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URI: http://hdl.handle.net/2144/973

Welcome to the Department of Electrical & Computer Engineering

The Department of Electrical & Computer Engineering (ECE) offers a world-class education and conducts innovative research at the forefront of evolving technologies like computer hardware and software development, electronic and photonic devices, as well as sensing, processing and communication of various forms of information. With a renowned faculty, interdisciplinary research focus, cutting-edge facilities, and diverse student body, ECE is at the forefront of the technological breakthroughs that are shaping the future. Research activities in ECE are broadly classified into three primary areas: Computer Engineering, Electro-Physics, and Information and Data Sciences. The boundaries between these groups are not sharp, and interaction and cross-fertilization is common. In addition to rigorous class work, ECE degree programs encourage students to pursue hands-on research under the guidance of our accomplished faculty and in cooperation with university-wide centers and cross-disciplinary collaborations. This combination of practical and theoretical education ensures a breadth of experience in innovative problem solving and exploration that will prepare graduates for wide-range of interdisciplinary engineering careers.

ECE Contacts

Boston University Department of Electrical & Computer Engineering
W. Clem Karl, PhD, Chair
8 St. Mary's St., Room 324
Phone: (617) 353-2811
Fax: (617) 353-7337
www.bu.edu/ece

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Recently Added

  • BOTection: bot detection by building Markov Chain models of bots network behavior 

    AlAhmadi, Bushra A.; Mariconti, Enrico; Spolaor, Riccardo; Stringhini, Gianluca; Martinovic, Ivan (ACM, 2020-10-05)
    Botnets continue to be a threat to organizations, thus various machine learning-based botnet detectors have been proposed. However, the capability of such systems in detecting new or unseen botnets is crucial to ensure its ...
  • Disturbed YouTube for kids: characterizing and detecting inappropriate videos targeting young children 

    Papadamou, Konstantinos; Papasavva, Antonis; Zannettou, Savvas; Blackburn, Jeremy; De Cristofaro, Emiliano; Kourtellis, Nicholas; Stringhini, Gianluca; Sirivianos, Michael (2020-06-08)
    A large number of the most-subscribed YouTube channels target children of very young age. Hundreds of toddler-oriented channels on YouTube feature inoffensive, well produced, and educational videos. Unfortunately, ...
  • Characterizing the use of images by state-sponsored troll accounts on Twitter 

    Zannettou, Savvas; Bradly, Barry; De Cristofaro, Emiliano; Stringhini, Gianluca; Blackburn, Jeremy (2020-06-08)
    State-sponsored organizations are increasingly linked to efforts aimed to exploit social media for information warfare and manipulating public opinion. Typically, their activities rely on a number of social network ...
  • Raiders of the lost Kek: 3.5 years of augmented 4chan posts from the politically incorrect board 

    Papasavva, Antonis; Zannettou, Savvas; De Cristofaro, Emiliano; Stringhini, Gianluca; Blackburn, Jeremy (2020-06-08)
    This paper presents a dataset with over 3.3M threads and 134.5M posts from the Politically Incorrect board (/pol/) of the imageboard forum 4chan, posted over a period of almost 3.5 years (June 2016–November 2019). To ...
  • Measuring and characterizing hate speech on news websites 

    Zannettou, Savvas; Elsherief, Mai; Belding, Elizabeth; Nilizadeh, Shirin; Stringhini, Gianluca (ACM, 2020-07-06)
    The Web has become the main source for news acquisition. At the same time, news discussion has become more social: users can post comments on news articles or discuss news articles on other platforms like Reddit. These ...
  • Opportunistic intermittent control with safety guarantees for autonomous systems 

    Huang, Chao; Xu, Shichao; Wang, Zhilu; Li, Wenchao; Lan, Shuyue; Zhu, Qi (2020)
    Control schemes for autonomous systems are often designed in a way that anticipates the worst case in any situation. At runtime, however, there could exist opportunities to leverage the characteristics of specific environment ...
  • TrojDRL: evaluation of backdoor attacks on deep reinforcement learning 

    Kiourti, Panagiota; Wardega, Kacper; Jha, Susmit; Li, Wenchao (2020)
    We present TrojDRL, a tool for exploring and evaluating backdoor attacks on deep reinforcement learning agents. TrojDRL exploits the sequential nature of deep reinforcement learning (DRL) and considers different gradations ...
  • Information-distilling quantizers 

    Bhatt, Alankrita; Nazer, Bobak; Ordentlich, Or; Polyanskiy, Yury (2018-02)
    Let X and Y be dependent random variables. This paper considers the problem of designing a scalar quantizer for Y to maximize the mutual information between the quantizer's output and X, and develops fundamental properties ...
  • Virtual phenomics - use of robots and drones in combination with genomics accelerate genetic gains in wheat breeding 

    Shafiee, Sahameh; From, Pål; Burud, Ingunn; Dieseth, Jon Arne; Vindfallet, Are; Crossa, Jose; Alsheikh, Muath (2019-10-22)
    Wheat breeding is a tedious process that usually takes 10-15 years and depends heavily on the ability to identify superior progeny lines by visual inspection and manual scoring of traits. Two emerging technologies are now ...
  • Towards verification-aware knowledge distillation for neural-network controlled systems: invited paper 

    Fan, Jiameng; Huang, Chao; Li, Wenchao; Chen, Xin; Zhu, Qi (IEEE, 2019-11)
    Neural networks are widely used in many applications ranging from classification to control. While these networks are composed of simple arithmetic operations, they are challenging to formally verify for properties such ...

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