Kamarthi Receives Excellence in Teaching Award

MIE Professor Sagar Kamarthi received the Northeastern University Excellence in Teaching Award. Nominations for the Excellence in Teaching Awards are made by students. They consider several criteria, including depth of knowledge in the subject, the rigor of course content, and the ability to provide effective links among course content, research, and experiential learning.

During his tenure at Northeastern, Professor Kamarthi has made a staggering number of contributions to mechanical and industrial engineering research, teaching, and service. An expert in manufacturing, data science, and health analytics, he is a prolific researcher with over 200 scholarly publications, including journal and conference papers and book chapters, and over $10.8 million in external funding, while also overseeing 20 doctoral and 45 master’s degree students. He has developed eight cutting-edge courses and taught a total of 16 different courses. Professor Kamarthi is the founding director of Northeastern’s master’s in data analytics engineering program. After envisioning the emergence of the data analytics field in 2011, he designed the curriculum, courses, and established the program. Three National Science Foundation grants have enabled his pioneering contributions to engineering education: the Engineering-Based Learning model, a structured version of project-based learning; the TRANSFORM model, a novel curriculum to train non-STEM graduates for manufacturing careers; and IMPEL, an online learning science research, and data science curriculum and courses for Industry 4.0. In addition, he is recognized for his Mass Customized Instruction model, a personalized learning approach to address the grand challenges posed by the National Academy of Engineering. As a testimony to his dedication, his students hold him in the highest regard.


The future of manufacturing is here. Are we ready?

Sagar Kamarthi is a professor of mechanical and industrial engineering at Northeastern. Photo by Matthew Modoono/Northeastern University

A new industrial revolution—a transformation in manufacturing—is underway, and in order to remain competitive globally, says Sagar Kamarthi, the people working in this industry must be able to keep up with the skills that new machines require.

Kamarthi, an industrial engineer by training and a professor of mechanical and industrial engineering at Northeastern, is doing his part in the shift toward modernizing manufacturing. Since October, he has been leading a team of researchers in an endeavor to develop courses to help people working in manufacturing retool their skills.

Supported by a $2 million grant from the National Science Foundation, Kamarthi will direct a program to design, develop, and deploy online data science curricula targeting professionals and college students interested in advancing their skills and knowledge for the digital age and artificial intelligence-driven world.

To allow learners to tailor the curricula to their individual needs, the team is building a system that prescribes the right set of courses and modules taking into consideration the learner’s aptitude, competency, and workplace needs. In this effort, the researchers plan to discover and study learning principles unique to online learners.

Kamarthi, who also directs the College of Engineering’s graduate program in data analytics engineering, develops algorithms that enable machines to detect errors and anticipate failures within their own systems. Beyond manufacturing, he also applies his machine learning expertise to other fields, such as healthcare and medicine. He is involved in research projects that attempt to develop methods for objective pain measurement and personalized breast cancer treatment.

He is also developing masters and doctoral programs in advanced and intelligent manufacturing, as part of which he will endeavor to establish, in collaboration with assistant professor of mechanical and industrial engineering Mohsen Moghaddam, a multi-use cyber-physical factory at Northeastern to prepare students for emerging Industry 4.0 technologies, such as the Internet of Things, cybersecurity, robotics and automation, machine learning and artificial intelligence, augmented and virtual reality, and smart and sustainable manufacturing.

For his efforts in curriculum development, education program administration, teaching and student mentoring, Kamarthi has been selected as one of two faculty members to receive Northeastern’s Excellence in Teaching Award. Nominations for the award are made by students based on the following criteria: the faculty members’ depth of knowledge in the subject, their ability to provide effective links among course content, research, and experiential learning, and the rigor of the course content.

Jacqueline Isaacs, interim dean of the College of Engineering and a professor of mechanical and industrial engineering, commended Kamarthi for envisioning the emergence of the data analytics field in 2011 and designing the curriculum and the courses for Northeastern’s data analytics engineering graduate program. The program, which was launched in 2016 on the Boston campus and in 2019 on the Seattle campus, has 400 students to date and is expected to nearly double in the fall.

“Over his 26 years at Northeastern he has been consistently at the forefront of his field and leveraged his research expertise in creating new classes, new programs, and making sure his undergraduate and graduate students get the best and most up-to-date education,” Isaacs wrote in her nomination letter for Kamarthi.

Kamarthi says he was thrilled and honored to receive the award, and that he will use the recognition to contribute to the vision of Northeastern 2025, the university’s academic plan and blueprint for the future.

He says he enjoys teaching and mentoring.

“I consider teaching students critical thinking and life-long learning skills is as important as teaching them ideas, concepts, and formulas,” he says.


by Khalida Sarwari, News @ Northeastern

Related Faculty: Sagar Kamarthi

Related Departments:Mechanical & Industrial Engineering