I am a passionate data scientist with a keen interest in scientific computing and AI research. I did my PhD at Imperial College London in the field of scientific modeling for energy storage systems, where I developed physics-based models to understand the performance and degradation of solid-state batteries. After completing my PhD, I joined BASF SE as a postdoctoral researcher in the field of data science for chemical R&D and application. It was an interesting transition from academia to industrial research, where I have the opportunity to apply my modeling and data analytics skills to solving real-world problems in the chemical industry. I was apppointed as a JSPS Fellow in 2024, which allowed me to conduct research at the Tohoku University in Japan for 3 months. During this time, I focused on benchmarking statistical and data-driven anomaly detection methods for battery applications.
I have a broad range of interests in the field of data science and AI, including but not limited to:
- Data Analytics, where I focus on developing innovative methods and tools to extract meaningful patterns and insights from large datasets.
- Scientific Machine Learning, where I explore the intersection of machine learning with scientific modeling to develop methods that can simulate and predict complex phenomena across various scientific domains.
- Machine Learning Operations (MLOps), where I am dedicated to optimizing the deployment and life-cycle management of AI models in production environments while minimizing the gaps between models developed for R&D and models integrated into real-world applications.
- Generative AI, where I am interested to develop conversational AI agents to extract information out of a mix of organized data (such as tables in a database) and unorganized data (like PDFs or text documents).
When I’m not immersed in coding, you can find me reading about philosophy, traveling, or experimenting with new recipes in the kitchen. I am always eager to learn and grow, both personally and professionally.
I like the Japanese idea of Kaizen, which means embracing continuous learning and improvement, even if it is just a small step every day. Whether it’s learning a new programming language, exploring a new research area, or simply trying out a new recipe, taking small concrete actions consistently do add up and lead to a meaningful progress in the long run. This also means that I value the process of learning and discovery as much as the end results. If you notice anything that I can improve in my work or presentations, I am always open to feedback and suggestions. I believe that learning is a lifelong journey, and there is always room for growth and improvement. So please don’t hesitate to get in touch if you have any thoughts or ideas to share!