Nikolaos Alachiotis completed his undergraduate studies at the ECE department of the Technical University of Crete (Greece) and his Ph.D. at the Informatics department of the Technische Universität München (Germany) in 2008 and 2012, respectively. His research interests lie in the fields of computer architecture, parallel computing, reconfigurable computing, and Bioinformatics. He joined the Computer Architecture Lab at Carnegie Mellon University as a post-doctoral researcher in 2014, where he led the design of a generic acceleration architecture for 3D-stacked DRAMs (DARPA-funded PERFECT project). He joined the Computer Architecture and VLSI Systems Laboratory at FORTH-ICS in September 2016, where he worked on architecture design and hardware development for specialized acceleration in disaggregated datacenters (EU-funded dReDBox project). In June 2019, he joined the Telecommunications Systems Research Institute to work on automated generation of hardware-accelerated software for deployment on the cloud (EU-funded EDRA project). He is with the CAES group at UT since June 2020.

Expertise

  • Computer Science

    • Convolutional Neural Network
    • Detection
    • Positive Selection
    • Field Programmable Gate Arrays
    • Neural Network Architecture
    • Linkage
    • Algorithms
  • Biochemistry, Genetics and Molecular Biology

    • Selective Sweep

Organisations

Publications

2025

Fast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN (2025)Communications Biology, 8(1). Article 58. van den Belt, S. & Alachiotis, N.https://doi.org/10.1038/s42003-025-07480-7Methods for selective sweep detection using convolutional neural networks (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Zhao, H.https://doi.org/10.3990/1.9789036569484Accelerated Phylogenetics on the AMD Versal Adaptive SoC (2025)ACM Transactions on Reconfigurable Technology and Systems, 18(3). Article 41. Roks, G., Ruiz Noguera, M. & Alachiotis, N.https://doi.org/10.1145/3747592Information processing with silicon-based nonlinear computing units (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Zolfagharinejad, M.https://doi.org/10.3990/1.9789036568104Exploring the AMD®Deep Learning Processor Unit for Accelerating Selective Sweep Detection (2025)In Proceedings - 2025 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2025 (pp. 949-958). IEEE. Alachiotis, N. & Souilljee, M.https://doi.org/10.1109/IPDPSW66978.2025.00147FPGA innovation research in the Netherlands: present landscape and future outlook (2025)Frontiers in High Performance Computing, 3. Article 1572844. Alachiotis, N., van den Belt, S., van der Vlugt, S., van der Walle, R., Safari, M., Endres Forlin, B., De Matteis, T., Al-Ars, Z., Jordans, R., Sousa de Almeida, A. J., Corradi, F., Baaij, C. & Varbanescu, A.-L.https://doi.org/10.3389/fhpcp.2025.1572844Accelerated CNN-based Scans for Traces of Positive Selection (2025)In PASC 2025 - Platform for Advanced Scientific Computing Conference, Proceedings. Association for Computing Machinery. van den Belt, S. & Alachiotis, N.https://doi.org/10.1145/3732775.3733583Embedded test instruments for ageing-aware multi-processor system-on-chips (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Ali, G.https://doi.org/10.3990/1.9789036566193Applications of neural networks for FMCW automotive radars: Techniques for improving detection and DoA estimation (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Lima de Oliveira, M. L.https://doi.org/10.3990/1.9789036566018Accelerating Selective Sweep Detection using AMD Deep Learning Processing Units and Vitis AI (2025)In 45th Symposium on Information Theory and Signal Processing (SITB 2025) (pp. 8-11) (Accepted/In press). Bunda, S., Alachiotis, N. & Spreeuwers, L.

Research profiles

Courses academic year 2025/2026

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2024/2025

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