Dynamic Positioning Based on Voronoi Cells (DPVC). - HesamAddin Dashti; Nima Aghaeepour; Sahar Asadi; Meysam Bastani; Zahra Delafkar; Fatemeh Miri Disfani; Serveh Ghaderi; Shahin Kamali; Sepideh Pashami; Alireza Siahpirani (RoboCup, 2005)

ICT solutions supporting collaborative information acquisition, situation assessment and decision making in contemporary environmental management problems: the DIADEM approach. - Sahar Asadi; Costin Badica; Tina Comes; Claudine Conrado; Vanessa Evers; Frans C. A. Groen; Sorin Ilie; Jan Steen Jensen; Achim J. Lilienthal; Bianca Milan; Thomas Neidhart; Kees Nieuwenhuis; et al. (EnviroInfo, 2011)

Detecting Changes of a Distant Gas Source with an Array of MOX Gas Sensors. - Sepideh Pashami; Achim J. Lilienthal; Marco Trincavelli (Sensors, 2012)

TREFEX: Trend Estimation and Change Detection in the Response of MOX Gas Sensors. - Sepideh Pashami; Achim J. Lilienthal; Erik Schaffernicht; Marco Trincavelli (Sensors, 2013)

Change detection in metal oxide gas sensor signals for open sampling systems. - Sepideh Pashami (2015)

Supporting Analytical Reasoning - A Study from the Automotive Industry. - Tove Helldin; Maria Riveiro 001; Sepideh Pashami; Göran Falkman; Stefan Byttner; Slawomir Nowaczyk (HCI (5), 2016)

Multi-Task Representation Learning. - Mohamed-Rafik Bouguelia; Sepideh Pashami; Slawomir Nowaczyk (SAIS, 2017)

Exploring home robot capabilities by medium fidelity prototyping. - Martin Cooney; Sepideh Pashami; Yuantao Fan; Anita Pinheiro Sant'Anna; Yinrong Ma; Tianyi Zhang; Yuwei Zhao; Wolfgang Hotze; Jeremy Heyne; Cristofer Englund; Achim J. Lilienthal; Tom Ziemke (CoRR, 2017)

Pitfalls of Affective Computing: How can the automatic visual communication of emotions lead to harm, and what can be done to mitigate such risks. - Martin Cooney; Sepideh Pashami; Anita Pinheiro Sant'Anna; Yuantao Fan; Slawomir Nowaczyk (WWW (Companion Volume), 2018)

Mode tracking using multiple data streams. - Mohamed-Rafik Bouguelia; Alexander Karlsson; Sepideh Pashami; Slawomir Nowaczyk; Anders Holst (Inf. Fusion, 2018)

Learning Low-Dimensional Representation of Bivariate Histogram Data. - Evaldas Vaiciukynas; Matej Ulicny; Sepideh Pashami; Slawomir Nowaczyk (IEEE Trans. Intell. Transp. Syst., 2018)

Predicting Air Compressor Failures Using Long Short Term Memory Networks. - Kunru Chen; Sepideh Pashami; Yuantao Fan; Slawomir Nowaczyk (EPIA (1), 2019)

Warranty Claim Rate Prediction Using Logged Vehicle Data. - Reza Khoshkangini; Sepideh Pashami; Slawomir Nowaczyk (EPIA (1), 2019)

Eliciting Structures in Data. - Ahmad Al-Shishtawy; Juhee Bae; Mohamed-Rafik Bouguelia; Göran Falkman; Sarunas Girdzijauskas; Olof Gönerup; Anders Holst; Alexander Karlsson; Slawomir Nowaczyk; Sepideh Pashami; Alan Said; Amira A. Soliman El Hosary (IUI Workshops, 2019)

Incremental Causal Discovery and Visualization. - Anders Holst; Sepideh Pashami; Juhee Bae (IDM@WSDM, 2019)

Interactive feature extraction for diagnostic trouble codes in predictive maintenance: A case study from automotive domain. - Parivash Pirasteh; Slawomir Nowaczyk; Sepideh Pashami; Magnus Löwenadler; Klas Thunberg; Henrik Ydreskog; Peter Berck (IDM@WSDM, 2019)

IDM-WSDM 2019: Workshop on Interactive Data Mining. - Alan Said; Denis Parra; Juhee Bae; Sepideh Pashami (WSDM, 2019)

Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters: Using Clustering and Rule-Based Machine Learning. - Oskar Dahl; Fredrik Johansson; Reza Khoshkangini; Sepideh Pashami; Slawomir Nowaczyk; Pihl Claes (IMMS, 2020)

