Linear Algebra, Signal Processing, and Wavelets - A Unified Approach

Øyvind Ryan, Linear Algebra, Signal Processing, and Wavelets - A Unified Approach, Python Version, Springer, 2019.  (code, Python)

1 Sound and Fourier Series

2 Digital Sound and Discrete Fourier Analysis

3 Discrete Time Filters

4 Motivation for Wavelets and Some Simple Examples

5 The Filter Representation of Wavelets

6 Constructing Interesting Wavelets

7 The Polyphase Representation of Filter Bank Transforms

8 Digital Images

9 Using Tensor Products to Apply Wavelets to Images

Appendix Basic Linear Algebra 

張忠謀在 APEC 非正式領袖會議的致詞

李玟儀

This Informal Retreat has been called to discuss how Asia-Pacific can collaborate to move through the COVID health crisis, and to accelerate the post-COVID economic recovery. Chinese Taipei will address these two topics specifically.

從AI到智慧醫療

蔣榮先，從AI到智慧醫療，商周，2020

本書作者蔣榮先教授為台灣資訊傑出人才，任教於成大醫學院、擔任成大醫院資訊長，從事醫療科技的尖端研究，並熟悉產業最新發展，深諳跨領域合作的必要性。

他以深入淺出的解說，配合大量生活應用實例、資訊圖表，描繪即將到來的AI智慧醫療新世界。值得醫界、產業界、藥界、醫材界的學者、專家參考，同時適合對健康醫療科技新知有興趣的大眾閱讀。

Politics, health collided in Taiwan's tortured BioNTech vaccine talks

Yimou Lee and Ben Blanchard, Politics, health collided in Taiwan's tortured BioNTech vaccine talks, Reuters, July 12, 2021.

Numerical Python

Robert Johansson, Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, Apress, 2019. (code)

 Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. 

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics

Justin Solomon, Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics,  1st Edition, A K Peters/CRC Press, 2015. (pdf)

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.

The book covers a wide range of topics—from numerical linear algebra to optimization and differential equations—focusing on real-world motivation and unifying themes. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students’ intuition while introducing extensions of the basic material.

The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background.

科技魅癮 (數位季刊)

 科技魅癮 

《科技魅癮》每期都精選1個國際關注的科技議題，邀請1位國內資深學者擔任客座編輯，並訪談多位來自相關領域的科研菁英，以「領路人」、「談觀點」、「探研究」、「躍思考」、「看世界」、「飆研值」等6個專欄，自多元視角剖析、探討該領域在臺灣及全球的研發現況、未來發展、相關衝擊及影響，希望藉由這個平臺，促進科際交流及跨域合作、激發科研人員創意思維、拓展產學鏈結網絡，進而增進國內研發能量。

沈孟儒院長：「精準健康，用科技讓醫療深植人心」，2021-03-31

簡禎富教授：「產業維新的初衷，是為了讓臺灣社會邁向以人為本的智慧生活。」，2021-06-09

The CEO of Pfizer on Developing a Vaccine in Record Time

Albert Bourla, The CEO of Pfizer on Developing a Vaccine in Record Time, Harvard Business Review, May–June 2021.

On March 19, 2020, as Covid-19 swept across the world, Bourla challenged everyone at Pfizer and its partner BioNTech—a German company focused on cancer immunotherapies—to “make the impossible possible”: develop a vaccine more quickly than anyone ever had before, ideally within six months and certainly before the end of the year.

Less than eight months later, on Sunday, November 8, they discovered that they had succeeded: Their combined phase two and three trials showed a 95% efficacy rate. In the spring, thanks to their work and that of the other companies whose vaccines have been authorized, 300 million doses should be available around the world.

It took a moon-shot challenge, out-of-the-box thinking, intercompany cooperation, liberation from bureaucracy, and most of all, hard work from everyone at Pfizer and BioNTech to accomplish what they did in 2020. Organizations of any size or in any industry can learn from these strategies to solve their own problems and to produce important work that benefits a broad swath of society.

SOMATIC - commercial bathroom cleaning robotics

SOMATIC - commercial bathroom cleaning robotics, 2021/5/6

敗部區疫苗的逆襲

楊惠君、陳潔敗文字，楊子磊攝影，敗部區疫苗的逆襲──從賽諾菲到國光，傳統疫苗大廠為何栽跟斗？有復活機會嗎？，報導者，2021/6/30

「國光生技」是台灣最老牌的人用疫苗廠，但與他們合作生產四價流感疫苗的國際伙伴──法國大藥廠賽諾菲集團（Sanofi）一樣，在COVID-19疫苗研發的第一階段競逐，落入敗部區。兩家藥廠的重組蛋白疫苗跌倒路徑也相似：「臨床試驗劑量計算失誤，沒有激發足夠的免疫反應」，只能退回起跑點再來過。...

Reinforcement Learning for Industrial AI with Pieter Abbeel

The TWIML AI Podcast, Reinforcement Learning for Industrial AI with Pieter Abbeel - #476, 2021/4/20.

Today we’re joined by Pieter Abbeel, a Professor at UC Berkeley, co-Director of the Berkeley AI Research Lab (BAIR), as well as Co-founder and Chief Scientist at Covariant.

In our conversation with Pieter, we cover a ton of ground, starting with the specific goals and tasks of his work at Covariant, the shift in needs for industrial AI application and robots, if his experience solving real-world problems has changed his opinion on end to end deep learning, and the scope for the three problem domains of the models he’s building.

We also explore his recent work at the intersection of unsupervised and reinforcement learning, goal-directed RL, his recent paper “Pretrained Transformers as Universal Computation Engines” and where that research thread is headed, and of course, his new podcast Robot Brains, which you can find on all streaming platforms today!

The complete show notes for this episode can be found at twimlai.com/go/476.

Optimization modelling: A practical approach

Ruhul Amin Sarker and Charles S. Newton, Optimization modelling: A practical approach, CRC Press, 2007. 

Although a useful and important tool, the potential of mathematical modelling for decision making is often neglected. Considered an art by many and weird science by some, modelling is not as widely appreciated in problem solving and decision making as perhaps it should be. And although many operations research, management science, and optimization books touch on modelling techniques, the short shrift they usually get in coverage is reflected in their minimal application to problems in the real world. Illustrating the important influence of modelling on the decision making process, Optimization Modelling: A Practical Approach helps you come to grips with a wide range of modelling techniques.

智能工廠來了

陳泳翰，智能工廠來了！：一場水五金與手工具的創新實驗紀錄，天下雜誌，2021

歷時兩年半的「水五金與手工具產業智動化計畫」，簡稱「水手計畫」，同時也象徵著水手們乘風破浪的勇敢無懼精神。來自上銀科技的精密機械工程師，攜手四間傳統工廠：隴鈦銅器、勝泰衛材、銳泰精密、伯鑫⼯具，讓機器人實現產線智慧化、自動化的願景，不僅減輕第一線的人力負擔，也改變了黑手工廠形象，吸引更多年輕世代投身其中。

Algorithms for Decision Making

Mykel Kochenderfer, Tim Wheeler, and Kyle Wray, Algorithms for Decision Making, MIT Press, 2022. (pdf available online)

A broad introduction to algorithms for optimal decision making under uncertainty. We cover a wide variety of topics related to decision making, introducing the underlying mathematical problem formulations and the algorithms for solving them. Figures, examples, and exercises are provided to convey the intuition behind the various approaches. This text is intended for advanced undergraduates and graduate students as well as professionals. The book requires some mathematical maturity and assumes prior exposure to multivariable calculus, linear algebra, and probability concepts. Some review material is provided in the appendix. