採訪撰文 簡克志，美術設計 林洵安，機器學習 x 鈣鈦礦材料：讓 AI 幫你最佳化太陽能電池材料的製程參數！，研之有物，2022-02-21
機器學習輔助材料設計
為了 2050 淨零排放的目標，太陽能發電為不可或缺的再生能源之一，其中「鈣鈦礦太陽能電池」是近年最熱門的研究領域，不僅成本低廉、光電轉換效率也可達到 25%。然而，鈣鈦礦材料在環境中容易降解，影響使用壽命。材料科學家為了做出效能好又穩定的鈣鈦礦「料理」，無不卯足了勁，替這道菜加上各種「食材」，但是越複雜的菜，調出好味道就越困難。人腦畢竟有限，如果交給機器呢？中央研究院「研之有物」專訪院內應用科學研究中心包淳偉研究員，他與團隊訓練了一套機器學習模型，可以又快又準的找出複雜鈣鈦礦材料的最佳化條件！
Molnar, Christoph. “Interpretable machine learning. A Guide for Making Black Box Models Explainable”, 2019. https://christophm.github.io/interpretable-ml-book/.
This book started as a side project when I was working as a statistician in clinical research. I worked four days a week, and on my “day off” I worked on side projects. Eventually, interpretable machine learning became one of my side projects. At first I had no intention of writing a book. Instead, I was simply interested in finding out more about interpretable machine learning and was looking for good resources to learn from. Given the success of machine learning and the importance of interpretability, I expected that there would be tons of books and tutorials on this topic. But I only found the relevant research papers and a few blog posts scattered around the internet, but nothing with a good overview. No books, no tutorials, no overview papers, nothing. This gap inspired me to start writing this book. I ended up writing the book I wished was available when I began my study of interpretable machine learning. My intention with this book was twofold: to learn for myself and to share this new knowledge with others.
備課的時候，除了論文和雜誌以外，我習慣看很多的書，以便整理出適合學生的教材。
系上配置4位助理，所以請助理幫我輸入圖書推薦清單。沒想到，才兩個禮拜，圖書館就已經通知我，可以借其中的十本。更開心的是，學校允許老師較長的借期，算一算，1年後才需回館。
亞當斯密早在十八世紀，就已經強調分工的重要性，以提升所有人的效率。
從排隊理論的觀點來看，如果一個隨機的服務系統，當使用率接近1的時候 ，就會產生事情延誤的狀況。更不要說，需要規劃與思考的工作，太過忙碌，很容易掛一漏萬。
對管理者而言，當然很難決定資源的配置。高強教授當成大校長的時候，使用資料包絡法，分析和比較系所的生產力。某董事長使用類比法，她說：等到你們研究像在坐的某教授一樣好 (剛從中正退休)，再來爭取。