I am Farzan, a third-year Computer Science Ph.D. candidate in the Department of Informatics at the University of Oslo. I am fortunate to be working with Prof. Jim Tørresen as part of the ROBIN group. I did my masters in Mechatronics Engineering from Air University, Islamabad, and worked with Prof. Noman Naseer. In the meanwhile, I was working as a Lab Engineer at the Dept. of Mechatronics Engineering.

My research goal is to build a predictive model from multi-sources of information to analyze the behavior and emotional state of the human for predicting future events or actions. The multi-modal multi-architectural deep learning approach would be useful to increase access to mental health services or to provide a better robot companion for elderly people. The study is focusing on analysis and modeling using data collected from different smartphone apps and sensors (wearable or ambient).

In the past, I worked on multi-robot patrolling of infrastructures, with an emphasis on robot perception methods for automatic detection and classification of abnormal situations and security threats in the context of infrastructure surveillance. I also worked with Brain-Computer Interface (BCI) during my masters focused on Optimal feature selection from functional near-infrared spectroscopy (fNIRS) signals using genetic algorithms for BCI.

    • My research publications on


Recent News


  • Paper accepted in "Journal of Neural Engineering" titled "Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis " (Impact Factor 4.14).


  • A dataset published in the "Proceedings of the 11th ACM Multimedia Systems Conference" titled "Toadstool: a dataset for training emotional intelligent machines playing Super Mario Bros".


  • Paper accepted in "IEEE International Conference on Ultra-wideband and ultra-short impulse signals " titled ""In-Home Emergency Detection Using An Ambient UltraWideband Radar Sensor and Deep Learning. September 21-25, 2020, Kharkiv, Ukraine


  • Paper accepted in "Journal of Healthcare Engineering" titled "Cortical Tasks-Based Optimal Filter Selection: An fNIRS Study " (Impact Factor 1.83).


  • Journal paper accepted based on Human Activity Recognition from Multiple Sensors Data Using Multi-Fusion Representations and CNN in "ACM Transactions on Multimedia Computing,Communications, and Applications (TOMM)", (Impact Factor 3.275).


  • Successfully defended my mid PhD evaluation.





  • Presented my work on sensor fusion in 2019 International Joint Conference on Neural Networks (IJCNN) at Budapest Hungry.


  • Presented my work in Scandinavian Conference on Image Analysis 2019 at Norrköping, Sweden.


  • Started Ph.D. at University of Oslo.


  • Journal Paper accepted in "Journal of NeuroEngineering and Rehabilitation" titled "fNIRS-based Neurorobotic Interface for gait rehabilitation".(Impact Factor 3.5)


  • A paper titled "On 3D Simulators for Multi-Robot Systems in ROS: MORSE or Gazebo?" in IEEE Proceedings International Symposium on Safety, Security and Rescue Robotics (SSRR) Shanghai, China, October 11-13, 2017



  • A paper titled "Enhancing Classification Performance of Functional Near-Infrared Spectroscopy- Brain–Computer Interface Using Adaptive Estimation of General Linear Model Coefficients" has been accepted for publication in Frontiers in Neurorobotics, Impact factor 2.48.


  • A paper titled "Optimal Feature Selection from fNIRS Signals using Genetic Algorithms for BCI" has been accepted for publication in Neuroscience Letters,Impact factor 2.10.




  • Travelled to Busan, Korea for extracting the brain signals using functional near-infrared spectroscopy(fNIRS). Availed

the opportunity to work on the DYNOT-232 (NIRx Medical Technologies, LLC.) and the Imagent (ISS, Champaign, Illinois).