Scripps Student Spotlight: Anuj Jain

Anuj Jain is a third-year undergraduate student at Scripps Institution of Oceanography at UC San Diego. He is from a town called Harda, which is in the district of Madhya Pradesh in central India. At UC San Diego, Jain is double majoring in oceanic and atmospheric sciences and computer science with a minor in mathematics. In 2019, Jain won a gold medal at the International Earth Science Olympiad in South Korea and was also the recipient of India’s Prime Minister Balshaki Award in Academics. He is currently researching where Argo robotic float sensors should be placed throughout the world’s oceans by collecting diversified ocean data. Jain is advised by Scripps researcher Matthew Mazloff and postdoctoral scholar Paul Chamberlain. 

explorations now (en):  Why did you choose to attend Scripps?
Anuj Jain (AJ): I chose to attend Scripps Institution of Oceanography to contribute to impactful computational research projects. In high school, I worked on a project titled "Discrepancy between Theoretical and Observed Decrease in Ocean pH." This involved an in-depth study of the Revelle factor, a parameter introduced by Roger Revelle, and how it could be improved. This is what first introduced me to UC San Diego and sparked my interest in joining Scripps.

en: What are you researching at Scripps? 

AJ: Argo is an international program that collects ocean data using robotic instruments, or floats. Several Argo floats under the Global Ocean-Biogeochemistry Array (GO-BGC) project form a global robotic network of floats carrying different chemical and biological sensors. My research involves optimizing where Argo sensors should be placed in the world's oceans. These sensors are very costly. Given the limited available funds and sensors, my task is to find the best sensor-wise distribution for these Argo floats that will revolutionize our understanding of ocean biogeochemical cycles and ecosystem health. Thus, the aim is to collect the most diversified ocean data by using data analysis and programming, running simulations and trying to minimize correlation between data points. This research was initiated by Paul Chamberlain, and our goal is to further enhance it. I have learned several techniques from him in this process.

en: How did you become interested in science and your field of study?

AJ: The ability to predict large-scale natural phenomena inspired my pursuit of science. While preparing for the International Earth Science Olympiad, I had the opportunity to participate in numerous field experiments and attend seminars on oceanographic research. Through collaboration with professors and fellow students, I realized that this field has a profound impact on our world and great potential for growth when combined with technical skills. The integration of programming to understand ocean-atmosphere coupling to make predictions influences my choice of major classes and projects.

en: What’s life like as a Scripps student? Describe a typical day?

AJ: A typical day for me begins with two hours of classes, followed by breakfast. I then dedicate my time to working on research projects and assignments until lunch. This involves reading recommended research papers, programming, and data analysis. Afterward, I have another two-hour class session. Additionally, I am actively involved in several leadership positions at UC San Diego, such as computer science and engineering undergraduate advising representative, Triton Quantitative Trading President, and Computer Science and Engineering Society Vice President, where I plan and host events. I conclude my day with some light entertainment.

en: What’s the most exciting thing about your work (in the field or in the lab)? 

AJ: The most exciting aspect of my work is the opportunity to learn and apply my skills simultaneously. Reviewing numerous research papers with similar assumptions and devising ways to eliminate those assumptions in discussions with my advisors is intellectually stimulating. Ultimately, using science and technology to influence policy decisions and make predictions is highly satisfying.

en: Are there any role models or mentors who have helped you along the way?

AJ: Scripps Professor Mark Merrifield serves as a role model for me. I have taken several courses with him, from which I not only gained academic knowledge but also developed collaboration, teaching, and presentation skills. He provided me with opportunities to visit various Scripps labs, which expanded my practical understanding of oceanography.

en: What are some of the challenges you face as a student? 

AJ: Managing my time effectively between programming and core science is a challenge, but the intersection of these areas in my work and projects keeps me enthusiastic. Additionally, as a vegetarian, I often encounter food-related challenges.

en: What are your plans post-Scripps? 

AJ: I'm considering at least a master's degree. I would like to keep contributing to research and am interested in industrial or entrepreneurship opportunities.

You can find Jain on LinkedIn and learn about his machine learning and deep learning-based El-Niño prediction project on YouTube.