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URI: http://hdl.handle.net/2144/971

The College of Engineering at Boston University is a community of students, faculty, and staff focused on advancing science and technology through research and discovery, and preparing students to be technology leaders in the 21st century. Undergraduate students participate in a comprehensive core curriculum that sets the foundation for their engineering studies while delivering a breadth of education across the humanities, mathematics, and social and natural sciences. Through an array of majors and concentrations, they can study aerospace, biomedical, computer, electrical, manufacturing or mechanical engineering, as well as nanotechnology, and energy technologies and environmental engineering. They also have the opportunity work side-by-side with research faculty in a number of modern, high-tech facilities. Graduate students partake in myriad programs and research opportunities leading to doctoral or master’s degrees in biomedical, computer, computer systems, electrical, manufacturing, mechanical, global manufacturing, photonics, systems, or materials science and engineering.

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  • Data for "a physics-informed impact model refined by multi-fidelity transfer learning" 

    Snapp, Kelsey L.; Silverman, Samuel; Pang, Richard; Tiano, Thomas M.; Lawton, Timothy J.; Whiting, Emily; Brown, Keith A.
    This folder contains the experimental data for the research paper "A physics-informed impact model refined by multi-fidelity transfer learning" which is scheduled to be published in Extreme Mechanics Letters. The designs ...
  • Data for "a Bayesian experimental autonomous researcher for mechanical design" 

    Gongora, Aldair E.; Xu, Bowen; Perry, Wyatt; Okoye, Chika; Riley, Patrick; Reyes, Kristofer G.; Morgan, Elise F.; Brown, Keith A.
  • Data for "designing lattices for impact protection using transfer learning" 

    Gongora, Aldair E; Snapp, Kelsey L; Pang, Richard; Lawton, Timothy J; Morgan, Elise F; Brown, Keith A; Tiano, Thomas M; Reyes, Kristofer G.; Whiting, Emily
  • Data for "using simulation to accelerate autonomous experimentation: a case study using mechanics" 

    Gongora, Aldair E.; Snapp, Kelsey L.; Whiting, Emily; Riley, Patrick; Reyes, Kristofer G.; Morgan, Elise F.; Brown, Keith A.
  • A general security approach for soft-information decoding against smart bursty jammers 

    Ercan, Furkan; Galligan, Kevin; Duffy, Ken R.; Medard, Muriel; Starobinski, David; Yazicigil, Rabia Tugce (IEEE, 2022-12-04)
    Malicious attacks such as jamming can cause significant disruption or complete denial of service (DoS) to wireless communication protocols. Moreover, jamming devices are getting smarter, making them difficult to detect. ...
  • Uncovering product vulnerabilities with threat knowledge graphs 

    Shi, Zhenpeng; Matyunin, Nikolay; Graffi, Kalman; Starobinski, David (IEEE, 2022-10)
    Threat modeling and security assessment rely on public information on products, vulnerabilities and weaknesses. So far, databases in these categories have rarely been analyzed in combination. Yet, doing so could help predict ...
  • Multi-protocol IoT network reconnaissance 

    Gvozdenovic, Stefan; Becker, Johannes Karl; Mikulskis, John; Starobinski, David (IEEE, 2022-10-03)
    Network reconnaissance is a core security functionality, which can be used to detect hidden unauthorized devices or to identify missing devices. Currently, there is a lack of network reconnaissance tools capable of discovering ...
  • Optimizing freshness in IoT scans 

    Becker, Johannes Karl; Starobinski, David
    Motivated by IoT security monitoring applications, we consider the problem of a wireless monitor that must implement a multi-channel scanning policy to minimize the Age of Information (AoI) of received information. We model ...
  • Empirical comparison of block relay protocols 

    Imtiaz, Muhammad Anas; Starobinski, David; Trachtenberg, Ari (Institute of Electrical and Electronics Engineers (IEEE), 2022-12)
    Block relay protocols play a key role in the performance and security of public blockchains. As a result, several such protocols have been deployed in the context of Bitcoin and its variants (e.g., legacy, compact block ...
  • Data for autonomous discovery of tough structures 

    Snapp, Kelsey L.; Verdier, Benjamin; Gongora, Aldair; Silverman, Samuel; Adesiji, Adedire D.; Morgan, Elise F.; Lawton, Timothy J.; Whiting, Emily; Brown, Keith A.
    This dataset contains the experimental data for the research paper "Autonomous Discovery of Tough Structure" which is currently in the peer review process. The document contains the record of physical experiments ...

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