Scientific Articles

A Knowledge Distillation Framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image

Jwalin Bhatt, Yaroslav Zharov, Sungho Suh, Tilo Baumbach, Vincent Heuveline, and Paul Lukowicz

IEEE, International Symposium on Biomedical Imaging (ISBI), April 2023

Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation

Nicklas Boserup, Raghavendra Selvan

Northern Lights Deep Learning Conference, January 2023

Addressing Sustainable ML Life-cycles through Human-Centered Design

Eya Ben Chaaben, Janin Koch

HCI for Climate Change, April 2023

Latent Inspector: An Interactive Tool for Probing Neural Network Behaviors Through Arbitrary Latent Activation

Daniel Geißler, Bo Zhou, Paul Lukowicz

International Joint Conference for Artificial Intelligence (IJCAI), May 2023

FieldHAR: A Fully Integrated End-to-end RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors

Mengxi Liu, Bo Zhou, Zimin Zhao, Hyeonseok Hong, Hyun Kim, Sungho Suh, Vitor Fortes Rey, Paul Lukowicz

IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP23), July 2023

Energy Efficiency Impact of Processing in Memory: A Comprehensive Review of Workloads on the UPMEM Architecture

Yann Falevoz, Julien Legriel

Workshop on Performance and Energy-efficiency in Concurrent and Distributed Systems (PECS 2023, Co-located with Euro-PAR 2023), April 2024

Novel Adaptive Quantization Methodology for 8-bit Floating-Point DNN Training

Mohammad Hassani Sadi, Chirag Sudarshan, and Norbert Wehn

Springer Journal of Design Automation for Embedded Systems (2023), February 2024

CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition

M. Liu, Zimin Zhao, Daniel Geißler, Bo Zhou, Sungho Suh, Paul Lukowicz

AAAI 2024 Sustainable AI workshop, January 2024

The Power of Training: How Different Neural Network Setups Influence the Energy Demand

D. Geißler, Bo Zhou, Mengxi Liu, Sungho Suh, Paul Lukowicz

Journal of Imaging Neuroscience

Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging

Nicholas E. Souter, Loïc Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae

AAAI 2024 Sustainable AI workshop, January 2024
37th GI/ITG International Conference on Architecture of Computing Systems

Operating critical machine learning models in resource constrained regimes

Raghavendra Selvan, Julian Schön, Erik B Dam

Resource Efficient Medical Image Analysis Workshop at MICCAI2023, February 2024

EC-NAS: Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search

Pedram Bakhtiarifard, Christian Igel, Raghavendra Selvan

International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), April 2024

Activation Compression of Graph Neural Networks using Block-wise Quantization with Improved Variance Minimization

Sebastian Eliassen, Raghavendra Selvan

International Conference on Acoustics, Speech, and Signal Processing (ICASSP), January 2024

Probabilistic feature matching for fast scalable visual prompting

Thomas Frick, Cezary Skura, Filip M. Janicki, Roy Assaf, Niccolo Avogaro, Daniel Caraballo, Yagmur G. Cinar, Brown Ebouky, Ioana Giurgiu, Takayuki Katsuki, Piotr Kluska, Cristiano Malossi, Haoxiang Qiu, Tomoya Sakai, Florian Scheidegger, Andrej Simeski, Daniel Yang, Andrea Bartezzaghi , Mattia Rigotti

International Joint Conferences on Artificial Intelligence (IJCAI), August 2024

Adaptive Conformal Regression with Jackknife+ Rescaled Scores

N. Deutschmann M. Rigotti, M. Rodriguez Martinez

Transactions on Machine Learning Research (TMLR), April 2024

Mixed selectivity: Cellular computations for complexity

KM Tye, EK Miller, FH Taschbach, MK Benna, M Rigotti, S Fusi

Neuron, July 2024

Energy-Efficient, Low-Latency and Non-contact Eye Blink Detection with Capacitive Sensing

Mengxi Liu, Sizhen Bian, Zimin Zhao, Bo Zhou, Paul Lukowicz

Frontiers in Computer Science, June 2024

Show or Tell? Effectively prompting Vision-Language Models for semantic segmentation

Niccolo Avogaro, Thomas Frick, Mattia Rigotti, Andrea Bartezzaghi, Filip Janicki, Cristiano Malossi, Konrad Schindler, Roy Assaf

Cornell University, March 2025

PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning

Raghavendra Selvan Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B Dam

Northern Lights Deep Learning Conference (NLDL), March 2024

Is Adversarial Training with Compressed Datasets Effective?

Tong Chen, Raghavendra Selvan

IEEE Conference on Secure and Trustworthy Machine Learning (SATML), June 2025

Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI

Dustin Wright, Gabrielle Samuel, Christian Igel, Raghavendra Selvan

Communications of ACM, June 2025

Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging

Nicholas E. Souter, Loïc Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae

Journal of Imaging Neuroscience, December 2023

BMRS: Bayesian Model Reduction for Structured Pruning

Nicholas E. Souter, Loïc Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae

38th Conference on Neural Information Processing Systems (NeurIPS), 2024

“Should I choose a smaller model?”: Understanding ML Model Selection and Its Impact on Sustainability

Eya Ben Chaaben, Janin Koch, Wendy Mackay

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, April 2025

PIM-AI: A Novel Architecture for High-Efficiency LLM Inference

Cristobal Ortega, Yann Falevoz, Renaud Ayrignac

November 2024

Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study

Mengxi Liu, Daniel Geißler, Sizhen Bian, Bo Zhou, Paul Lukowicz

2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), January 2025

Initial Investigation of Kolmogorov-Arnold Networks (KANs) as Feature Extractors for IMU Based Human Activity Recognition

Mengxi Liu, Daniel Geißler, Dominique Nshimyimana, Sizhen Bian, Bo Zhou, Paul Lukowicz

UbiComp '24: Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing, June 2024

Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency

Hallgrimur Thorsteinsson, Valdemar J Henriksen, Tong Chen, Raghavendra Selvan

March 2024

Human in the Latent Loop (HILL): Interactively Guiding Model Training Through Human Intuition

Daniel GEISSLER,Lars KRUPP, Vishal BANWARI,David HABUSCH, Bo ZHOU, Paul LUKOWICZ, Jakob KAROLUS

Proceedings of the 4th International Conference on Hybrid Human-Artificial Intelligence (HHAI 2025), May 2025

The Role of Design in the Future of Human-AI Interaction

Janin Koch, Wendy E. Mackay & Albrecht Schmidt

AAR Adjunct '25: Adjunct Proceedings of the Sixth Decennial Aarhus Conference: Computing X Crisis, August 2025

Talk2X--An Open-Source Toolkit Facilitating Deployment of LLM-Powered Chatbots on the Web

L Krupp, D Geißler, P Hevesi, M Hirsch, P Lukowicz, J Karolus

April 2025

How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About It

Nanna Inie, Jeanette Falk, Raghavendra Selvan

CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, April 2025

When Can Memorization Improve Fairness?

Bob Pepin, Christian Igel, Raghavendra Selvan

December 2024

Challenges and Opportunities of Moderating Usage of Large Language Models in Education

Bob Pepin, Christian Igel, Raghavendra Selvan

MUM '24: Proceedings of the International Conference on Mobile and Ubiquitous Multimedia, December 2024

A Case Study on Energy-Efficient Edge AI Crack Segmentation

Matthias Tschope, Mohamed Moursi, Vladimir Rybalkin, Bo Zhou, Norbert Wehn, Paul Lukowicz

IEEE Splitech 2026