Ioannis Dasoulas

PhD Researcher &
Electrical and Computer Engineer

Meet Me

Short Bio

Ioannis Dasoulas

Electrical and Computer Engineer, currently working as a Computer Science PhD Researcher. After graduating from University of Patras with an Integrated Master in Electrical and Computer Engineering and a specialization in machine learning, and software development, I started pursuing a PhD in Computer Science at KU Leuven. My research work focuses on data engineering for machine learning pipelines leveraging linked data, knowledge graph construction, and semantic enrichment methods. In my free time, I work on projects related to deep learning and cyber-physical systems, as well as for the Beyond Orbit robotics team as a machine learning engineer.

Ioannis Dasoulas
MLSeascape

Embedded AI Project

NVIDIA Jetson Guide for Real-Time Deep Learning Inference from Scratch

Ioannis Dasoulas
A detailed guide to set up NVIDIA Jetson devices in order to run custom deep learning models from scratch efficiently. The guide contains instructions on booting embedding devices, configuring internet connection and memory, as well as setting up Python and running custom deep learning code.

MLSeascape

Publication

MLSeascape: Machine Learning Metadata Search Empowered by Knowledge Graphs

Ioannis Dasoulas, Duo Yang, Anastasia Dimou
A web application built on-top of MLSea-KG, which allows seamless search over machine learning knowledge from all over the web. The user is able to search for machine learning datasets, models, software, tasks, implementations, algorithms and publications as well as view their metadata. The application is open-source.

MLSea-KG

Publication

MLSea: A Semantic Layer for Discoverable Machine Learning

Ioannis Dasoulas, Duo Yang, Anastasia Dimou
A declaratively constructed and regularly updated KG with more than 1.44 billion RDF triples of ML experiments, regarding datasets used in ML experiments, tasks, implementations and related hyper-parameters, experiment executions, their configuration settings and evaluation results, code notebooks and repositories, algorithms, publications, models, scientists and practitioners. It integrates data from OpenML, Kaggle and Papers with Code.

TorchicTab

Publication

TorchicTab: Semantic Table Annotation with Wikidata and Language Models

Ioannis Dasoulas, Duo Yang, Xuemin Duan, Anastasia Dimou
A versatile semantic table interpretation system able to annotate tables with varied structures by using either an external knowledge graph, such as Wikidata, or annotated tables with pre-defined terms for training, leveraging kanguage models. TorchicTab achieved 1st place in the 2023 SemTab accuracy competition hosted at ISWC 2023.

Morph-KGC

Publication

Declarative RDF Construction from In-Memory Data Sources

Ioannis Dasoulas, David Chaves-Fraga, Daniel Garijo, Anastasia Dimou
A method to construct RDF graphs from data produced by a software process and stored in RAM. RML's syntax is extended to describe software produced data sources. Morph-KGC is extended to also construct KGs from Python data using the proposed syntax.

Yatter

Publication

Human-Friendly RDF Construction

Ana Iglesias-Molina, David Chaves-Fraga, Ioannis Dasoulas, Anastasia Dimou
A set of updates over the YARRRML serialisation to empower it with the latest necessities for constructing RDF graphs, accompanied with an implementation of these features in a new open-source translator, Yatter, currently used in different real use cases and international projects, as well as with a qualitative comparison of this proposal against similar state-of-the-art serialisations, and their associated translators over a set of conformance test cases.
Paper

Project Mars

Computer Vision Project

Mars Rock Segmentation and Size Estimation for Autonomous Rovers

Ioannis Dasoulas
Computer vision project that aims to identify and segment rocks in a Mars-like environment. YOLOv8 is used for rock detection and segmentation, as well as the MarsData dataset. Project is developed with pytorch, ultralytics, supervision and cv2 packages. For size estimation, a depth camera is used to estimate the size of the rocks. Model is also deployed on an NVIDIA Jetson Nano device, allowing real-time detection on rover cameras. Code will soon be open-sourced.

Project Mars

Data Engineering Project

Automated Feature Enrichment for Tabular Data with Semantic Table Annotation

Ioannis Dasoulas
Data engineering demo that leverages semantic table annotation to analyze tabular data, providing information about the column cells, types and relationships. The semantic annotations are used for querying external large knowledge bases and extracting more features about the table. In this demo we start with a table of airplanes, airplane families and airlines and manage to automatically extract new features such as wingspan, plane length, height and maximum operating altitude.

Project

Natural Language Processing Project

Simple Trigram Language Model for City Name Generation

Ioannis Dasoulas
This project explores the usage of basic n-gram neural networks for character generation. A trigram neural network is trained on character pairs from greek city names to produce novel city names. The project is an exercise task inspired by makemore's challenges. PyTorch is used for model development and training.

Project

Robot Navigation Project

Point Cloud Surface Reconstruction for Autonomous Rovers

Ioannis Dasoulas
Robot navigation project that leverages point clouds inferred by rovers to reconstruct the surface and spaces around it. Different surface reconstruction and point cloud processing methods are tested. Point cloud segmentation are also leveraged to cluster the incoming point clouds. Open3D package is used.

