“As instruments become more automated, there is a risk that users rely on established workflows without fully understanding the principles behind them, the potential or limitations of the technique, or the factors that can affect data quality. This makes strong training in analytical science more important than ever.”
What does your research focus on, and what problem are you trying to solve?
My research advances analytical and separation chemistry by developing innovative microextraction and separation technologies for environmental and bioanalytical applications. We use task-specific materials to develop efficient, sustainable workflows for the selective extraction, separation, and detection of emerging contaminants while advancing the fundamental understanding of chemical interactions governing partitioning processes.
What aspect of your current research excites you most – and why is this an important moment for it?
What excites me most about my research is developing analytical tools that allow us to look more closely at complex environmental and biological systems – not just measuring what is there, but understanding how chemicals interact, partition, and move within these systems. I especially enjoy the interdisciplinary aspect of this work, where advances in separation science can be combined with complementary expertise to answer scientific questions that no single discipline could address alone.
Looking five to 10 years ahead, what emerging trend do you think will have the greatest impact on analytical science?
Looking five to 10 years ahead, I believe the miniaturization of analytical platforms will have a major impact on analytical science by making in situ, in vivo, and on-site measurements increasingly accessible. The long-term potential is to make sophisticated chemical measurements increasingly accessible and practical for routine use, including outside highly specialized laboratory settings. Combined with artificial intelligence, this could further expand our ability to predict analytical performance, optimize workflows, and interpret increasingly complex data. However, I believe AI will have the greatest impact when it complements, rather than replaces, the analytical scientist’s fundamental understanding of analytical processes and instrumentation.
What is the biggest challenge facing analytical science today?
I see one overarching challenge in analytical science today: ensuring that the increasing accessibility of sophisticated instrumentation does not come at the expense of analytical expertise. Modern instruments are remarkably user-friendly, which has made powerful analytical technologies accessible to a much broader scientific community. However, operating an instrument and generating data are not the same as understanding the measurement. As instruments become more automated, there is a risk that users rely on established workflows without fully understanding the principles behind them, the potential or limitations of the technique, or the factors that can affect data quality. This makes strong training in analytical science more important than ever, particularly when these measurements are used to support conclusions and decisions in interdisciplinary research.
What decision, opportunity, or unexpected event has had the greatest influence on your career so far?
The decision that has had the greatest influence on my career was spending about half of my PhD at the University of Waterloo in Canada under the mentorship of Professor Janusz Pawliszyn, while pursuing my degree at the University of Calabria in Italy. It was not an easy decision, and pursuing the opportunity required significant commitment, effort, and personal investment, but the experience shaped me both as a scientist and as a person. It exposed me to a highly international and productive research environment, allowed me to learn from scientists with different backgrounds and perspectives, and gave me valuable opportunities to interact with industry. Many of the relationships and collaborations I established during that time remain active today and continue to influence my research program, mentorship, and approach to scientific collaboration.
What interest or skill outside science has made you a better researcher?
I was raised to be hands-on and to value precision, patience, and attention to detail, and I think that has naturally shaped the way I approach analytical science. My early education in math, physics, and Latin also gave me a strong foundation in logical and systematic thinking, which still influences how I move a research question from an idea to a conclusion. I have also always loved nature and been curious about how things work. For me, analytical measurements are one of the clearest ways we have to understand what is happening around us at the molecular level. That combination of precision, logical thinking, and curiosity continues to shape the way I approach research.
Emanuela Gionfriddo is Associate Professor of Chemistry at the University at Buffalo – The State University of New York, USA
Explore The Analytical Scientist 40 Under 40 Power List 2026
Newsletters
Receive the latest analytical science news, personalities, education, and career development – weekly to your inbox.
