@misc{basnet2026diffusion,
  author        = {Basnet, Laxman and Szorkovszky, Alexander and Lind, Pedro G. and Yazidi, Anis and Bhandari, Shailendra},
  title         = {Diffusion models for eye-gaze trajectory generation using position and velocity representations},
  year          = {2026},
  note          = {Submitted manuscript},
  eprint        = {2609.05522},
  archiveprefix = {arXiv},
  doi           = {10.48550/arXiv.2609.05522},
  url           = {https://doi.org/10.48550/arXiv.2609.05522}
}

@misc{bhandari2026evolutionary,
  author        = {Bhandari, Shailendra and Szorkovszky, Alex and Yazidi, Anis and Lind, Pedro G.},
  title         = {Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes},
  year          = {2026},
  note          = {Accepted at NeurIPS 2026},
  eprint        = {2609.39239},
  archiveprefix = {arXiv},
  url           = {https://evo-foraging.github.io/}
}

@misc{bhandari2026parwiswinnerdeterminationshoestring,
      title={PARWiS: Winner determination under shoestring budgets using active pairwise comparisons}, 
      author={Shailendra Bhandari},
      year={2026},
      eprint={2603.01171},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2603.01171}, 
}
@article{Mathema2026EyeGaze,
  author  = {Mathema, R. and Nav, S. M. and Bhandari, S. and others},
  title   = {Comprehensive dataset of features describing eye-gaze dynamics across multiple tasks},
  journal = {Scientific Data},
  year    = {2026},
  doi     = {10.1038/s41597-026-06754-x},
  url     = {https://doi.org/10.1038/s41597-026-06754-x},
  received = {2025-09-12},
  accepted = {2026-01-27},
  published = {2026-02-07}
}

@article{Orioma2026,
  author  = {Orioma, Charles and Krivan, Josef and Mathema, Rujeena and Lencastre, Pedro and Lind, Pedro G. and Szorkovszky, Alexander and Bhandari, Shailendra},
  title   = {Identification of fixations and saccades in eye-tracking data using adaptive threshold-based methods},
  journal = {The European Physical Journal Special Topics},
  year    = {2026},
  date    = {2026-05-07},
  issn    = {1951-6401},
  doi     = {10.1140/epjs/s11734-026-02324-9},
  url     = {https://doi.org/10.1140/epjs/s11734-026-02324-9}
}

@article{Budhathoki2026,
  author  = {Budhathoki, Anup and Gorj{\~a}o, Leonardo Rydin and Lind, Pedro G. and Bhandari, Shailendra},
  title   = {Jump-diffusion models of parametric volume--price distributions},
  journal = {The European Physical Journal Special Topics},
  year    = {2026},
  date    = {2026-05-07},
  issn    = {1951-6401},
  doi     = {10.1140/epjs/s11734-026-02323-w},
  url     = {https://doi.org/10.1140/epjs/s11734-026-02323-w}
}

@article{Bhandari2025Optimizing,
  author       = {Bhandari, Shailendra and Nichele, Stefano and Denysov, Sergiy and Lind, Pedro G.},
  title        = {Optimizing Quantum Circuits with Evolutionary Algorithms for Stable Boolean Gates,
                  Elementary Cellular Automata, and Highly Entangled Quantum States},
  journal      = {International Journal of Unconventional Computing},
  year         = {2025},
  volume       = {20},
  number       = {3},
  pages        = {225--257},
  doi          = {10.32908/ijuc.v20.270425},
  eprint       = {2408.00448},
  archivePrefix= {arXiv},
  primaryClass = {quant-ph},
  url          = {https://doi.org/10.48550/arXiv.2408.00448}
}


@INPROCEEDINGS{11228340,
  author={Lencastre, Pedro and Devkota, Ananta and Bhandari, Shailendra and Kuriakose, Bineeth and Lind, Pedro G.},
  booktitle={2025 International Joint Conference on Neural Networks (IJCNN)}, 
  title={Comparing eye-tracking time series imaging methods in ADHD screening}, 
  year={2025},
  volume={},
  number={},
  pages={1-7},
  keywords={Wavelet transforms;Visualization;Accuracy;Time series analysis;Neural networks;Imaging;Gaze tracking;Clinical trials;Convolutional neural networks;Usability;Eye-tracking;ADHD;Time-series;Imaging methods;CNN;Classification},
  doi={10.1109/IJCNN64981.2025.11228340},
  slides = {/assets/presentations/IJCNN_2025_presentation.pdf}
  }


@inproceedings{bhandari2022evolving,
  author = {Bhandari, Shailendra and Overskott, Sebastian and Adamopoulos, Ioannis and Lind, Pedro G. and Denysov, Sergiy and Nichele, Stefano},
  title = {Evolving Quantum Circuits to Implement Stochastic and Deterministic Cellular Automata Rules},
  booktitle = {Cellular Automata},
  year = {2022},
  editor = {Chopard, Bastien and Bandini, Stefania and Dennunzio, Alberto and Arabi Haddad, Mira},
  publisher = {Springer International Publishing},
  address = {Cham},
  pages = {119--129},
  doi = {10.1007/978-3-031-14926-9_11},
  isbn = {978-3-031-14926-9},
  slides = {/assets/presentations/ACRI_presentation.pdf},
  abstract = {The aim of this work is to generate specific rules of deterministic and stochastic cellular automata (CA) using the set of five quantum gates, which is known to generate any quantum circuit. To build such quantum circuits, we use an evolutionary algorithm, based in mutations, which allows the optimization of quantum gate types and their connectivity. The fitness function of the evolutionary algorithm aims at minimizing the difference between the output of the quantum circuit and the CA rule. We also inspect the differences observed when changing the number of gates and the mutation rate. We benchmark our methods with stochastic as well as deterministic CA rules, and briefly discuss the possible extensions their quantum ``cousins'' may enable.}
}

