World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
36
Citations
6313
World Ranking
5295
National Ranking
271

Overview

Ivan Glesk is affiliated with the University of Strathclyde in the United Kingdom. Their research primarily focuses on Engineering, with substantial contributions in Electrical and Electronic Engineering, Atomic and Molecular Physics and Optics, Artificial Intelligence, Building and Construction, and Renewable Energy, Sustainability and the Environment.

Their work covers several key topics, including:

  • Optical Network Technologies
  • Advanced Photonic Communication Systems
  • Photonic and Optical Devices
  • Advanced Fiber Optic Sensors
  • Advanced Fiber Laser Technologies
  • Building Energy and Comfort Optimization
  • Energy Efficiency and Management

Glesk has published extensively in several academic journals. The most frequent publication venues include:

  • Sensors
  • Applied Energy
  • Automation in Construction
  • Nanomaterials
  • Journal of Lightwave Technology

Among recent papers authored or co-authored by Glesk are:

  • Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making, 2020, Applied Energy
  • Data driven model improved by multi-objective optimisation for prediction of building energy loads, 2020, Automation in Construction
  • High-Efficiency Metamaterial-Engineered Grating Couplers for Silicon Nitride Photonics, 2024, Nanomaterials
  • Beyond 5G Fronthaul Based on FSO Using Spread Spectrum Codes and Graphene Modulators, 2023, Sensors
  • Impact of Wind Gust on High-Speed Characteristics of Polarization Mode Dispersion in Optical Power Ground Wire Cables, 2020, Sensors

Frequent co-authors collaborating with Glesk include:

  • Jozef Dubovan
  • Daniel Benedikovič
  • Anderson L. Sanches
  • Gabriel Cibira
  • Saleh Seyedzadeh

Best Publications

  • A terahertz optical asymmetric demultiplexer (TOAD)

    J.P. Sokoloff;P.R. Prucnal;I. Glesk;M. Kane

  • Machine learning for estimation of building energy consumption and performance: a review

    Saleh Seyedzadeh;Farzad Pour Rahimian;Ivan Glesk;Marc Roper

  • Tuning machine learning models for prediction of building energy loads

    Saleh Seyedzadeh;Farzad Pour Rahimian;Parag Rastogi;Ivan Glesk

  • A widely tunable narrow linewidth semiconductor fiber ring laser

    Deyu Zhou;P.R. Prucnal;I. Glesk

  • Demonstration of all-optical demultiplexing of TDM data at 250 Gbit/s

    I. Glesk;J. P. Sokoloff;P. R. Prucnal

  • All-optical data format conversion between RZ and NRZ based on a Mach-Zehnder interferometric wavelength converter

    Lei Xu;B.C. Wang;V. Baby;I. Glesk

  • All-optical address recognition and self-routing in a 250 Gbit/s packet-switched network

    I. Glesk;J. P. Solokoff;P. R. Prucnal

  • Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making

    Saleh Seyedzadeh;Farzad Pour Rahimian;Stephen Oliver;Sergio Rodriguez

  • Performance of a 50 Gbit/s optical time domain multiplexed system using a terahertz optical asymmetric demultiplexer

    J.P. Sokoloff;I. Glesk;P.R. Prucnal;R.K. Boncek

  • Comparison of Sagnac and Mach-Zehnder ultrafast all-optical interferometric switches based on a semiconductor resonant optical nonlinearity.

    K. I. Kang;T. G. Chang;I. Glesk;Paul Richard Prucnal

  • Observation of temporal vector soliton propagation and collision in birefringent fiber

    Darren Rand;Ivan Glesk;Camille Sophie Brès;Daniel A. Nolan

  • Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses

    Neha Mathur;Ivan Glesk;Arjan Buis

  • Subwavelength grating filtering devices.

    Junjia Wang;Ivan Glesk;Lawrence R. Chen

  • Subwavelength grating enabled on-chip ultra-compact optical true time delay line.

    Junjia Wang;Reza Ashrafi;Rhys Adams;Ivan Glesk

  • Data driven model improved by multi-objective optimisation for prediction of building energy loads

    Saleh Seyedzadeh;Farzad Pour Rahimian;Farzad Pour Rahimian;Stephen Oliver;Ivan Glesk

  • A novel fast optical switch based on two cascaded Terahertz Optical Asymmetric Demultiplexers (TOAD).

    Bing C. Wang;Varghese Baby;Wilson Tong;Lei Xu

  • Unbalanced TOAD for optical data and clock separation in self-clocked transparent OTDM networks

    K.-L. Deng;I. Glesk;K.I. Kang;P.R. Prucnal

  • Asymmetric optical loop mirror: analysis of an all-optical switch

    Michael G. Kane;Ivan Glesk;Jason P. Sokoloff;Paul R. Prucnal

  • Experimental demonstration and scalability analysis of a four-node 102-Gchip/s fast frequency-hopping time-spreading optical CDMA network

    V. Baby;I. Glesk;R.J. Runser;R. Fischer

  • Comparison of three nonlinear interferometric optical switch geometries

    Paul Toliver;Robert J. Runser;Ivan Glesk;Paul Richard Prucnal

  • Routing of 100 Gb/s words in a packet-switched optical networking demonstration (POND) node

    P. Toliver;I. Glesk;R.J. Runser;Kung-Li Deng

Frequent Co-Authors

Paul R. Prucnal
Paul R. Prucnal Princeton University
Ivan Andonovic
Ivan Andonovic University of Strathclyde
Lawrence R. Chen
Lawrence R. Chen McGill University
Michael J. Strain
Michael J. Strain University of Strathclyde
Ting Wang
Ting Wang Washington University in St. Louis
Ying-Sheng Huang
Ying-Sheng Huang National Taiwan University of Science and Technology
Stephen R. Forrest
Stephen R. Forrest University of Michigan–Ann Arbor
Fengnian Xia
Fengnian Xia Yale University
Alejandro Ortega-Moñux
Alejandro Ortega-Moñux University of Malaga
J-M. Fedeli
J-M. Fedeli CEA LETI

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