skip to content
Home

Department of Computer Science and Technology

Research staff Subscribe to RSS - Research staff

Singular: 
Research staff
Slug: 
research-staff
Read more at: Omer Nivron

Omer Nivron

In my research, I'm interested in developing probabilistic machine learning tools and apply them to climate-related problems. 

More specifically, my current research is motivated by the following questions:

(1) What will be the temperature at any specific location in 2050 (or any other mid-long term forecast)? 

(2)  How can we reason about temperatures and their associated uncertainties when we can barely say what will be the temperatures next week?

Read more at: Christian Cabrera Jojoa

Christian Cabrera Jojoa

Read more at: Konrad Witaszczyk

Konrad Witaszczyk

I am a research associate and a PhD student working on the CHERI project. I joined the project as a research associate in January 2021 to work on third-party software for the CheriBSD operating system and started my PhD in October 2022 to explore compartmentalisation ideas in the CheriBSD kernel under supervision of Prof. Robert Watson.

Read more at: Filip Svoboda

Filip Svoboda

Read more at: David Buterez

David Buterez

Read more at: Kayla Butkow

Kayla Butkow

Read more at: Al Amjad Tawfiq Isstaif

Al Amjad Tawfiq Isstaif

I am a first year PhD student in the Systems Research Group (SRG) at the Department of Computer Science and Technology (also known as “The Computer Lab”), working under the supervision of Professor Richard Mortier. I am a member of Clare College.

In 2018, I was awarded the Said Foundation Cambridge Scholarship , to study the MPhil in Advanced Computer Science (ACS) at the Computer Lab. Before moving to Cambridge, I co-founded several projects for empowering engineering students in Syria, including the award-winning education enterprise: Wikilogia.

Conference proceedings

  • Isstaif, AAT. and Mortier, R., 2023. Towards Latency-Aware Linux Scheduling for Serverless Workloads Proceedings of the 1st Workshop on SErverless Systems, Applications and MEthodologies,
    Doi: 10.1145/3592533.3592807
    •
  • Isstaif, AAT., 2020. Self-managed services using MirageOS unikernels Middleware 2020 Doctoral Symposium Proceedings of the 2020 21st International Middleware Conference Doctoral Symposium Part of Middleware 2020,
    Doi: 10.1145/3429351.3431748
    •
  • Isstaif, AAT. and Alhafez, N., 2018. Performance Model of Apache Cassandra Under Heterogeneous Workload Using the Quantitative Verification Approach Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, v. 11178 LNCS
    Doi: 10.1007/978-3-030-02227-3_7
    •
    Conference proceedings

    2023

  • Isstaif, AAT. and Mortier, R., 2023. Towards Latency-Aware Linux Scheduling for Serverless Workloads Proceedings of the 1st Workshop on SErverless Systems, Applications and MEthodologies,
    Doi: 10.1145/3592533.3592807
    •

    2020

  • Isstaif, AAT., 2020. Self-managed services using MirageOS unikernels Middleware 2020 Doctoral Symposium Proceedings of the 2020 21st International Middleware Conference Doctoral Symposium Part of Middleware 2020,
    Doi: 10.1145/3429351.3431748
    •

    2018

  • Isstaif, AAT. and Alhafez, N., 2018. Performance Model of Apache Cassandra Under Heterogeneous Workload Using the Quantitative Verification Approach Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, v. 11178 LNCS
    Doi: 10.1007/978-3-030-02227-3_7
    •
    Read more at: Jan Blumenkamp

    Jan Blumenkamp

    Read more at: Marton Erdos

    Marton Erdos

    Read more at: Stefanos Bakirtzis

    Stefanos Bakirtzis

    Theses / dissertations

  • Bakirtzis, SS., 2024 (No publication date). Applications of Artificial Intelligence to Electromagnetism and Indoor Wireless Networks
    Doi: 10.17863/CAM.113346
    •

