Who? Martin Andraud

What? Assistant professor

Where? UCLouvain (BE) & Aalto University (FI)

Contact? martin.andraud [at] uclouvain [.] be

Research interests

Processors (accelerators) for edge AI 85%
Accelerators for Hybrid AI (probabilistic, neurosymbolic) 95%
test and reliability of AI accelerator SoCs 50%
About me

I am an assistant professor at UCLouvain, Belgium, since January 2024, and a visting professor at Aalto University, Finland. My research interestsresearch interests include ASIC design for hybrid AI tasks (e.g., deep learning, neurosymbolic AI, or probabilistic AI) and hardware/software co-design, test, and reliability of custom ASICs for digital or mixed-signal AI acceleration.

I obtained my doctoral degree in TIMA lab, Grenoble-Alpes University, France, in 2016, supervised by Emmanuel Simeu and Haralampos Stratigopoulos. I then worked as a post-doc successively in TU Eindhoven and KU Leuven from 2016 to 2019. Prior to joining UCLouvain in 2024, I was an assistant professor at Aalto University between 2019 and 2023.

I am always interested in collaborating, please do not hesitate to get in touch.

Fresh In

Paper accepted at TVLSI 2024

Our paper "A 22nm All-Digital Time-Domain Neural Network Accelerator for Precision In-Sensor Processing" ( with Ahmed Mohey, Jelin Leslin, Gaurav Singh, Marko Kosunen and Jussi Ryynänen) has been accepted in IEEE Transactions on VLSI.

Paper accepted at UAI 2024

Our paper "On Hardware-efficient Inference in Probabilistic Circuits" ( with Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh, Peng Zhang, and Karthekeyan Periasamy) has been accepted at the UAI conference, which will be held in July 2024. Blog info will follow.

I started at UCLouvain!

Pretty big news, I officially started in January 2024 as an assistant professor at UCLouvain, in Belgium. I will continue my work at Aalto as a visiting professor, stay tuned!

Open Positions

Open Positions

Doctoral candidate in IC design for heterogenous AI accelerators

Open PhD Position

Martin A.
06.03.2025

Latest publications

You can find me on Google scholar

Peer-reviewed journals

(J8) Ahmed M. Mohey, Jelin Leslin, Gaurav Singh, Marko Kosunen, Jussi Ryynänen, Martin Andraud, “A 22nm All-Digital Time-Domain Neural Network Accelerator for Precision In-Sensor Processing”, IEEE Transactions on VLSI, 2024.

Peer-reviewed conferences

(C23) J. Leslin, M. Trapp, M. Andraud, “Mixed precision HW acceleration in PCs”, the IoT, Edge, and Mobile for Embedded Machine Learning workshop, co-located with The European Conference in Machine Learning, 2024.

(C22) K. Periasamy, J. Leslin, A. Korsman, L. Yao and M. Andraud, "AutoPC: An Open-Source Framework for Efficient Probabilistic Reasoning on FPGA Hardware," 2024 22nd IEEE Interregional NEWCAS Conference (NEWCAS), 2024.

(C21) L. Yao, M. Trapp, J. Leslin, G. Singh, P. Zhang, K. Periasamy, M. Andraud, “On Hardware-efficient Inference in Probabilistic Circuits”, the 40th Conference on Uncertainty in Artificial Intelligence, 2024.

(C20) G. Singh, O. Numan, D. Monga, M. Andraud and K. Halonen, "On-chip Built-In Self-Calibration of Thermal Variations for Mixed-Signal In-Memory Computing," 2024 IEEE European Test Symposium (ETS), The Hague, Netherlands, 2024.

Other contributions

(O3) L. Yao, M. Trapp, K. Periasamy, J. Leslin, G. Singh, M. Andraud, “Logarithm-Approximate Floating-Point Multiplier for Hardware-efficient Inference in Probabilistic Circuits”, 6th workshop on Tractable Probabilistic Modelling, collocated with the Uncertainty in Artificial Intelligence (UAI) conference, August 2023

Sponsored research

FAMES Pilot Line

EU - Region Wallone / 2024-2029

Keywords : AI accelerator, analog computing, Emerging memories

(SustAIn) Smart Building Sensitive to Daily Sentiment

EU EiC Pathfinder project | 2022-2026

Keywords : Autonomous sensor nodes, distributed intelligence, AI accelerators, probabilistic models, probabilistic circuits, self-adaptive circuits

(A-core) Aalto RISC-V processor core with embedded AI accelerators

Internal collaboration / 2021-...

Keywords : AI accelerators, In-memory Computing, RISC-V processor

(WHISTLE) When integrated systems gain life experience: towards self-learning circuits with resource-efficient embedded artificial intelligence

Academy of Finland | 2020-2024

Keywords : Probabilistic models, probabilistic circuits, self-adaptive circuits, self-learning circuits

(DIFFER) Digital-intensive IC sensor interface for frequency-modulated gyroscopes

Industry collaboration / 2021-2023

Keywords : Sensor interface, IC design, time-based circuits

(PiCo) Processing in contact, High Density, Ultra Low Power Computing Element

Industry collaboration / 2020-2022

Keywords : AI accelerator, convolutional neural networks, analog computing

(ferrARI) Ferroelectric-enhanced Analog accelerators for Robust, ultra-low power edge Intelligence.

Finnish Research Council / 2024-2027

Keywords : AI accelerator, analog computing, Emerging memories

Blog

Papers we write

Monga et al., ISCAS'23

A temperature and process compensation circuit for resistive-based in-memory computing arrays" By Dipesh Monga et al., ISCAS'23

Martin A.
10.07.2023
Papers I Read

TeAAL

"TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators", by Nandeeka Nayak et al.

Martin A.
10.07.2023

Team

Current post-doctoral researchers

Gaurav Singh (UCL) “Reliable mixed-signal Compute-in-Memory Accelerators with emerging memory technologies (FAMES) ” - Starting date: December 2024

Current PhD researchers

Kazybek Adam (AAL) (Supervisor), “In Memory Computing architecture for fully-analog on-chip machine learning accelerators”. Starting date: Oct. 2020

Jelin Leslin (AAL) (Supervisor), “Probabilistic Machine Learning Hardware Architectures towards Self Learning Edge AI”. Starting date: May 2021

Ahmed Mohey (AAL) (Supervisor), “Integrated Circuit (IC) Architectures for Novel Time-Based Sensor Interfaces”. Starting date: September 2021

Lingyun Yao (AAL) (Supervisor). “Hardware-accelerated Probabilistic circuits for probabilistic edge AI”. Starting date: October 2022

Omar Numan (AAL) (Advisor, supervisor Prof. Kari Halonen), “Design of analog and analog-mixed-signal integrated-circuits for analog in-memory computing for AI applications”. Starting date: November 2020

Gaurav Singh (AAL) (Advisor, supervisor Prof. Kari Halonen) “Signal processing enabled system-on-chip for wireless-transfer of critical sensor data at low power” - Starting date: January 2019

Previous doctoral students

Karthekeyan Periasamy (AAL) (Supervisor), “Custom hardware accelerators for on-chip probabilistic machine learning”. Apr. 2021 - Feb. 2025 (Defense Pending). Current position: SoC designer, Nokia Finland

Current master thesis students