
Always kind, respectful, and approachable.
Challenges students to grow and excel.
Helps students see the bigger picture.
Always prepared and organized for students.
A true mentor who cares about success.
Dr. Ashish Dutt serves as a Lecturer in the School of Science at Monash University Malaysia. His academic journey began with a Bachelor of Science degree from Panjab University in Chandigarh, India. Following his undergraduate studies, he gained a decade of professional experience in the information technology sector, working with leading companies such as Dell and IBM in India. Drawing on this rich industrial background, he pursued higher education, earning a Master of Computer Science from Staffordshire University at its Malaysia campus. He later completed his PhD in Computer Science at the University of Malaya, awarded on December 16, 2020, with a focus on mixed data clustering in the field of Educational Data Mining. Prior to his appointment at Monash University Malaysia, Dr. Dutt was a Senior Data Scientist at Micron Technology Sdn Bhd in Penang, Malaysia, where he developed video analytics-based solutions for smart solid-state drive manufacturing.
Dr. Dutt's research specializations include Educational Data Mining, mixed data clustering, feature selection methods in Educational Data Mining, clustering algorithms, Artificial Intelligence in Education, and Machine Learning. He has contributed significantly to the academic literature through peer-reviewed publications in high-impact journals and conferences. Notable works include "A Systematic Review on Educational Data Mining," co-authored with Maizatul Akmar Ismail and Tutut Herawan and published in IEEE Access in 2017, which has received 427 citations per Scopus. Other key publications are "A partition-based feature selection method for mixed data: a filter approach" with Maizatul Akmar Ismail in the Malaysian Journal of Computer Science (2020), "Applying clustering approach to analyze reflective dialogues and students' problem solving ability" (2015), "An approachable analytical study on big educational data mining" from ICCSA 2014, and "Can we predict student learning performance from LMS data? A classification approach" (2019). He also serves as a reviewer for several ISI and Scopus-indexed journals in computer science. In his teaching role, Dr. Dutt delivers units such as ADS1002 - Data Challenges 2 within the Bachelor of Applied Data Science program, bridging practical data science applications with educational research.