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
Email

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

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