About
Research at the intersection of artificial intelligence, physics, and stochastic modelling
Shailendra Bhandari is a PhD Candidate in Artificial Intelligence at Oslo Metropolitan University. His research focuses on computational models of eye movements and visual behaviour, with broader interests in stochastic processes, evolutionary computation, and quantum information.
Research statement
From measured trajectories to interpretable dynamics
The research develops computational methods for modelling eye movements as structured time series, using deep generative models, spectral representations, intermittent-search models, Lévy walks, and related stochastic processes.
A central aim is to connect data-driven modelling with interpretable dynamical descriptions of visual behaviour. This includes synthetic gaze generation, fixation and saccade identification, time-series imaging, and statistical tools for analysing behavioural trajectories.
A complementary line of work addresses evolutionary and quantum computation, including the design of robust quantum circuits and computational structures through evolutionary search.
Education
Academic background
Training spanning artificial intelligence, data science, nuclear physics, statistics, and mathematics.
- 2023–present
PhD Candidate, Artificial Intelligence
OsloMet · Oslo Metropolitan University
Generative and stochastic modelling of eye-tracking time series and behavioural dynamics.
- 2021–2023
MSc, Applied Computer and Information Technology · Data Science
OsloMet · Oslo Metropolitan University
- 2019–2021
MSc, Nuclear and Energy Physics
University of Oslo
- 2014–2018
BSc, Physics, Statistics, and Mathematics
Tribhuvan University · Tri-Chandra Multiple Campus
Research areas
Methods and domains
Eye-tracking and gaze dynamics
Gaze velocity, fixation and saccade dynamics, behavioural time series, and data-driven markers.
Stochastic processes
Intermittent search, Lévy walks, foraging dynamics, return intervals, and jump-diffusion models.
Generative modelling
GANs, diffusion models, spectral constraints, synthetic trajectories, and distributional evaluation.
Quantum and evolutionary computation
Evolutionary circuit design, quantum information, entanglement, and computational structure.
Academic service & leadership
Service to the research community
Conference organisation, research-school representation, and service to the doctoral community.
Publicity Chair · IEEE QAI 2027
3rd IEEE International Conference on Quantum Artificial Intelligence, Oslo, Norway, 7–9 September 2027.
Conference website ↗Student Council Member · NORA-Tech
OsloMet representative on the NORA-Tech Research School Student Council, supporting the national PhD research community.
NORA-Tech Student Council ↗Election Committee Member · SiN 2026
Served on the election committee of the Association of Doctoral Organisations in Norway (SiN) in 2026.
SiN website ↗Science communication
QubitInk
QubitInk is a visual science-communication project devoted to quantum computing and quantum information, with mathematical ideas developed through clear narration and animation.
