tell us about the research projects you are currently working on.

Currently, I am working on the development of a Machine Learning-based Auroral Ionosphere Electrodynamics Model (ML-AIM) with Dr. Hyunju Connor. The core objective of ML-AIM is to solve the current continuity equation by utilizing machine learning techniques. In its simplest form, the current continuity equation expresses the fact that the total current flowing into a region must equal the total current flowing out, assuming there's no accumulation of charge. In the context of the auroral ionosphere, the current continuity equation plays a vital role in describing how currents (such as Field-Aligned Currents (FACs)) flow along magnetic field lines, linking different regions of the ionosphere and magnetosphere. Specifically, the ML-AIM incorporates FACs and empirical conductance as key components, which are critical for understanding the electrical and dynamical processes occurring in the auroral ionosphere.

In addition to ML-AIM, I am also developing a Machine Learning-based Particle Precipitation Model (ML-PPM). This model focuses on simulating the energy fluxes of both electrons and ions, which are essential inputs for Global Circulation Models (GCMs). These energy fluxes are crucial for simulating the behavior of the ionosphere and for improving the accuracy of space weather predictions.

The ultimate goal of these efforts is to integrate these individual machine learning models into a comprehensive framework. We are working towards creating the Artificial Intelligence Modeling Framework for Advancing Heliophysics Research (AIMFAHR). This framework will combine these models to enhance our understanding of space weather phenomena and to advance research in heliophysics by leveraging the power of artificial intelligence.

The recent Gannon/Mother's Day geomagnetic storm, one of the strongest in years, captured global attention. Active auroras were visible as far south as the southernmost parts of the United States, a rare and remarkable event. We are developing a Machine Learning–based Electron Precipitation Model (ML-EPM) using electron and ion precipitation data from the Defense Meteorological Satellite Program (DMSP). This image displays the model's predictions: total electron energy flux, the equatorward edge (green dots), and the poleward edge (red dots) of the auroral oval. During the Gannon storm, ML-EPM indicated intense electron precipitation with a significantly equatorward expansion of the auroral oval—consistent with widespread citizen science observations reported through Aurorasaurus. Further validations are currently in progress.
Credit: Gowtam Valluri and Hyunju Connor

What skills are most useful to you in your work, and where did you develop those skills?

Several key skills have been instrumental in my work—data analysis, programming (particularly in Python and MATLAB), machine learning, and domain expertise in space physics and ionospheric modeling. I developed the foundation for these skills during my Ph.D. at the Indian Institute of Geomagnetism, under the mentorship of Prof. Tulasi Ram, where I worked extensively with satellite and ground-based data to model global ionosphere. We developed an Artificial Neural Network based Ionospheric Model (ANNIM) during my Ph.D. and Post doc times at IIG, which helped me to gain deeper understanding about space weather, the ionosphere and machine learning. During my postdoctoral work at the University of Alaska Fairbanks, I further honed my auroral physics and machine learning skills by collaborating on the Machine Learning Algorithms for Geomagnetically Induced Currents in Alaska and New Hampshire (MAGICIAN) project. Working in research environments like UAF and NASA also helped me refine my critical thinking and collaboration skills.

What keeps you inspired by your work?

What keeps me inspired by my work is the sense of curiosity and the drive to explore the unknown. I'm motivated by the challenge of solving complex problems and the potential to make meaningful contributions to our understanding of the natural world. Specifically, working in the realm of space weather adds an exciting dimension, knowing that my efforts can help predict and mitigate the effects of geomagnetic storms and other space weather phenomena that impact satellites, communications, navigation systems, and even power grids on Earth. It's deeply fulfilling to be part of a mission that safeguards our technology-dependent society while also advancing scientific research. Being in a field where innovation and discovery are constant, collaboration and creativity directly influence how we understand and respond to the dynamics of space gives me a strong sense of purpose.

This photo was taken during an active geomagnetic storm in Fairbanks, Alaska, on March 23, 2023—one of my favorite aurora shots. There's a small hill spot near the UAF campus where people often gather during predicted aurora activity. The bright auroral arcs here indicate intense particle precipitation. I really love how my research connects so vividly with real-world auroral displays!
Credit: Gowtam Valluri

What inspired you to pursue a career in Space Physics?

During my master's project at the Indian Institute of Geomagnetism, I came across a picture of the aurora for the first time. I was completely mesmerized and started wondering what those beautiful lights were and how they appeared in the sky. That curiosity led me to learn about space weather and how solar storms are responsible for auroras. I was instantly fascinated. As I continued exploring, I read stories about how people in ancient times interpreted auroras, long before the science behind them was known. For example, the Scandinavian people believed auroras were reflections of the Valkyries' armor as they guided fallen warriors to the afterlife. In some Indigenous North American cultures, auroras were thought to be the spirits of ancestors dancing in the sky. The combination of natural beauty, mystery, and the powerful forces from the Sun that affect our planet deeply inspired me. That initial spark of curiosity eventually grew into a strong desire to understand space weather and the physics behind it, which set me on the path to a career in space physics.

The Richardson Highway is one of Alaska's oldest and most scenic highways, stretching from Fairbanks to Valdez. Along the route, travelers are treated to breathtaking views. Valdez, nestled at the head of a deep fjord in Prince William Sound, is known for its dramatic landscapes, rich history, and outdoor adventures like fishing, hiking, and glacier tours. I was stunned by the beauty of Valdez during my visit and went camping there during my postdoc at UAF.
Credit: Jhansi

What do you like to do in your free time?

In my free time, I love to travel and immerse myself in the beauty of nature. During my postdoctoral position in Alaska, I was fortunate to experience a once-in-a-lifetime opportunity to explore one of the most breathtaking regions on Earth. Alaska's vast and untouched wilderness captivated me with its beautiful aurora, stunning landscapes, glaciers, and mountain ranges. I spent my summer weekends visiting some of the state's most iconic attractions—glacier hikes, wildlife viewing, and serene lake trails that felt like scenes from a dream. During the winters, travel becomes limited as temperatures drop below -40°C, yet the season offers a unique opportunity to witness the enchanting aurora. I used to closely follow geomagnetic storm predictions and venture out on aurora-chasing nights, often rewarded with mesmerizing displays in the sky. These adventures offered not only thrilling experiences but also a deep sense of peace and connection to nature. Traveling, especially through such raw and awe-inspiring places, rejuvenates my mind and inspires me in both personal and professional spheres. Exploring Alaska's natural wonders was truly unforgettable, and it strengthened my passion for discovering new places and cultures whenever I have the chance.

The Western Ghats are among the most breathtaking hill ranges in the Indian subcontinent. During the monsoon, they transform into a lush paradise, attracting trekkers from far and wide.During my PhD at IIG, a small group of us would venture out on weekend treks, especially at the height of the monsoon season. This photo was captured during one such monsoon trek in the suburbs of Mumbai.
Credit: Ankush

What are your future research interests and goals?

Looking ahead, my research goals center around advancing AI-driven frameworks for space weather modeling and prediction. I'm particularly interested in integrating machine learning with physics-based models to improve our understanding of magnetosphere-ionosphere-thermosphere coupling processes. Expanding auroral precipitation and electrodynamics models into a robust, scalable system that can support both operational forecasting and fundamental science is a long-term objective. Additionally, I aim to contribute to building open-source tools and datasets that can empower the broader space science community. Ultimately, my goal is to push the boundaries of how we use AI to decode the complex behavior of our near-Earth space environment and enhance our preparedness for space weather impacts.

I visited the Castner Glacier Ice Caves—an unforgettable experience. Located approximately 145 miles southeast of Fairbanks, Alaska, these naturally formed ice caves offer a remarkable winter adventure. They are accessible via a relatively easy hike and are best visited during the colder months, when conditions are more stable.
Credit: Jhansi