    Conference proceedings

  • Bakirtzis, S., Fiore, M. and Wassell, I., 2024 (Accepted for publication). Towards Physics-Informed Graph Neural Network-based Computational Electromagnetics
    Doi: 10.17863/CAM.108313
    •
  • Bakirtzis, S., Fiore, M. and Wassell, I., 2024. Towards Physics-Informed Graph Neural Network-based Computational Electromagnetics IEEE Antennas and Propagation Society AP S International Symposium Digest,
    Doi: 10.1109/AP-S/INC-USNC-URSI52054.2024.10686000
    •
  • Bakirtzis, S., Zanella, AF., Rubrichi, S., Ziemlicki, C., Smoreda, Z., Wassell, I., Zhang, J. and Fiore, M., 2023. Characterizing Mobile Service Demands at Indoor Cellular Networks Proceedings of the ACM SIGCOMM Internet Measurement Conference IMC,
    Doi: 10.1145/3618257.3624807
    •
  • Qiu, K., Bakirtzis, S., Wassell, IJ., Song, H., Lin, K. and Zhang, J., 2023. IRDM: A Generative Diffusion Model for Indoor Radio Map Interpolation. GLOBECOM,
    •
  • Qiu, K., Bakirtzis, S., Song, H., Wassell, IJ. and Zhang, J., 2023. Deep Learning-Based Path Loss Prediction for Outdoor Wireless Communication Systems. ICASSP,
    •
  • Bakirtzis, S., Wassell, IJ., Fiore, M. and Zhang, J., 2022. Stochastic Evaluation of Indoor Wireless Network Performance with Data-Driven Propagation Models. GLOBECOM,
    •
  • Bakirtzis, S., Wassell, I., Fiore, M. and Zhang, J., 2022. Stochastic Evaluation of Indoor Wireless Network Performance with Data-Driven Propagation Models Proceedings IEEE Global Communications Conference Globecom,
    Doi: 10.1109/GLOBECOM48099.2022.10001717
    •
  • Bakirtzis, S., Qiu, K., Zhang, J. and Wassell, I., 2021 (Accepted for publication). DeepRay: Deep Learning Meets Ray-Tracing 2022 16th European Conference on Antennas and Propagation, EuCAP 2022,
    Doi: 10.23919/EuCAP53622.2022.9769203
    •

    Journal articles

  • Bakirtzis, S., Wassell, I., Fiore, M. and Zhang, J., 2024. AI-Assisted Indoor Wireless Network Planning With Data-Driven Propagation Models IEEE Network, v. 38
    Doi: 10.1109/MNET.2024.3397801
    •
  • Ferreira, GO., Zanella, AF., Bakirtzis, S., Ravazzi, C., Dabbene, F., Calafiore, GC., Wassell, I., Zhang, J. and Fiore, M., 2024. A Joint Optimization Approach for Power-Efficient Heterogeneous OFDMA Radio Access Networks IEEE Journal on Selected Areas in Communications,
    Doi: 10.1109/JSAC.2024.3431524
    •
  • Bakirtzis, S., Chen, J., Qiu, K., Zhang, J. and Wassell, I., 2022. EM DeepRay: An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model IEEE Transactions on Antennas and Propagation,
    Doi: 10.1109/tap.2022.3172221
    •
  • Bakirtzis, S., Qiu, K., Wassell, I., Fiore, M. and Zhang, J., 2022. Deep Learning-based Multivariate Time Series Classification for Indoor/Outdoor Detection IEEE Internet of Things Journal,
    Doi: 10.1109/jiot.2022.3190555
    •
  • Qiu, K., Bakirtzis, S., Song, H., Zhang, J. and Wassell, I., 2022. Pseudo Ray-Tracing: Deep Leaning Assisted Outdoor mm-Wave Path Loss Prediction IEEE Wireless Communications Letters, v. 11
    Doi: 10.1109/LWC.2022.3175091
    •

    Datasets

  • Bakirtzis, S., Qiu, K., Wassell, I., Fiore, M. and Zhang, J., 2022. Research data supporting ''Deep Learning-based Multivariate Time Series Classification for Indoor Outdoor Detection"
    Doi: 10.17863/CAM.82668
    •
    Theses / dissertations

    2024 (No publication date)

  • Bakirtzis, SS., 2024 (No publication date). Applications of Artificial Intelligence to Electromagnetism and Indoor Wireless Networks
    Doi: 10.17863/CAM.113346
    •
    Conference proceedings

    2024 (Accepted for publication)

  • Bakirtzis, S., Fiore, M. and Wassell, I., 2024 (Accepted for publication). Towards Physics-Informed Graph Neural Network-based Computational Electromagnetics
    Doi: 10.17863/CAM.108313
    •

