Project participants:

• Prof. Stefanie Mueller, MIT Computer Science and Artificial Intelligence Laboratory
• Prof. Patrick Baudisch, Hasso Plattner Institute, Research Group "Human Computer Interaction"

The laser cutting design software Kyub, developed in Patrick Baudisch’ lab at Hasso Plattner Institute, allows users to design and fabricate high-quality physical prototypes with the help of subtractive fabrication machines, such as laser cutters. In this project the team of researchers from MIT and HPI will introduce the notion of sustainability into the software. The team will develop software that will suggest, during editing and in real-time, how to reduce material consumption, while minimizing impact in the design intent. This will build on a fast layout algorithm developed at Stefanie Mueller’s lab at MIT. The team will then evaluate how well both objectives, i.e., design intent and material efficiency can be achieved at the same time.

Societal impact

The work focuses on the sustainable development goal #12 Responsible Consumption and Production (reducing material waste by optimizing material usage), #9 Industry, Innovation and Infrastructure (by developing novel digital manufacturing strategies), and #4 Quality Education (by teaching high school students about novel digital manufacturing processes, such as laser cutting, and the need to be mindful of material usage).

“In the digital realm, personalization is everywhere, and thus we can assume that with the rise of digital manufacturing and the option to personalize physical products, there will be a similar large demand. It therefore is crucial to consider the impact of personalization of physical products on sustainability now and we do this in our work by investigating the trade-off between personalizing physical goods and the impact on material usage.”

Stefanie Mueller (MIT)

Project participants:

• Jillian Kwong, PhD Research Scientist, Cybersecurity at MIT Sloan (CAMS)
• Keri E. Pearlson, DBA MIT Sloan School of Management; Executive Director, Cybersecurity at MIT Sloan (CAMS)
• Prof. Christian Doerr, Hasso Plattner Institute, Research Group "Cybersecurity – Enterprise Security"

Compromised supply chains has become one of the biggest risks to businesses around the world. Not only do they threaten a company’s information assets but can also disrupt everyday operations. While companies of all sizes struggle with these issues, supply chain cybersecurity is especially difficult for small to medium-sized enterprises (SMEs). Despite the growing number of cybersecurity standards being passed around the world, research has shown some regulations can actually have an opposite effect by introducing greater levels of risk into cybersecurity supply chains. Rather than building resiliency, some government legislation has actually caused SMEs to leave the supply chain altogether (e.g., 2016 US Department of Defense (DoD) DFARS 252.204-7012 mandate). Our study explores how and why regulation fails to improve cyber-resiliency among SMEs and what can be done about it.

By understanding how companies implement new mandates and the barriers to improving SME cybersecurity, our project begins to shed light on why certain cyber-security regulations have the opposite of their intended effect. This research will allow us to provide recommendations for how SMEs can achieve higher levels of cyber-maturity as well as insights for regulators and larger organizations on how to support and drive change in SMEs.

Societal impact

Securing the cybersecurity supply chain is essential for enabling progress on all SDGs. As more activity, processes, and data move online into the cloud, it becomes essential that we focus on securing supply chains for organizations of all shapes and sizes. Enhancing security is crucial step in developing the basic infrastructure needed to carry out and make progress on any SDG. Specific goals it contributes to includes SDG #8.3 decent work and economic growth, as it supports SMEs, a pillar of the European economy, to cope with and remain competitive in view of increasing demands for cybersecurity regulation.

“This research will provide much needed context for lawmakers, company leadership, and government officials as they think about and design new policy and improve regulation moving forward."

Keri Pearlson

Project participants:

• Prof. Regina Barzilay, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
• Abdul Latif, Jameel Clinic for Machine Learning in Health, Massachusetts Institute of Technology
• Prof. Bernhard Renard, Hasso Plattner Institute, Data Analytics and Computational Statistics

Antibiotic resistance presents a serious threat to global health. We use deep learning with the goals of designing more sustainable, alternative antimicrobial agents for both clinical and agricultural use.  This can be achieved through the generation of new biomolecules, which can be used instead of traditional antibiotics to precisely target pathogenic microbes. We will use methods of explainable AI to gain insights into the biology of the designed molecules and thereby significantly advance the state of deep learning for synthetic biology.

Societal impact

Our study will not only significantly enhance the state of deep learning for synthetic biology, but also enable design of more sustainable, alternative antimicrobial agents for both clinical and agricultural use.  Therefore the project’s contributions will help ensure health and well-being (SDG #3) in the context of infectious diseases, while developing responsible consumption and production patterns for both antimicrobials and industries dependent on their use (SDG #12).  Since more frequent emergence of pathogens due to climate change must be mitigated (SDG #13) innovation solutions in those two areas are urgently needed.

“With the support of the HPI-MIT Designing for Sustainability Program, we will establish a close cooperation between the project partners to profit from our complementary competences."

Jakub Bartoszewicz