GrainSpeech preprint: compact speech synthesis with finer detail
Our new GrainSpeech arXiv preprint introduces a 264.8K-parameter acoustic model for compact speech synthesis. The code, pretrained model and audio demos are available online.
Updates & perspectives
New results, new conversations, and milestones along the way.
22 stories · 2024–2026
Our new GrainSpeech arXiv preprint introduces a 264.8K-parameter acoustic model for compact speech synthesis. The code, pretrained model and audio demos are available online.
Congratulations to EMI MSc student Navya Agarwal, whose internship research at imec has been accepted for presentation and publication at the 2026 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2026).
Excited to share that our article by our industrial PhD student Yi Zhu, “Deep-Learning Based Hardware-Efficient Load Identification for Power Amplifiers,” has been published in the IEEE Journal of Selected Topics in…
Very happy to share that our proposal, “The Living Radio Chip,” has been awarded a €100,000 NWO Open Mind Grant for a one-year, high-risk, high-gain research project.
We are thrilled to announce that PhD student Yizhuo Wu has been selected as a recipient of the 2026 IEEE Microwave Theory and Technology Society (MTT-S) Graduate Fellowship.
We were honored to host Dr. Chris Dick at our EMI lab at Delft University of Technology to share and discuss our recent work in radio-frequency digital predistortion (DPD) and to hear an insightful talk that provided…
We were honored to host Dr. Shintaro Shiba (Research Scientist and Technical Lead at Woven by Toyota) for an insightful talk titled "Unlocking the potential of event cameras: From events to motion to 3D…
On February 19, 2026, Chang Gao gave a featured talk at ISSCC titled "Open-Source AI for Analog Correction: From RF Power Amplifiers to Energy-Efficient Silicon". Speaking in the "Analog for AI and AI for Analog"…
We are thrilled to announce the successful completion of the AIRHAR (An Energy-Efficient AI-Powered Portable Radar System for Human Activity Recognition) project in collaboration with Dr. Francesco Fioranelli and…
We are thrilled to announce the publication of our new Perspective article, "Exploiting neuro-inspired dynamic sparsity for energy-efficient intelligent perception," in the latest issue of Nature Communications.
Proud moment for our Lab of Efficient Machine Intelligence (EMI) at TU Delft: three of our MSc students have their work accepted to flagship international conferences in circuits, systems, and computing:
Congratulations to our PhD student Yizhuo Wu, who won second place in the DPD competition at the 2025 IEEE MTT-S International Microwave Symposium (IMS).
We’re thrilled to announce that our patent “Neural Network-Based Inference Method and Apparatus” (US12299576B2) has officially been granted by the USPTO!
Congratulations to our PhD student, Ang Li, who received the 2025 IEEE Circuits and Systems Student Travel Grant for his oral presentation: "DPD-NeuralEngine: A 22-nm 6.6-TOPS/W/mm2 Recurrent Neural Network…
1️⃣Full-Custom Digital ASIC Design for Edge AI Computing
We are thrilled to announce our new collaboration with NXP Semiconductors to tackle the future of high-performance Analog-to-Digital Converters (ADCs) by harnessing machine learning to calibrate impairments and boost…
We are thrilled to announce that our EMI Research Group’s brilliant students have achieved remarkable success at this year’s flagship IEEE conferences!
Dr. Chang Gao has been awarded a prestigious Veni grant of €320,000 from the Dutch Research Council (NWO) for the project "Energy-Efficient Real-Time Edge Intelligence for Wearable Healthcare Devices." This…
Congratulations to Qinyu Chen (Assistant Prof. @ Leiden Univ.) and Chang Gao (Assistant Prof. @ TU Delft) for their paper at ISCAS 2024. The paper is titled "Epilepsy Seizure Detection and Prediction using an…
We're thrilled to announce our collaboration with GlobalFoundries in the GF 12LP+ University Partnership Program to support our research on Low-Power AI Hardware Accelerators using the cutting-edge 12 nm technology…
The premier International Microwave Symposium (IMS) has accepted our paper "MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Pre-distortion of Wideband Power Amplifiers," mainly…
We are thrilled to release OpenDPD: An Open-Source PyTorch-based End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeling and Digital Pre-Distortion (DPD). Authored by Yizhuo Wu, Gagan Deep…