DeepVentilation: Learning to Predict Physical Effort from Breathing. - Sagar Sen; Pierre Bernabé; Erik Johannes B. L. G. Husom (IJCAI, 2020)

On The Reliability Of Machine Learning Applications In Manufacturing Environments. - Nicolas Jourdan 001; Sagar Sen; Erik Johannes Husom; Enrique Garcia-Ceja; Tobias Biegel; Joachim Metternich (CoRR, 2021)

UDAVA: an unsupervised learning pipeline for sensor data validation in manufacturing. - Erik Johannes Husom; Simeon Tverdal; Arda Goknil; Sagar Sen (CAIN, 2022)

Machine Learning for Fatigue Detection using Fitbit Fitness Trackers. - Erik Johannes Husom; Rustem Dautov; Adela-Aniela Nedisan; Fotis Gonidis; Spyridon Papatzelos; Nikolaos Malamas (icSPORTS, 2022)

Bridging the Gap Between Java and Python in Mobile Software Development to Enable MLOps. - Rustem Dautov; Erik Johannes Husom; Fotis Gonidis; Spyridon Papatzelos; Nikolaos Malamas (WiMob, 2022)

Taming Data Quality in AI-Enabled Industrial Internet of Things. - Sagar Sen; Erik Johannes Husom; Arda Goknil; Simeon Tverdal; Phu Hong Nguyen; Iker Mancisidor (IEEE Softw., 2022)

Replay-Driven Continual Learning for the Industrial Internet of Things. - Sagar Sen; Simon Myklebust Nielsen; Erik Johannes Husom; Arda Goknil; Simeon Tverdal; Leonardo Sastoque Pinilla (CAIN, 2023)

Towards Community-Driven Generative AI. - Rustem Dautov; Erik Johannes Husom; Sagar Sen; Hui Song (FedCSIS (Position Papers), 2023)

Automated Behavior Labeling for IIoT Data. - Erik Johannes Husom; Arda Goknil; Simeon Tverdal; Sagar Sen; Phu Hong Nguyen (IoT, 2023)

REPTILE: a Tool for Replay-driven Continual Learning in IIoT. - Erik Johannes Husom; Sagar Sen; Arda Goknil; Simeon Tverdal; Phu Hong Nguyen (IoT, 2023)

Edge-based Data Profiling and Repair as a Service for IoT. - Simeon Tverdal; Arda Goknil; Phu Hong Nguyen; Erik Johannes Husom; Sagar Sen; Jan Ruh; Francesca Flamigni (IoT, 2023)

AutoConf: Automated Configuration of Unsupervised Learning Systems Using Metamorphic Testing and Bayesian Optimization. - Lwin Khin Shar; Arda Goknil; Erik Johannes Husom; Sagar Sen; Yan Naing Tun; Kisub Kim (ASE, 2023)

A blockchain-based framework for trusted quality data sharing towards zero-defect manufacturing. - Mauro Isaja; Phu Hong Nguyen; Arda Goknil; Sagar Sen; Erik Johannes Husom; Simeon Tverdal; Abhilash Anand; Yunman Jiang; Karl John Pedersen; Per Myrseth; Jørgen Stang; Harris Niavis; et al. (Comput. Ind., 2023)

Virtual sensors for erroneous data repair in manufacturing a machine learning pipeline. - Sagar Sen; Erik Johannes Husom; Arda Goknil; Dimitra Politaki; Simeon Tverdal; Phu Hong Nguyen; Nicolas Jourdan 001 (Comput. Ind., 2023)

Engineering Carbon Emission-aware Machine Learning Pipelines. - Erik Johannes Husom; Sagar Sen; Arda Goknil (CAIN, 2024)

INTEND: Intent-Based Data Operation in the Computing Continuum. - Donatella Firmani; Francesco Leotta; Jerin George Mathew; Jacopo Rossi; Lorenzo Balzotti; Hui Song; Dumitru Roman; Rustem Dautov; Erik Johannes Husom; Sagar Sen; Vilija Balionyte-Merle; Andrea Morichetta 002; et al. (CAiSE Research Projects Exhibition, 2024)

Data Quality as a Service Framework for AI-Enabled Industrial Internet of Things. - Arda Goknil; Phu Hong Nguyen; Erik Johannes Husom; Sagar Sen; Simeon Tverdal; Flavien Peysson; Dimitra Politaki; Roberto González-Velázquez (IoT, 2024)

Latency-Aware Node Selection in Federated Learning. - Rustem Dautov; Erik Johannes Husom (IFIP Networking, 2024)

Drowsiness Detection Using Federated Learning: Lessons Learnt from Dealing with Non-IID Data. - Rustem Dautov; Erik Johannes Husom (PETRA, 2024)

INTEND: Human-Like Intelligence for Intent-Based Data Operations in the Cognitive Computing Continuum. - Rustem Dautov; Hui Song; Dumitru Roman; Erik Johannes Husom; Sagar Sen; Vilija Balionyte-Merle; Donatella Firmani; Francesco Leotta; Jerin George Mathew; Jacopo Rossi; Lorenzo Balzotti; Andrea Morichetta 002; et al. (RuleML+RR (Companion), 2024)

Raft Protocol for Fault Tolerance and Self-Recovery in Federated Learning. - Rustem Dautov; Erik Johannes Husom (SEAMS@ICSE, 2024)

The Price of Prompting: Profiling Energy Use in Large Language Models Inference. - Erik Johannes Husom; Arda Goknil; Lwin Khin Shar; Sagar Sen (CoRR, 2024)

Uncertainty-Aware Virtual Sensors for Cyber-Physical Systems. - Sagar Sen; Erik Johannes Husom; Arda Goknil; Simeon Tverdal; Phu Hong Nguyen (IEEE Softw., 2024)

ERG-AI: enhancing occupational ergonomics with uncertainty-aware ML and LLM feedback. - Sagar Sen; Victor Gonzalez; Erik Johannes Husom; Simeon Tverdal; Shukun Tokas; Svein O. Tjøsvoll (Appl. Intell., 2024)

3D-DaVa: Enhancing 3D Point Cloud Data Reliability for Industrial Applications. - Adela Nedisan Videsjorden; Arda Goknil; Sagar Sen; Erik Johannes Husom; Phu Hong Nguyen (ACM J. Data Inf. Qual., 2025)

Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency. - Erik Johannes Husom; Arda Goknil; Merve Astekin; Lwin Khin Shar; Andre Kåsen; Sagar Sen; Benedikt Andreas Mithassel; Ahmet Soylu (CoRR, 2025)