Kamal Nayal

Kamal Nayal is a first-year Ph.D. student in Theoretical & Computational Chemistry at Carnegie Mellon University with a keen interest in Algorithm Development and Machine Learning for Chemistry problems.

He completed his Master of Science degree at Indian Institute of Technology (IIT) Kharagpur after a 5-year Integrated BS-MS coursework.

Kamal is characterized as self-motivated, goal-oriented, and collaborative, thriving on challenges and always seeking opportunities to learn.

His educational background includes a Doctor of Philosophy (Ph.D.) in Theoretical Chemistry & Machine Learning from Carnegie Mellon University and a Master of Science in Chemistry from IIT Kharagpur.

Kamal has a diverse professional experience, having worked at organizations like Crowd2Map Tanzania, ETH Zürich, University of Helsinki, Princeton University, Aarhus University, Technical University Munich, and Regalix, in roles ranging from a LinkedIn Administrator to a Graduate Research Assistant.

He also held positions such as ISIP Scholar at Princeton University, Machine Learning Intern at Regalix, and Research Fellow at Technical University Munich, showcasing his varied skill set and adaptability.

Additionally, Kamal has been involved in extracurricular activities during his time at IIT Kharagpur, serving as a Department Representative at the Career Development Centre and a Student Member at the International Relations Cell.