You can also find my articles on my Google Scholar profile

Books

• Laura Isabel Galindez Olascoaga, Wannes Meert, and Marian Verhelst. Hardware-Aware Probabilistic Machine Learning Models. Springer, 2021.

Journal Publications

• Shah, Nimish, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, and Marian Verhelst. DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. in IEEE Journal of Solid-State Circuits (2021).
• Laura Galindez, Komail Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst, Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification, in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2018, Vol. 8, iss. 4, pp. 858 - 872

Conference Publications

• Accepted for publication: Alisha Menon, Anirudh Natarajan, Laura I. Galindez Olascoaga, Youbin Kim, Braeden Benedict and Jan M. Rabaey. On the Role of Hyperdimensional Computing for Behavioral Prioritization in Reactive Robot Navigation Tasks. IEEE International Conference on Robotics and Automation (ICRA 2022).
• Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, and Marian Verhelst. 9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. In 2021 IEEE International Solid-State Circuits Conference (ISSCC), vol. 64, pp. 150-152. IEEE, 2021.
• Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, and Marian Verhelst. Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. In IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning, pp. 283-295. Springer, Cham, 2020.
• Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert, and Marian Verhelst. Acceleration of probabilistic reasoning through custom processor architecture. In 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 322-325. IEEE, 2020.
• Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst, Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams, accepted for publication in Proceedings of Symposium on Intelligent Data Analysis (IDA), 2020.
• Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck, Towards Hardware-Aware Tractable Learning of Probabilistic Models, in Proceedings of Advances in Neural Information Processing Systems 32 (NeurIPS), 2019
• Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst, ProbLP: A framework for low-precision probabilistic inference, in Proceedings of the 56th Annual Design Automation Conference 2019, 2019, pp. 190:1 - 6
• Laura I. Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst, Feature Noise Tuning for Resource Efficient Bayesian Network Classifiers, in Proceedings of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) 2018, pp. 147 - 152
• Martin Andraud, Laura Galindez, Yichuan Lu, Yiorgos Makris, Marian Verhelst, On the use of Bayesian Networks for Resource-Efficient Self-Calibration of Analog/RF ICs, in Proceedings of IEEE INTERNATIONAL TEST CONFERENCE (ITC), 2018, Vol. 2018-October, pp. -
• Laura I. Galindez Olascoaga, Komail Badami, Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst, Exploiting System Configurability towards Dynamic Accuracy-Power Trade-offs in Sensor Front-ends, in Proceedings of 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, 2016, pp. 1027 - 1031
• Laura I. Galindez Olascoaga,Wannes Meert, Herman Bruyninckx, Marian Verhelst, Extending naive Bayes with precision-tunable feature variables for resource-efficient sensor fusion, in Proceedings of CEUR Workshop Proceedings, 2016, Vol. 1724, pp. 23 - 30

Workshops

• Laura Isabel Galindez Olascoaga, Alisha Menon, Mohamed Ibrahim, and Jan Rabaey. A Brain-Inspired Hierarchical Reasoning Framework for Cognition-Augmented Prosthetic Grasping In Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations. , AAAI 2021.
• Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst, On hardware-aware probabilistic frameworks for resource constrained embedded applications, in Proceedings of 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing, Co-located with the 33rd Conference on Neural Information Processing Systems NeurIPS 2019, Vancouver, Canada, 2019.
• Shah Nimish, Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst, PRU: Probabilistic Reasoning processing Unit for resource-efficient AI, presented at Hot Chips: A Symposium on High Performance Chips, 2019, Palo alto, California, United States.
• Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst, Guy Van den Broeck, Towards Hardware-Aware Tractable Learning of Probabilistic Models (workshop version), presented at 3rd Tractable Probabilistic Modeling Workshop colocated with the 36th International Conference on Machine Learning (TPM-ICML 2019), Long Beach, California, United States, 2019