Seminars

October 29, 2019: Ms. Nguyen Thi Anh Dao (AVITECH), EEG signal processing systems for automatic detection of epileptic spikes

The thesis aims to build EEG signal processing systems that automatically detect epileptic spikes by exploiting the relationship between adjacent spikes in time (single-channel EEG data analysis) and space (simultaneous multi-channel EEG data analysis).

Speaker: Ms. Nguyen Thi Anh Dao, AVITECH

Time: 15:30, Tuesday, October 29, 2019

Venue: E3-212, 144 Xuan Thuy, Cau Giay, Hanoi

Nguyen Thi Anh-Dao was born in Thai Binh, Vietnam, in 1981. She got her Bachelor degree in Electronics – Telecommunications Technology in 2003, Master degree in Electronics -Telecommunications Technology in 2013 and since November 2013, she has been a Ph.D. student in Electronics – Telecommunications Technology in 2013 from University of Engineering and Technology, Vietnam National University Hanoi.

SAME CATEGORY

May 16, 2024: TECHNICAL MEETING, Dr. Tran Quoc Long (Institute for Artificial Intelligence, UET), How Healthcare Systems in Vietnam Work

Vietnam’s healthcare system is a unique amalgamation of public and private sectors, designed to provide comprehensive care to its diverse population. This talk aims to elucidate the structure, function, and challenges of the Vietnamese healthcare system, with a special focus on the integration of artificial intelligence (AI) into healthcare practices. We will explore the historical […]

May 16, 2024: TECHNICAL MEETING, Prof. Maarten De Vos (Departments of Engineering and Medicine, KU Leuven, Belgium), AI in healthcare: turning the hype into a help

AI is everywhere, and has the potential to disrupt also healthcare. However, particular challenges related to healthcare applications need to be addressed. Those are exciting times being at the intersection of AI and healthcare. The impact of AI in healthcare will only grow, and we are here at the right time to also unlock the […]

February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]