Tareq Si Salem
Paris, France

Tareq Si Salem · Ph.D.

Applied research: theory meets practice

Machine learning. Mathematical modeling.
Senior researcher at Huawei Paris Research Center.

طارق سي سالم ⵜⴰⵔⵉⵇ ⵙⵉ ⵙⴰⵍⴻⵎ

Research perspective

Tareq Si Salem (طارق سي سالم, ⵜⴰⵔⵉⵇ ⵙⵉ ⵙⴰⵍⴻⵎ) is a senior researcher at Huawei Paris Research Center. He earned his Ph.D. in Computer Science (2022) from Université Côte d'Azur / Inria Sophia Antipolis with Giovanni Neglia, and held research positions at Northeastern University (with Stratis Ioannidis) and TU Delft (with George Iosifidis). His work spans machine learning and mathematical modeling, focusing on learning under constraints such as privacy, safety, fairness, memory, and communication. He has published in IEEE/ACM ToN, ACM SIGMETRICS, AAAI, and IEEE INFOCOM, and won the ITC'33 Best Paper Award (2021).

  • Online learning
  • Time-series forecasting
  • Constrained optimization
  • Machine learning systems

Selected publications

All publications ↗

Bandits in Flux: Dynamic Regret under Adversarial Constraints

Author: Tareq Si Salem

International Conference on Artificial Intelligence and Statistics (AISTATS), 2026

machine learning multi-armed bandits online learning dynamic regret non-stationary environments

Rebuttal

Goal-Oriented Time-Series Forecasting: Foundation Framework Design

Authors: Luca-Andrei Fechete, Mohamed Sana, Fadhel Ayed, Nicola Piovesan, Wenjie Li, Antonio De Domenico, Tareq Si Salem (lead researcher)

The AAAI Conf. on Artificial Intelligence (AAAI), Singapore, 2026 (A*, 17.6% AR)

machine learning multivariate time-series forecasting decision-centric forecasting inference-time task adaptation

Online Submodular Maximization via Online Convex Optimization

Authors: Tareq Si Salem, Gözde Özcan, Iasonas Nikolaou, Evimaria Terzi, Stratis Ioannidis

The AAAI Conf. on Artificial Intelligence (AAAI), Vancouver, Canada, 2024 (A*, 23% AR)

online learning bandits submodular optimization non-convex optimization

Enabling Long-term Fairness in Dynamic Resource Allocation

Authors: Tareq Si Salem, George Iosifidis, Giovanni Neglia

ACM International Conferences on Measurement and Modeling of Computer Systems (SIGMETRICS), Orlando, Florida, USA, 2023 (A*, 15% AR)

multi-criteria optimization axiomatic bargaining α-fairness resource allocation

Ascent Similarity Caching with Approximate Indexes

Authors: Tareq Si Salem, Giovanni Neglia, Damiano Carra

IEEE/ACM Transactions on Networking (ToN) (Best Paper ITC'33), 2022

information retrieval and ranking similarity search non-euclidean gradient methods

GRADES: Gradient Descent for Similarity Caching

Authors: Anirudh Sabnis, Tareq Si Salem, Giovanni Neglia, Michele Garetto, Emilio Leonardi, Ramesh K. Sitaraman

IEEE International Conferences on Computer Communications (INFOCOM), 2021 (A*, 19% AR)

machine learning systems similarity caching gradient methods

Mentorship

Students & interns

Current
  • M. DOROCH
    École Normale Supérieure Paris-Saclay / St. Petersburg State University. Co-supervised with EURECOM. Topic: Foundation Models for Time Series Modeling. CIFRE Ph.D., 2026–2029.
Past
  • D. KUSMANOV
    University College London, MSc Data Science and Machine Learning. Topic: Time Series Model Identification. Internship, June–September, 2026.
  • A. AGUERJOUT
    École Polytechnique, X2027. Topic: Time Series. Internship, June–September, 2026.
  • L. FECHETE
    École Polytechnique, BX 2025 → EPFL M.S. Statistics. Topic: Goal-oriented Forecasting; resulted in an AAAI A* paper (4 months, 2025).