Decentralized and Adaptive K-Means Clustering for Non-IID Data Using HyperLogLog Counters. - Amira Soliman 001; Sarunas Girdzijauskas; Mohamed-Rafik Bouguelia; Sepideh Pashami; Slawomir Nowaczyk (PAKDD (1), 2020)

Forklift Truck Activity Recognition from CAN Data. - Kunru Chen; Sepideh Pashami; Slawomir Nowaczyk; Emilia Johansson; Gustav Sternelöv; Thorsteinn S. Rögnvaldsson (IoT Streams/ITEM@PKDD/ECML, 2020)

Avoiding Improper Treatment of Persons with Dementia by Care Robots. - Martin Cooney; Sepideh Pashami; Eric Järpe; Awais Ashfaq (CoRR, 2020)

Early Prediction of Quality Issues in Automotive Modern Industry. - Reza Khoshkangini; Peyman Sheikholharam Mashhadi; Peter Berck; Saeed Gholami Shahbandi; Sepideh Pashami; Slawomir Nowaczyk; Tobias Niklasson (Inf., 2020)

Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi (CEC, 2021)

Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses. - Mohammed Ghaith Altarabichi; Yuantao Fan; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk (DSAA, 2021)

COCLUBERT: Clustering Machine Learning Source Code. - Marcus Hägglund; Francisco J. Peña; Sepideh Pashami; Ahmad Al-Shishtawy; Amir Hossein Payberah (ICMLA, 2021)

AI in Smart Cities: Challenges and approaches to enable road vehicle automation and smart traffic control. - Cristofer Englund; Eren Erdal Aksoy; Fernando Alonso-Fernandez; Martin Daniel Cooney; Sepideh Pashami; Björn Åstrand (CoRR, 2021)

Parallel orthogonal deep neural network. - Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk; Sepideh Pashami (Neural Networks, 2021)

SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP. - Abdallah Alabdallah; Sepideh Pashami; Thorsteinn S. Rögnvaldsson; Mattias Ohlsson (DSAA, 2022)

A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set. - Narjes Davari; Sepideh Pashami; Bruno Veloso; Slawomir Nowaczyk; Yuantao Fan; Pedro Mota Pereira; Rita P. Ribeiro; João Gama 001 (IDA, 2022)

Towards Geometry-Preserving Domain Adaptation for Fault Identification. - Zahra Taghiyarrenani; Slawomir Nowaczyk; Sepideh Pashami; Mohamed-Rafik Bouguelia (PKDD/ECML Workshops (2), 2022)

Siambert: Siamese Bert-based Code Search. - Francisco J. Peña; Angel Luis Gonzalez; Sepideh Pashami; Ahmad Al-Shishtawy; Amir Hossein Payberah (SAIS, 2022)

An Explainable Knowledge-based AI Framework for Mobility as a Service. - Enayat Rajabi; Slawomir Nowaczyk; Sepideh Pashami; Magnus Bergquist (SEKE, 2022)

Why Is Multiclass Classification Hard? - Pablo del Moral; Slawomir Nowaczyk; Sepideh Pashami (IEEE Access, 2022)

Semi-Supervised Learning for Forklift Activity Recognition from Controller Area Network (CAN) Signals. - Kunru Chen; Thorsteinn S. Rögnvaldsson; Slawomir Nowaczyk; Sepideh Pashami; Emilia Johansson; Gustav Sternelöv (Sensors, 2022)

Towards Explainable Deep Domain Adaptation. - Szymon Bobek; Slawomir Nowaczyk; Sepideh Pashami; Zahra Taghiyarrenani; Grzegorz J. Nalepa (ECAI Workshops (1), 2023)

Toward Solving Domain Adaptation with Limited Source Labeled Data. - Kunru Chen; Thorsteinn S. Rögnvaldsson; Slawomir Nowaczyk; Sepideh Pashami; Jonas Klang; Gustav Sternelöv (ICDM (Workshops), 2023)

Component attention network for multimodal dance improvisation recognition. - Jia Fu 001; Jiarui Tan; Wenjie Yin; Sepideh Pashami; Mårten Björkman (ICMI, 2023)

XAI for Predictive Maintenance. - João Gama 001; Slawomir Nowaczyk; Sepideh Pashami; Rita P. Ribeiro; Grzegorz J. Nalepa; Bruno Veloso (KDD, 2023)

Why Industry 5.0 Needs XAI 2.0? - Szymon Bobek; Slawomir Nowaczyk; João Gama 001; Sepideh Pashami; Rita P. Ribeiro; Zahra Taghiyarrenani; Bruno Veloso; Lala H. Rajaoarisoa; Maciej Szelazek; Grzegorz J. Nalepa (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2023)

Explainable Predictive Maintenance. - Sepideh Pashami; Slawomir Nowaczyk; Yuantao Fan; Jakub Jakubowski; Nuno Paiva; Narjes Davari; Szymon Bobek; Samaneh Jamshidi; Hamid Sarmadi; Abdallah Alabdallah; Rita P. Ribeiro; Bruno Veloso; et al. (CoRR, 2023)

Heterogeneous Federated Learning via Personalized Generative Networks. - Zahra Taghiyarrenani; Abdallah Alabdallah; Slawomir Nowaczyk; Sepideh Pashami (CoRR, 2023)

Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles. - Yuantao Fan; Zhenkan Wang; Sepideh Pashami; Slawomir Nowaczyk; Henrik Ydreskog (CoRR, 2023)

Fast Genetic Algorithm for feature selection - A qualitative approximation approach. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi (Expert Syst. Appl., 2023)

Pitfalls of assessing extracted hierarchies for multi-class classification. - Pablo del Moral; Slawomir Nowaczyk; Anita Pinheiro Sant'Anna; Sepideh Pashami (Pattern Recognit., 2023)

Multi-domain adaptation for regression under conditional distribution shift. - Zahra Taghiyarrenani; Slawomir Nowaczyk; Sepideh Pashami; Mohamed-Rafik Bouguelia (Expert Syst. Appl., 2023)

Material handling machine activity recognition by context ensemble with gated recurrent units. - Kunru Chen; Thorsteinn S. Rögnvaldsson; Slawomir Nowaczyk; Sepideh Pashami; Jonas Klang; Gustav Sternelöv (Eng. Appl. Artif. Intell., 2023)

Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks. - Mohammed Ghaith Altarabichi; Abdallah Alabdallah; Sepideh Pashami; Thorsteinn S. Rögnvaldsson; Slawomir Nowaczyk; Mattias Ohlsson (GECCO Companion, 2024)

A Review of Randomness Techniques in Deep Neural Networks. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Julia Handl (GECCO Companion, 2024)

Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Bus Fleets. - Yuantao Fan; Mohammed Ghaith Altarabichi; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk (HAII5.0@ECAI, 2024)

Evaluating Multi-task Curriculum Learning for Forecasting Energy Consumption in Electric Heavy-duty Vehicles. - Yuantao Fan; Zhenkan Wang; Sepideh Pashami; Slawomir Nowaczyk (HAII5.0@ECAI, 2024)

Understanding Survival Models Through Counterfactual Explanations. - Abdallah Alabdallah; Jakub Jakubowski; Sepideh Pashami; Szymon Bobek; Mattias Ohlsson; Thorsteinn S. Rögnvaldsson; Grzegorz J. Nalepa (ICCS (4), 2024)

Mind the Data, Measuring the Performance Gap Between Tree Ensembles and Deep Learning on Tabular Data. - Axel Karlsson; Tianze Wang; Slawomir Nowaczyk; Sepideh Pashami; Sahar Asadi (IDA (1), 2024)

The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models. - Abdallah Alabdallah; Mattias Ohlsson; Sepideh Pashami; Thorsteinn S. Rögnvaldsson (Artif. Intell. Medicine, 2024)

Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey. - Jakub Jakubowski; Natalia Wojak-Strzelecka; Rita P. Ribeiro; Sepideh Pashami; Szymon Bobek; João Gama 001; Grzegorz J. Nalepa (CoRR, 2024)

CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis. - Abdallah Alabdallah; Omar Hamed; Mattias Ohlsson; Thorsteinn S. Rögnvaldsson; Sepideh Pashami (CoRR, 2024)

Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks. - Mohammed Ghaith Altarabichi; Slawomir Nowaczyk; Sepideh Pashami; Peyman Sheikholharam Mashhadi; Julia Handl (Inf. Sci., 2024)

Pragmatic Paradigm for Multi-stream Regression. - Nuwan Gunasekara; Slawomir Nowaczyk; Sepideh Pashami (IDA, 2025)

Assessing the Graph Structure Learning in Graph Deviation Networks. - Canberk Ozen; Slawomir Nowaczyk; Prayag Tiwari; Sepideh Pashami (IDA, 2025)

DiffPAD: Denoising Diffusion-Based Adversarial Patch Decontamination. - Jia Fu 001; Xiao Zhang; Sepideh Pashami; Fatemeh Rahimian; Anders Holst (WACV, 2025)

DiffCAP: Diffusion-based Cumulative Adversarial Purification for Vision Language Models. - Jia Fu 001; Yongtao Wu; Yihang Chen; Kunyu Peng; Xiao Zhang; Volkan Cevher; Sepideh Pashami; Anders Holst (CoRR, 2025)