Meet Our Students

Akshita Ramya Kamsali, a fifth-year Ph.D. candidate in electrical and computer engineering at Purdue University, is a Data Science Summer Institute intern in LLNL’s Computing directorate. Her work centers on integrating large language models into self-driving labs, with a focus on improving the security and alignment of artificial intelligence (AI) systems. Kamsali’s hands-on research is accelerating scientific discovery by leveraging advanced AI, and her experience at LLNL has exceeded her expectations, both professionally and personally. “Working at a top-tier institution like LLNL has always been a dream of mine. Being part of LLNL and working in the Advanced Manufacturing Lab has exceeded my expectations, both professionally and personally,” Kamsali said. Inspired by LLNL’s reputation for combining fundamental research with real-world impact, Kamsali has found the Lab’s collaborative and supportive environment instrumental in reigniting her passion for research. Guided by her mentor on the Advanced Robotics for Materials and Manufacturing Optimization and Research project, a Laboratory Directed Research Development-funded project, she has grown technically and personally, and now encourages future interns to communicate openly, engage with the community and seek involvement beyond their main projects.

Haesung Becker is an incoming master’s student in data science at the University of California (UC), Irvine. He just completed his seventh summer stint as an intern at LLNL, having assisted with several projects throughout the years in areas from the National Ignition Facility to finance. This summer, he worked with the Data Science Institute Consulting Service, mentored by Gemma Anderson, to help employees seeking to use data science or machine learning to enhance their projects. One key example involved working with the Transformation Team to address scheduling questions relevant to all employees, such as how much time people spend in meetings and how often they are overbooked. Becker parsed Outlook information through Python, then created graphs of variables such as the average amount of hours spent in meetings over a given week or the distribution of meetings over a given weekday. In addition to his work at the Laboratory, Becker’s education in data science has also been multifaceted, with much of his learning taking place outside of the classroom during his undergraduate years at Diablo Valley College and UC Santa Cruz. “Programming isn't something that you can simply learn from school,” he said. “You have to experiment, branch out, and make your own projects; a lot of what I learned, I learned by doing things on my own for personal work or researching myself.” For example, in his spare time, Becker enjoys gaming—especially World of Warcraft Classic, to which he applied his programming knowledge with a Python project to keep track of loot items dropped from raid bosses. Becker’s advice to other students in this field shares a similar sentiment of independent exploration. “Use a large language model frequently, and don't be afraid to iterate or touch base with your mentor frequently,” he said. “At the same time, don't be afraid to branch out and give contributions that weren't exactly required of you. Because the people around you may not have all the knowledge you have on data science, they might not see all the opportunities for problem-solving that you would.”