Blog
Beginning of the project
28.12.2020. The first meeting of the team in an electronic environment took place in mid-December. The goals and tasks of the project were discussed, as well as the current tasks.
Media article
Article reveling the project mission, aims and challenging problems is published in CIO magazine, issue 3 from April 2021. Advantages of machine learning, artificial intelligence and statistics for improving different engineering tasks at design, analysis, testing, measurement and manufacturing of electronic modules and devices are also discussed. The article is a result of the united efforts of some project members.
The picture is taken from the published article, CIO, issue 3, April, 2021.
Diploma projects of Master degree students
Four Master degree students successfully defended their diploma theses on topics related to the Project statements. The application of statistics methods and machine learning algorithms were explored for solving different problems in electronics.
Invitation
Dear colleagues,
The team of the project "Exploration the application of statistics and machine learning in electronics", funded by the NSF, is pleased to invite you to a lecture by Prof. Petia Georgieva from the University of Aveiro, Portugal on the topic: "Deep training in brain-computer interface", which will be held on 25.02.2022 (Friday) from 11 am at the Technical University - Sofia, Center for International Meetings and virtually at: meet.google.com/com-bgsp-fcf.
You are welcome!
EASMLE project team
Lecture by Prof. Petia Georgieva
TU_BCI_25Fev2022.pdf
International Conference on Statistics and Machine Learning in Electronics
The first conference Statistics and Machine Learning in Electronics, brought together researchers from several countries as a forum for sharing interesting ideas and creation of fruitful collaborations. The invited lecturers Prof. Petya Georgieva and Prof. Stefan Hensel discussed new aspects and problems in the application of machine and deep learning. Two articles were awarded as the best:
in the scientifically applied aspect: Off-line Inertial-Sensor Based Hand Gesture Recognition and Evaluation, Mirela Kundid Vasić, Tamara Grujić, Ivo Stančić, Josip Music, Mirjana Bonković;
in theoretical aspect: Stochastic processes with applications in supply chain management of electronics industry, Meglena Lazarova.
Proceedings of the International Conference Statistics and Machine Learning in Electronics
The Proceedings of the International Conference Statistics and Machine Learning in Electronics is available at: http://ir.bas.bg/ccs/2022/index.html
International Symposium on Statistics and Machine Learning in Electronics
We are very grateful to SpliTech 2023 for their wonderful organization and hosting of the International Symposium on Statistics and Machine Learning in Electronics! The deadline for papers submission is 24 February 2023! You are very welcome to join us!
Extended variants of the accepted and presented papers will be published in a special issue of MDPI Computation!
Invitation
Dear colleagues,
The team of the project "Exploration the application of statistics and machine learning in electronics", funded by the NSF, is pleased to invite you to a lecture by Dr Stoyan Stoyanov from the University of Greenwich in UK on the topic: "Microelectronics design and qualification test driven by AI", which will be held on 17.03.2023 (Friday) from 11.30 virtually at: meet.google.com/com-bgsp-fcf.
You are welcome!
EASMLE project team
Lecture by Dr Stoyan Stoyanov
TU Sofia Talk March 2023.pdfSummer School
Summer_school_final.pdfThe Summer school "Exploration the applications of Statistics and Machine Learning in Electronics" will be held in a hybrid form at the Center for International Meetings at the Technical University - Sofia and in Google Meet: https://meet.google.com/fdq-gmum-jak
on June 28 2023. Students, young and experienced researchers are very welcome!
info1_En.pdfInvitation
POKANA_Svetozar_Ilchev_En.pdfInternational Symposium on Statistics and Machine Learning in Electronics 2024
24SYM on Statistics and Machine Learning in Electronics.pdf