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.


  • Computer Science

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

    • Selective Sweep



FPGA-accelerated Quantum Transport MeasurementsIn 2023 International Conference on Field Programmable Technology (ICFPT) (pp. 44-52). IEEE. Haarman, T., Sousa de Almeida, A. J., Heskes, A., Zwanenburg, F. A. & Alachiotis, N. Real-Time Classification of Evolving Data Streams using Adaptive Random ForestsIn 2023 International Conference on Field Programmable Technology (ICFPT), Article 10416141 (pp. 232-237). IEEE. Ridder, F., Chen, K.-H. & Alachiotis, N.
Effective Data Preprocessing Techniques for CNN-based Selective Sweep DetectionIn 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Article 10385303 (pp. 793-800). IEEE. Zhao, H. & Alachiotis, N. Radiation Tests of the NEORV32 RISC-V SoC on Flash-Based FPGAsIn 36th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT 2023. IEEE. Böhmer, K., Forlin, B., Cazzaniga, C., Rech, P., Furano, G., Alachiotis, N. & Ottavi, M. A Lightweight CNN Architecture for the Classification of Adaptive Genomic RegionsIn PASC '23: Proceedings of the Platform for Advanced Scientific Computing Conference, Article 12 (pp. 1-10). ACM Press. Zhao, H., Pavlidis, P. & Alachiotis, N. Survey of Processing Systems for Phylogenetics and Population GeneticsACM Transactions on Reconfigurable Technology and Systems, 16(3), 1-27. Corts, R. & Alachiotis, N. sweeps identification in distinct groups of cultivated rye (Secale cereale L.) germplasm provides potential candidate genes for crop improvementBMC Plant Biology, 23, Article 323, 1-17 (E-pub ahead of print/First online). Hawliczek, A., Borzecka, E., Tofil, K., Alachiotis, N., Bolibok, L., Gawroński, P., Siekmann, D., Hackauf, B., Dušinsk, R., Švec, M. & Bolibok-Bragoszewska, H. scans for selective sweeps using convolutional neural networksBioinformatics, 39(Supplement1), i194-i203. Zhao, H., Souilljee, M., Pavlidis, P. & Alachiotis, N. Performance of Hardware Accelerators by Optimizing Data Movement: A Bioinformatics Case StudyElectronics, 12(3), Article 586. Knoben, P. & Alachiotis, N. unprotected RISC-V Soft-core processor on an SRAM FPGA: Is it as bad as it sounds?In Proceedings - 2023 IEEE European Test Symposium, ETS 2023. IEEE. Forlin, B. E., van Huffelen, W., Cazzaniga, C., Rech, P., Alachiotis, N. & Ottavi, M.

Research profiles

Courses academic year 2023/2024

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 2022/2023


University of Twente

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