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

2024

Accelerated Spiking Convolutional Neural Networks for Scalable Population Genomics (2024)In Proceedings of the 14th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies, HEART 2024 (pp. 53-62) (ACM International Conference Proceeding Series). Association for Computing Machinery. Corradi, F., Shen, Z., Zhao, H. & Alachiotis, N.https://doi.org/10.1145/3665283.3665285Lightweight Instrumentation for Accurate Performance Monitoring in RTOSes (2024)In 2024 Design, Automation and Test in Europe Conference and Exhibition, DATE 2024 - Proceedings (Proceedings -Design, Automation and Test in Europe, DATE). IEEE. Forlin, B., Chen, K. H., Alachiotis, N., Cassano, L. & Ottavi, M.https://ieeexplore.ieee.org/document/10546790Accelerated Real-Time Classification of Evolving Data Streams using Adaptive Random Forests (2024)In 2023 International Conference on Field Programmable Technology (ICFPT) (pp. 232-237). Article 10416141. IEEE. Ridder, F., Chen, K.-H. & Alachiotis, N.https://doi.org/10.1109/ICFPT59805.2023.00031FPGA-accelerated Quantum Transport Measurements (2024)In 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.https://doi.org/10.1109/ICFPT59805.2023.00010

2023

Effective Data Preprocessing Techniques for CNN-based Selective Sweep Detection (2023)In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 793-800). Article 10385303 (IEEE International Conference on Bioinformatics and Biomedicine (BIBM); Vol. 2023). IEEE. Zhao, H. & Alachiotis, N.https://doi.org/10.1109/BIBM58861.2023.10385303Neutron Radiation Tests of the NEORV32 RISC-V SoC on Flash-Based FPGAs (2023)In 36th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT 2023 (Proceedings - IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT; Vol. 36). IEEE. Böhmer, K., Forlin, B., Cazzaniga, C., Rech, P., Furano, G., Alachiotis, N. & Ottavi, M.https://doi.org/10.1109/DFT59622.2023.10313556SweepNet: A Lightweight CNN Architecture for the Classification of Adaptive Genomic Regions (2023)In PASC '23: Proceedings of the Platform for Advanced Scientific Computing Conference (pp. 1-10). Article 12. ACM Press. Zhao, H., Pavlidis, P. & Alachiotis, N.https://doi.org/10.1145/3592979.3593411A Survey of Processing Systems for Phylogenetics and Population Genetics (2023)ACM Transactions on Reconfigurable Technology and Systems, 16(3), 1-27. Corts, R. & Alachiotis, N.https://doi.org/10.1145/3588033Genome-wide scans for selective sweeps using convolutional neural networks (2023)Bioinformatics, 39(Supplement1), i194-i203. Zhao, H., Souilljee, M., Pavlidis, P. & Alachiotis, N.https://doi.org/10.1093/bioinformatics/btad265Selective sweeps identification in distinct groups of cultivated rye (Secale cereale L.) germplasm provides potential candidate genes for crop improvement (2023)[Dataset Types › Dataset]. Zenodo. Hawliczek, A., Borzęcka, E., Tofil, K., Alachiotis, N., Bolibok, L., Gawroński, P., Siekmann, D., Hackauf, B., Dušinský, R., Švec, M. & Bolibok-Bragoszewska, H.https://doi.org/10.5061/dryad.866t1g1vx

Research profiles

Courses academic year 2024/2025

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 2023/2024

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