Behavioral selection in domestic assistance robots: A comparison of different methods for optimization of utility functions. - Jimmy Pettersson; David Sandberg; Krister Wolff; Mattias Wahde (SMC, 2006)

Evolutionary optimization of a bipedal gait in a physical robot. - Krister Wolff; David Sandberg; Mattias Wahde (IEEE Congress on Evolutionary Computation, 2008)

Particle swarm optimization of feedforward neural networks for the detection of drowsy driving. - David Sandberg; Mattias Wahde (IJCNN, 2008)

A Robot Localization Method Based on Laser Scan Matching. - David Sandberg; Krister Wolff; Mattias Wahde (FIRA, 2009)

An Algorithm for Sensory Area Coverage by Mobile Robots Operating in Complex Arenas. - Mattias Wahde; David Sandberg (FIRA, 2009)

Model-Based Video Coding Using Colour and Depth Cameras. - David Sandberg; Per-Erik Forssén; Jens Ogniewski (DICTA, 2011)

The performance of driver sleepiness indicators as a function of interval length. - David Sandberg (ITSC, 2011)

Detecting Driver Sleepiness Using Optimized Nonlinear Combinations of Sleepiness Indicators. - David Sandberg; Torbjörn Åkerstedt; Anna Anund; Göran Kecklund; Mattias Wahde (IEEE Trans. Intell. Transp. Syst., 2011)

Multi-Rate Uplink Channel Prediction and Enhanced Link Adaptation for VoLTE. - David Sandberg; Torbjörn Wigren (VTC Fall, 2015)

Narrowband Internet of Things 5G Performance. - Olof Liberg; Tuomas Tirronen; Y.-P. Eric Wang; Johan Bergman; Andreas Hoglund; Talha Khan; Gerardo Agni Medina-Acosta; Henrik Ryden; Antti Ratilainen; David Sandberg; Yutao Sui (VTC Fall, 2019)

Deep Reinforcement Learning for Dynamic Spectrum Sharing of LTE and NR. - Ursula Challita; David Sandberg (ICC, 2021)

Learning Robust Scheduling with Search and Attention. - David Sandberg; Tor Kvernvik; Francesco Davide Calabrese (ICC, 2022)

AI-Assisted Network Traffic Prediction Without Warm-Up Periods. - Amin Bolakhrif; Mustafa Özger; David Sandberg; Cicek Cavdar (VTC Spring, 2022)

Mobility, traffic and radio channel prediction: 5G and beyond applications. - Henrik Rydén; Alexandros Palaios; László Hévizi; David Sandberg; Tor Kvernvik; Hamed Farhadi (CoRR, 2022)

mmWave Beam Selection in Analog Beamforming Using Personalized Federated Learning. - Martin Isaksson; Filippo Vannella; David Sandberg; Rickard Cöster (CoRR, 2023)

Next Generation Mobile Networks' Enablers: Machine Learning-Assisted Mobility, Traffic, and Radio Channel Prediction. - Henrik Rydén; Hamed Farhadi; Alexandros Palaios; László Hévizi; David Sandberg; Tor Kvernvik (IEEE Commun. Mag., 2023)

Online Frequency Scheduling by Learning Parallel Actions. - Anastasios Giovanidis; Mathieu Leconte; Sabrine Aroua; Tor Kvernvik; David Sandberg (6GNet, 2024)

AI/ML-driven beamforming with imperfect channel state information for multi-user MIMO transmission. - Hamed Farhadi; Prayag Gowgi; David Sandberg (ICASSP Workshops, 2025)