Ziyang Wang

I am a Machine Learning Engineer at Eurofins Scientific, where I develop artificial intelligence (AI) and machine learning (ML) solutions for scientific data analysis and automated analytical instrumentation.

I received my Ph.D. in Electrical and Computer Engineering from Rice University, where I conducted research in the SCOPE Lab under the supervision of Prof. Shengxi Huang. Prior to Rice, I earned dual bachelor’s degrees in Computer Science and Mathematics from The Pennsylvania State University as a Schreyer Honors Scholar.

My expertise lies at the intersection of artificial intelligence, computational science, and experimental technologies. My work focuses on developing interpretable machine learning methods for scientific data analysis, computational modeling, and spectroscopy, with applications spanning analytical chemistry, biomedical sciences, materials characterization, molecular sensing, and automated laboratory systems.

During my doctoral and postdoctoral research, I developed AI-powered spectroscopy frameworks for disease diagnosis, biomarker discovery, virus identification, cancer research, and next-generation materials characterization. At Eurofins, I am extending these methodologies to real-world analytical chemistry by developing machine learning algorithms for chromatography, mass spectrometry, and laboratory automation to improve the speed, accuracy, and scalability of chemical analysis. My long-term vision is to integrate AI into scientific instrumentation and autonomous laboratories, enabling data-driven discovery across healthcare, environmental monitoring, food safety, and advanced materials while accelerating scientific innovation and improving human health.