The SDM community is continually addressing some of the world's most complex challenges through innovative problem-solving. Our faculty continue to shape the field of systems thinking through their research. With critical guidance from our faculty and industry professionals, our students and alumni harness the principles and theories from their SDM education to find innovative solutions and serve as leaders in their fields.
Submitted by Aravind Asokan. Abstract: Commercial flight operations have seen the consistent reduction of flight crew from five to two over the past several decades. As technology
Pankhuri Sen, SDM ’20 and a research assistant in MIT’s AutoID Laboratory, was featured in MIT News for the laboratory’s work on RFID sensors that could be
Submitted by Javier Gotschlich Praus. Abstract: This paper examines how fuel tax policies affect the generation of revenue to maintain the US road infrastructure. Currently,
In the spring of 2018, System Design and Management hosted a symposium on characterizing the gap between strategy and implementation. This symposium featured original work from
Submitted by Siddhartha Ray Barua. Abstract: Many companies are increasing their focus on Artificial Intelligence as they incorporate Machine Learning and Cognitive technologies
Thesis: Investigating the transformation of a medical enterprise : can a medical device company truly become agile?
Submitted by Arlesa Hubbard. Abstract: With the competitive landscape of technology increasing at a rapid pace, medical device manufacturers are struggling to keep up with the
Submitted by Hiroyuki Ikukawa. Abstract: Japanese construction industry is currently struggling with technology development due to the resisting forces against introducing and
Submitted by Kautilya Vemulapalli. Abstract: The Commercial UAS industry is relatively new and has significant growth potential as new technology are incorporated into it, new
Thesis: Evaluation of the smoothing activation function in neural networks for business applications
Submitted by Jun Siong Ang. With vast improvements in computational power, increased accessibility to big data, and rapid innovations in computing algorithms, the use of neural