國立臺灣大學生物機電工程學系

  Workshop 交流會師生合照 (螢幕右方：左一至左五依序為：長船健二教授、侯詠德教授、鄭宗記教授、吳筱梅助理教授) Workshop 交流會的會後餐敘合照 (左一至左五依序為：謝博全副教授、侯詠德教授、長船健二教授、陳力騏教授、鄭宗記教授)     生機系侯詠德教授再次邀請日本京都大學 iPS 細胞研究所的長船健二教授/副所長於 2024年 12 月 18 日至 19 日蒞臨本系，並於 12 月 18 日與生機系的師生們於知武館 401 教室一同參與 2nd National Taiwan University and Kyoto University Joint-symposium。 會中，除了長船健二教授帶來的「iPSC technology-based regenerative therapy and drug discovery for liver diseases」演講之外，還包含以下研究發表： 丁健芳助理教授：「Evaluation of hepatocyte separation and culture in laser-fabricated microchannels」 侯詠德教授團隊： Development of a DLM-coated liver-on-a chip for enhanced hepatic functions and drug testing applications Development of a vascularized liver-on-a chip platform for liver tissue engineering Establishment of a fatty liver detection and drug prediction platform using a machine learning-based liver-on-a chip system 謝博全副教授團隊：「An aptamer-based capacitive biosensor for gluten detection」 鄭宗記教授團隊：「Determination of o‑phthalaldehyde for dose verification of the clinical disinfectant by fluorescent sequential injection analysis」 吳筱梅助理教授團隊：「Development of a smart automated microscopic image tracking system for precision of living cells」 盧彥文教授團隊：「Innovative technologies in blood filtration and component separation」 陳林祈教授團隊：「Rapid D-dimer colorimetric assay based on unmodified aptamer-gold nanoparticle conjugates」 會中除了再次讓本系教師群能與長船健二教授交流討論研究議題之外，侯詠德教授亦曾於 2024 1015~1215 期間派遣兩位碩班同學至長船健二教授實驗室交流學習兩個月，這也更增加了雙方日後的交流合作之空間。

  胡副總介紹了許多商業與產品決策的思維與邏輯，例如以多變量分析計算每個因素對產品定位的影響，進而找到獨特市場定位增加競爭力。此外，每當提出獨特與創新的想法時，必會受到各方質疑和負面回饋，講者也分享要如何透過市場調研、工程技術方面說服公司內部同事與外部客戶，這些經驗分享相信都能讓我在未來職場上受用許多。   撰寫者: 碩士班學生梁桓瑜 In his talk, Mr. Hu shared valuable insights into the approaches and rationale behind business and product decision-making. He illustrated how multivariable analysis can assess each factor's impact on product positioning, ultimately helping to carve out a unique market stance and enhance competitiveness. He also shed light on the inevitable challenges of presenting innovative ideas—facing skepticism and resistance from various angles. By recounting his experiences with leveraging market research and engineering expertise to convince both internal teams and external clients, Mr. Hu offered practical lessons that I believe will be invaluable in my future career.   Author: Master student: Huan-Yu Liang p { line-height:1.7; }

  This topic focuses on EEG-based seizure prediction using an online system with group learning, adaptive postprocessing, and feature encoding, achieving high sensitivity and low falsepositive rates in long-term data (>6 months). It addresses seizure clustering in real-world scenarios and demonstrates the effectiveness of this novel approach. The second topic about “unsupervised EEG feature Learning for Seizure Prediction based on convolutional Autoencoder” explores unsupervised feature learning using convolutional autoencoders (CAEs) applied to the CHB-MIT scalp EEG database for better prediction. Research should explore advanced deep learning models, expand datasets for diverse patient data, and integrate real-time adaptive strategies with additional physiological signals to improve prediction accuracy.   Author: PhD student: Vidhatri Gujela p { line-height:1.7; }

  In this lecture, Dr. Ying-Ja Chen from NVIDIA discussed the impact of Generative AI in the biomedical field. She explained how AI is used in areas like digital health, genomics, drug discovery, and medical imaging. She talked about challenges in using AI in biomedical projects which is figuring out the right problem to solve and setting realistic goals and expectation. Dr. Chen also discussed how GPUs outperform CPUs for machine learning and how they help train large AI models. The AI software which has been developed with GPUs is advancing many fields, including biology and robotics. As a PhD student working on AI in medical imaging, this lecture was very helpful for me. It gave me a better understanding of the power of Generative AI and the opportunities NVIDIA’s GPUs offer for building advanced machine learning models. I’m now more interested in NVIDIA’s work and aspire to contribute to their innovative research as an engineer in the future.   Author: PhD student: Shaghayegh Afshari p { line-height:1.7; }