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The Department of Computer Science has a distinguished track record of academic excellence and major achievement in an increasingly vital field that is expanding at a rapid pace. Faculty research is published in the most prominent venues and recognized by significant citations and awards, both national and international. BA, MS, and PhD students are recruited for internships and positions by such industry-leading firms as Motorola Labs, Google, and Microsoft, and are also recruited as PhD students, postdoctoral researchers, and tenure-track professors by some of the best computer science departments in the country.


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  • DMCL: distillation multiple choice learning for multimodal action recognition 

    Bargal, Sarah; Garcia, Nuno; Ablavsky, Vitaly; Morerio, Pietro; Murino, Vittorio; Sclaroff, Stan (2019)
    In this work, we address the problem of learning an ensemble of specialist networks using multimodal data, while considering the realistic and challenging scenario of possible missing modalities at test time. Our goal ...
  • COSE: configuring serverless functions using statistical learning 

    Akhtar, Nabeel; Raza, Ali; Ishakian, Vatche; Matta, Ibrahim (IEEE, 2020-07)
    Serverless computing has emerged as a new compelling paradigm for the deployment of applications and services. It represents an evolution of cloud computing with a simplified programming model, that aims to abstract away ...
  • PAStime: progress-aware scheduling for time-critical computing 

    Sinha, Soham; West, Richard; Golchin, Ahmad (2020-07-07)
    Over-estimation of worst-case execution times (WCETs) of real-time tasks leads to poor resource utilization. In a mixed-criticality system (MCS), the over-provisioning of CPU time to accommodate the WCETs of highly critical ...
  • Boomerang: real-time I/O meets legacy systems 

    Golchin, Ahmad; Sinha, Soham; West, Richard (2020-04-21)
    This paper presents Boomerang, an I/O system that integrates a legacy non-real-time OS with one that is customized for timing-sensitive tasks. A relatively small RTOS benefits from the pre-existing libraries, drivers and ...
  • smARTflight: an environmentally-aware adaptive real-time flight management system (best paper award) 

    Farrukh, Anam; West, Richard (2020-07-07)
    Multi-rotor drones require real-time sensor data processing and control to maintain flight stability, which is made more challenging by external disturbances such as wind. In this paper we introduce smARTflight: an ...
  • Parallel algorithm for non-monotone DR-submodular maximization 

    Ene, Alina; Nguyen, Huy Le (2020-08-14)
    In this work, we give a new parallel algorithm for the problem of maximizing a non-monotone diminishing returns submodular function subject to a cardinality constraint. For any desired accuracy 𝜖, our algorithm achieves ...
  • How to train your quadrotor: a framework for consistently smooth and responsive flight control via reinforcement learning 

    Mysore, Siddharth; Mabsout, Bassel; Saenko, Kate; Mancuso, Renato (2020)
    We focus on the problem of reliably training Reinforcement Learning (RL) models (agents) for stable low-level control in embedded systems and test our methods on a high-performance, custom-built quadrotor platform. A ...
  • Regularizing action policies for smooth control with reinforcement learning 

    Mysore, Siddharth; Mabsout, Bassel; Mancuso, Renato; Saenko, Kate (2020)
    A critical problem with the practical utility of controllers trained with deep Reinforcement Learning (RL) is the notable lack of smoothness in the actions learned by the RL policies. This trend often presents itself ...
  • CovidCTNet: an open-source deep learning approach to diagnose Covid-19 using small cohort of CT images 

    Javaheri, T.; Homayounfar, M.; Amoozgar, Z.; Reiazi, R.; Homayounieh, F.; Abbas, E.; Laali, A.; Radmard, A.R.; Gharib, M.H.; Mousavi, S.A.J.; Ghaemi, O.; Babaei, R.; Mobin, H.K.; Hosseinzadeh, M.; Jahanban-Esfahlan, R.; Seidi, K.; Kalra, M.K.; Zhang, G.; Chitkushev, L.; Haibe-Kains, B.; Malekzadeh, R.; Rawassizadeh, R. (Nature Research (part of Springer Nature), 2021-02-17)
    Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, ...
  • Reconciling predictability and coherent caching 

    Bansal, Ayoosh; Singh, Jayati; Hao, Yifan; Wen, Jen-Yang; Mancuso, Renato; Caccamo, Marco (IEEE, 2020-06)
    Real-time systems are required to respond to their physical environment within predictable time. While multi-core platforms provide incredible computational power and throughput, they also introduce new sources of ...

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