Hyunhoe An, Graduate
Bachelor's degree
Thanks for stopping by. My objective is to find a task-optimized architecture and its evolution that is akin to biological system representations by investigating recurrent neural networks (RNNs). RNNs are a type of artificial neural network (ANN) in which the output of one time step is fed back into the next. RNN can evolve over time for cognitive tasks such as working memory, or decision making.
- Location
- IBS Center for Neuroscience Imaging Research, N Center, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, 16419, Suwon, South Korea
- hyunhoe.an@gmail.com
- Google Scholar
- Hyunhoe An
Professional
–
researcher at Cell physiology laboratory, Seoul National University, Seoul, South Korea
Highlights
–
research intern at Nano Fabrication and Micro Optics National Research Laboratory, Yonsei University, Seoul, South Korea
Highlights
Education
–
BSc at Yonsei University, Seoul, South Korea
Courses
- Major: Mechanical Engineering
- Minor: Psychology
Honors, Awards, Grants
Nano-IMP 2018 Best Poster Award from Nano-Imprint-Molding-Forum
Conferences
NANOPIA 2018 Poster presentation
Design and fabrication of normal incident surface plasmon resonance sensor using nano-imprinting for detecting cardiac troponin T, biomarker for myocardial infarction
Nano-IMP 2018 Poster presentation
Design of a surface plasmon resonance sensor for label-free detection of cardiac troponin T in acute myocardial infarction
ICMTE 2014 Poster presentation
Detection of bio-molecular interactions by multi-scale microwell arrays integrated with microfluidic device
Languages
- Korean
- Fluency: native
- English
- Fluency: fluent
