Craig Waitt

craig wiattCraig Waitt

Trine University - Rinker-Ross School of Health Sciences
B.S. – Montclair State University; Ph.D. – University of Notre Dame
260.665.4581 | email

I'm a passionate advocate for combining the power of chemistry and computing to tackle real-world challenges. As a computational chemist, I'm thrilled to bring together my love for molecules and machines to develop innovative solutions.

My academic journey has taken me to some incredible institutions, including Montclair State University and the University of Notre Dame, where I earned degrees in chemistry, specializing in theoretical and physical chemistry. These experiences have equipped me with a strong foundation in computational methods and their applications in chemistry.

My research focuses on harnessing the potential of machine learning techniques and computational chemistry to tackle problems related to catalysis. By integrating these two fields, I aim to develop novel catalysts that can revolutionize various industrial processes.

But what really drives me is not just the science itself, but also the people behind it. As a teacher and mentor, I'm passionate about empowering students with the skills they need to tackle real-world challenges in computational modeling. There's nothing more rewarding than seeing students develop their own problem-solving strategies and techniques, and then applying them to make meaningful contributions.

When I'm not geeking out over code or molecules, you can find me on the tennis court or pickleball court. I'm a huge fan of both sports and love the camaraderie and competitive spirit they bring!

I'm excited to share my knowledge and enthusiasm with students, colleagues and collaborators. Whether it's discussing research opportunities, developing new projects or simply exploring the intersection of chemistry and computing, I'm always up for a great conversation.

Feel free to reach out if you'd like to learn more about my work, explore collaboration opportunities, or just chat about the wonders of computational modeling.