    2024

  • Bakirtzis, S., Fiore, M. and Wassell, I., 2024. Towards Physics-Informed Graph Neural Network-based Computational Electromagnetics IEEE Antennas and Propagation Society AP S International Symposium Digest,
    Doi: 10.1109/AP-S/INC-USNC-URSI52054.2024.10686000
    •

    2023

  • Bakirtzis, S., Zanella, AF., Rubrichi, S., Ziemlicki, C., Smoreda, Z., Wassell, I., Zhang, J. and Fiore, M., 2023. Characterizing Mobile Service Demands at Indoor Cellular Networks Proceedings of the ACM SIGCOMM Internet Measurement Conference IMC,
    Doi: 10.1145/3618257.3624807
    •
  • Qiu, K., Bakirtzis, S., Wassell, IJ., Song, H., Lin, K. and Zhang, J., 2023. IRDM: A Generative Diffusion Model for Indoor Radio Map Interpolation. GLOBECOM,
    •
  • Qiu, K., Bakirtzis, S., Song, H., Wassell, IJ. and Zhang, J., 2023. Deep Learning-Based Path Loss Prediction for Outdoor Wireless Communication Systems. ICASSP,
    •

    2022

  • Bakirtzis, S., Wassell, IJ., Fiore, M. and Zhang, J., 2022. Stochastic Evaluation of Indoor Wireless Network Performance with Data-Driven Propagation Models. GLOBECOM,
    •
  • Bakirtzis, S., Wassell, I., Fiore, M. and Zhang, J., 2022. Stochastic Evaluation of Indoor Wireless Network Performance with Data-Driven Propagation Models Proceedings IEEE Global Communications Conference Globecom,
    Doi: 10.1109/GLOBECOM48099.2022.10001717
    •

    2021 (Accepted for publication)

  • Bakirtzis, S., Qiu, K., Zhang, J. and Wassell, I., 2021 (Accepted for publication). DeepRay: Deep Learning Meets Ray-Tracing 2022 16th European Conference on Antennas and Propagation, EuCAP 2022,
    Doi: 10.23919/EuCAP53622.2022.9769203
    •
    Journal articles

    2024

  • Bakirtzis, S., Wassell, I., Fiore, M. and Zhang, J., 2024. AI-Assisted Indoor Wireless Network Planning With Data-Driven Propagation Models IEEE Network, v. 38
    Doi: 10.1109/MNET.2024.3397801
    •
  • Ferreira, GO., Zanella, AF., Bakirtzis, S., Ravazzi, C., Dabbene, F., Calafiore, GC., Wassell, I., Zhang, J. and Fiore, M., 2024. A Joint Optimization Approach for Power-Efficient Heterogeneous OFDMA Radio Access Networks IEEE Journal on Selected Areas in Communications,
    Doi: 10.1109/JSAC.2024.3431524
    •

    2022

  • Bakirtzis, S., Chen, J., Qiu, K., Zhang, J. and Wassell, I., 2022. EM DeepRay: An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model IEEE Transactions on Antennas and Propagation,
    Doi: 10.1109/tap.2022.3172221
    •
  • Bakirtzis, S., Qiu, K., Wassell, I., Fiore, M. and Zhang, J., 2022. Deep Learning-based Multivariate Time Series Classification for Indoor/Outdoor Detection IEEE Internet of Things Journal,
    Doi: 10.1109/jiot.2022.3190555
    •
  • Qiu, K., Bakirtzis, S., Song, H., Zhang, J. and Wassell, I., 2022. Pseudo Ray-Tracing: Deep Leaning Assisted Outdoor mm-Wave Path Loss Prediction IEEE Wireless Communications Letters, v. 11
    Doi: 10.1109/LWC.2022.3175091
    •
    Datasets

    2022

  • Bakirtzis, S., Qiu, K., Wassell, I., Fiore, M. and Zhang, J., 2022. Research data supporting ''Deep Learning-based Multivariate Time Series Classification for Indoor Outdoor Detection"
    Doi: 10.17863/CAM.82668
    •

    Department of Computer Science and Technology
    University of Cambridge
    William Gates Building
    15 JJ Thomson Avenue
    Cambridge
    CB3 0FD

    About the department

    Study here
    Research
    News
    Jobs
    How to get here
    About the department

    Contact us

    Website privacy policy

    Social media

    Athena Swan bronze award logo

    Study at Cambridge

    About the University

    Research at Cambridge