@misc{bhandari2023goal_specific,
  author = {Bhandari, Shailendra},
  title = {Building Goal-Specific Quantum Circuits with Evolutionary Algorithms},
  year = {2023},
  howpublished = {Master's thesis, OsloMet -- Oslo Metropolitan University},
  url = {https://hdl.handle.net/11250/3102558}
}

@inproceedings{bhandari2024modeling,
  author = {Bhandari, Shailendra and Lencastre, Pedro and Lind, Pedro},
  title = {Modeling Stochastic Eye Tracking Data: A Comparison of Quantum Generative Adversarial Networks and Markov Models},
  booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
  year = {2024},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  pages = {1934--1941},
  doi = {10.1145/3638530.3664134},
  isbn = {9798400704956},
  location = {Melbourne, VIC, Australia},
  series = {GECCO '24 Companion},
  keywords = {quantum generative adversarial networks QGANs, markov models, eye-tracking data},
  abstract = {We explore the use of quantum generative adversarial networks QGANs for modeling eye movement velocity data. We assess whether the advanced computational capabilities of QGANs can enhance the modeling of complex stochastic distribution beyond the traditional mathematical models, particularly the Markov model. The findings indicate that while QGANs demonstrate potential in approximating complex distributions, the Markov model consistently outperforms in accurately replicating the real data distribution. This comparison underlines the challenges and avenues for refinement in time series data generation using quantum computing techniques. It emphasizes the need for further optimization of quantum models to better align with real-world data characteristics.},
  slides    = {/assets/presentations/GECCO_2024_presentation.pdf}
}

@article{bhandari2025intlevpy,
  author = {Bhandari, Shailendra and Lencastre, Pedro and Denisov, Sergey and Bystryk, Yurii S. and Lind, Pedro G.},
  title = {IntLevPy: A Python Library to Classify and Model Intermittent and L{\'e}vy Processes},
  journal = {SoftwareX},
  volume = {31},
  pages = {102334},
  year = {2025},
  issn = {2352-7110},
  doi = {10.1016/j.softx.2025.102334},
  url = {https://www.sciencedirect.com/science/article/pii/S2352711025003000},
  keywords = {Intermittent processes, L{\'e}vy flights, Stochastic simulations},
  abstract = {IntLevPy provides a comprehensive description of the IntLevPy Package, a Python library designed for simulating and analyzing intermittent and L{\'e}vy processes. The package includes functionalities such as full parameter estimation and fitting optimization for both families of processes, as well as moment calculation, and classification methods. More specifically, as an optimized model for specific datasets, it retrieves the respective parameter values. As for the classification methodology, it utilizes adjusted-R$^2$ and an effective performance measure $\Gamma$, enabling the distinction between intermittent and L{\'e}vy processes. As a ready-to-use set of routines, it enables to compute statistical moments of stochastic data series and derive model fitting, integrating iterative parameter optimization with simulation-based validation. Moreover, we also address concrete use-cases, showing IntLevPy's application through synthetic and real-world eye-tracking data. The open-source package includes comprehensive unit tests for reliability, making it easily extensible. All in all, IntLevPy facilitates systematic exploration of these two broad classes of stochastic processes, bridging theoretical models and practical applications.}
}

@article{bhandari2025modeling,
  author = {Bhandari, Shailendra and Lencastre, Pedro and Mathema, Rujeena and Szorkovszky, Alexander and Yazidi, Anis and Lind, Pedro G.},
  title = {Modeling Eye Gaze Velocity Trajectories Using GANs with Spectral Loss for Enhanced Fidelity},
  journal = {Scientific Reports},
  volume = {15},
  pages = {19929},
  year = {2025},
  publisher = {Nature Publishing Group},
  doi = {10.1038/s41598-025-05286-5},
  url = {https://doi.org/10.1038/s41598-025-05286-5}
}

@article{bhandari2025optimizing,
  author = {Bhandari, Shailendra and Nichele, Stefano and Denysov, Sergiy and Lind, Pedro},
  title = {Optimizing Quantum Circuits with Evolutionary Algorithms for Stable Boolean Gates, Elementary Cellular Automata, and Highly Entangled Quantum States},
  journal = {International Journal of Unconventional Computing},
  volume = {20},
  number = {3},
  pages = {225--257},
  year = {2025},
  publisher = {Old City Publishing},
  doi = {10.32908/ijuc.v20.270425},
  url = {https://doi.org/10.32908/ijuc.v20.270425},
  institution = {OsloMet -- Oslo Metropolitan University},
  articleno = {270425}
}