Project 1

Machine learning project (Diploma Thesis)

Chess Engine Development using Deep Learning Techniques

Ioannis Dasoulas
Three chess engines (Python Machine Learning Chess Engine) based on machine learning, and more specifically on reinforcement and supervised learning. The chess engines were developed using Python programming language. In total, three different game models were created, a model that was trained by playing games against itself, a model that was trained with data from past professional games stored in online databases and a combinational model that was trained using both methods. The engines’ choice of move is made using Monte Carlo Tree Search, which is a heuristic algorithm for certain types of decision-making processes.

Project 2

Web development project (Diploma Thesis Side Project)

Chess Playing Website

Ioannis Dasoulas
Online application that allows the user to play against the chess engines mentioned on the above project, but also to watch them play against each other. The website was created using, Python (Flask API), HTML5, CSS and Javascript.

Project 3

Database Application

Energy Distribution System Application

Ioannis Dasoulas, Aristeidis Dourdounas
Application about an energy distribution system. The app is meant to be used by a company that manages the distribution of electrical energy. The app provides a general picture of the distribution network, providing information about citizens' energy consumption and the energy produced by indepedent units of renewable energy. The project is written in Python and SQL.

Project 4

Web development project

Smart-Home Application

Ioannis Dasoulas, Christoforos Vaggelis
Application that simulates a real smart home application which enables the user to control smart devices in his/her house and assign each device to a room of his/her house. The application provides three access levels for three different classes of users, assigned by the administrator of the house. Application is written in HTML5, CSS, Javascript, using Node JS and express.js for backend as well as Bootstrap for frontend.

Project 16

Machine learning project

Real Estate Value Prediction Algorithms

Ioannis Dasoulas
Python project using 9 house characteristics such as location, area population and number of rooms to predict the value of houses. The prediction is accomplished using: a) Least Mean Squares Linear Regression, b) Ordinary Least Squares Regression and c) Neural Network.

Project 5

Human-Computer interaction project

MyDidaskalia Application

Ioannis Dasoulas, Christoforos Vaggelis
Zoom optimization project about designing an application named "MyDidaskalia" used for modern online lessons. The first part of the project was evaluating well known applications used for this purpose. The second part was choosing one of those applications (Zoom was chosen) and trying to improve it following human-computer interaction rules.

Project 6

Data retrieval project

Movie Search Engine Application

Ioannis Dasoulas
Movie search engine based on elasticsearch. The search engine decides the order of results' presentation utilizing machine learning techniques. The order of presentation depends on elasticsearh similarity metrics, user ratings, average ratings and user clustering. Word embeddings were also used to predict missing ratings of certain movies for the users.

Project 7

Parallel programming project

OpenMP Utilization in Classic Algorithms

Ioannis Dasoulas
Four projects about the utilization of OpenMP library in parallel programming. The library is used to accelerate the runtime of the classic K-Means algorithm, the travelling salesperson problem and the error-backpropagation computation in neural networks. All algorithms are written in C language.

Project 8

Java multi-thread project

Sleeping Barber Problem Application

Ioannis Dasoulas
Classic sleeping barber problem implementated in Java language using object oriented techniques and thread syncronization.

Project 9

Java server-client project

Blood Pressure Monitoring System Application

Ioannis Dasoulas
Application that has both server and client modes. Users can send medical data through the client interface to the server or use the server interface to view data sent by the clients, sort them, find spesific details, delete them or save them to a local file.

Project 11

VLSI project

VHDL Circuits Simulation

Ioannis Dasoulas
Classic circuits simulation and experimentaition using VHDL language and the ModelSim environment.

Project 12

Digital Signal Processing project

C67 DSK Board Programming

Ioannis Dasoulas, Dourdounas Aristeidis
C67 DSK board programming using Assembly and C language. The board was used for interrupts experimentation, A/D and D/A conversion, sampling, creation of FIR and IIR filters, creation of a DTFM decoder and creation of a spectrum analyzer.

Project 13

Pattern Recognition project

Matlab pattern recognition

Ioannis Dasoulas
Pattern recognition projects using Matlab language. Projects include pattern sorting using distance functions, K-Means algorithm implementation, Perceptron algorithm implementation and data classification.

Project 14

Data Mining project

Mail and Patient Classification

Ioannis Dasoulas
Mail classification (real or spam) and patient classification (possible stroke or not) using data mining and artificial intelligence techniques. Techniques include creating a K-Nearset-Neighbors model, creating a Random Forest Classifier model, as well as word embeddings with the implementation of a Doc2Vec model supported by a neural network. Project was implemented using Python 3.7.

Project 15

VLSI project

Circuit Design and Simulation

Ioannis Dasoulas, Vaggelis Christoforos
Design and simulation of basic and complicated CMOS circuits, study of the parasitic capacities, the delay, the critical path delay and the energy consumption of CMOS circuits using the Microwind tool. Also, LtSpice was used to design some of the circuits and simulate them.

Contact

E-mail

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