Stochastic Numerics and Statistical Learning:
Theory and Applications Workshop 2026
ABOUT THE CONFERENCE
Update:
Due to international travel advisories, SNSL 2026 has transitioned to a fully online, highly interactive format. The scientific program remains rigorous, featuring live discussions and advance slide access.
The Stochastic Numerics and Statistical Learning Workshop 2026 will be held between November 22 and November 26. It will convene leading scholars in stochastic algorithms, numerical analysis, statistical learning, optimization, Bayesian inference, stochastic optimal control, quantitative finance, and data assimilation, as well as experts from focused application areas which are of crucial importance globally and in the Kingdom.
Poster Sessions
Updates coming soon
- The talks will be streamed on our official Zoom channel
- Previous talks and recorded poster presentations are available at the workshop's YouTube channel
AGENDA
13:45 - 14:00
Opening remarks
14:00 - 15:00
TBA
15:00 – 15:10
15:10 - 15:35
Dynamical low-rank ensemble Kalman filters for state and parameter identification
15:35 - 16:00
TBA
16:00 - 16:25
Quasi-Monte Carlo with A Hankel Random Digital Net
16:25 - 16:35
Poster Flash Reel 1
16:35 – 16:45
16:45 - 17:10
An Adjoint Method for Monte Carlo Simulation of the Boltzmann Equation
17:10 - 17:35
Operator-matched spatial regression
14:00 - 15:00
TBA
15:00 – 15:10
15:10 - 15:35
Generative modeling without neural networks
15:35 - 16:00
Fading Memory Signatures: A Universal Framework for Time Series Learning
16:00 - 16:25
Local regression on path-space
16:25 - 16:35
Poster Flash Reel 2
16:35 – 16:45
16:45 - 17:10
Score-based generative modeling via entire signature jump-diffusions
17:10 - 17:35
Solving LQ Stochastic Control Problems with Signatures
17:35 - 18:00
Weak error approximation for rough and Gaussian mean-reverting stochastic volatility models
14:00 - 15:00
TBA
15:00 – 15:10
15:10 - 15:35
Deterministic Score-Based Purification toward Flat Modes of the Data Distribution
15:35 - 16:00
TBA
16:00 - 16:25
Adaptive Random Fourier Features: Random Walk, Resampling, and Applications
16:25 - 16:35
Poster Flash Reel 3
16:35 – 16:45
16:45 - 17:10
Two-stage conditional-moment regression for SDE learning with adaptive random Fourier features
17:10 - 17:35
From scalar indices to a sensitivity field: locating regimes and transitions
17:35 - 18:00
Duality Methods in Stochastic Optimal Control
14:25 - 14:50
Sequential Entropic Optimal Transport for Bayesian Inverse Problems via Multilevel Monte Carlo
14:50 - 15:15
TBA
15:15 – 15:25
15:25 - 15:50
Hierarchical Importance Sampling for Estimating Occupation Times of SDE Solutions
15:50 - 16:15
Error estimates and adaptivity for optimal control problems
16:15 - 16:40
Adaptive numerical methods for the approximation of exploding, exiting, and reflecting dynamics
16:40 - 16:50
Poster Flash Reel 4
16:50 – 17:00
17:00 - 18:00
Interacting Particle Formulations for Stochastic Optimal Control
18:00 - 18:25
Strong Approximation of McKean–Vlasov SDEs with Generalized-Moment Interactions
14:00 - 15:00
MLMC analysis of the stochastic heat equation
15:00 – 15:10
15:10 - 15:35
Efficient nested integral estimation using median randomized quasi-Monte Carlo
15:35 - 16:00
Reliable and Efficient Pricing in the Rough Heston Model
16:00 - 16:25
Adaptive Variance Reduction in Stochastic Quasi-Newton Optimization
16:25 – 16:45
16:45 - 17:10
Uncertainty quantification analysis of bifurcations of the Allen-Cahn equation with random coefficients
17:10 - 17:35
Uncovering Implicit Beliefs Behind Decisions: Policies as Counterfactual Worlds
17:35 - 17:45
Closing remarks
PLAN YOUR VISIT
To help you prepare for your upcoming visit, we encourage you to review the key information and travel advice below.
Before travelling, please check the latest travel guidelines from your country’s embassy and consult your primary care provider about vaccinations or other health preparations.
King Abdullah University of Science & Technology
4700 King Abdullah University of Science and Technology
Thuwal 23955-6900
Kingdom of Saudi Arabia
We cannot accept responsibility for visa applications. If a delegate is unable to attend due to visa issues, our usual cancellation policy will apply. We recommend obtaining travel insurance for the duration of your visit.
GCC citizens
Do not need a visa. Passport must be valid for at least six months after your planned entry date.
eVisa
Available to many countries in Europe, North America, Oceania, and parts of Asia.
Delegates are responsible for booking and paying for their accommodation. Recommended hotels:
Boulevard, 7729 Bayt Al Hikma Blvd, Thuwal
5-min walk from KAUST
- Dress code: Conservative. Business or business casual. No abaya/headscarf required.
- Language: Arabic (official); English widely spoken.
- Weather: Around 35°C. Bring sunscreen, sunglasses, and a light jumper for indoors.
- Currency: Saudi Riyal (SAR). Credit cards widely accepted. ATMs available.
- Power sockets: Type G & C, 230V / 60Hz. Bring a universal adapter.
- Wi-Fi: Free Wi-Fi across KAUST campus.
- Water: Safe to drink from fountains. Tap water not recommended.
- Alcohol: Strictly prohibited.
More travel info: Visit Saudi
- Keep valuables out of sight
- Use reliable transport
- Travel with others, especially at night
- Stay alert in crowded public areas
- Shield your PIN when using ATMs
Emergency services: If you are within the KAUST campus and are in need of emergency services, call 911. For a full list of emergency numbers, visit this link HERE.
KAUST Centers of Excellence
KAUST Launches Four Pioneering Centers of Excellence to Address Key National and International Priorities
KAUST CORE LABS
KAUST hosts a wide range of sophisticated instruments and world-class facilities that students can access, including the Prototyping and Product Development Core Lab, and laboratories involving robotics and embedded systems, sensors, intelligent autonomous systems and biotechnology. Specific labs will be identified based on the curriculum and individual projects.
ABOUT KAUST
Established in 2009, King Abdullah University of Science and Technology (KAUST) is a graduate research university dedicated to addressing major scientific and technological challenges. It is recognized globally for excellence, ranked #1 worldwide in citations per faculty, #1 in Saudi Arabia and #1 in the Times Higher Education Arab University Rankings for both 2023 and 2024, and #4 in Western Asia according to Nature Index 2022. With a community representing over 120 nationalities, KAUST fosters international collaboration and advances research in health, environment, energy, and digital technologies, serving as a leading global center of knowledge. The university is ranked #112 globally, has achieved 17 years of excellence, and maintains Top-20 supercomputing performance.
CONTACT US
King Abdullah University of Science and Technology (KAUST)
4700 King Abdullah University of Science and Technology
Thuwal 23955-6900
Kingdom of Saudi Arabia
Follow us on Social media: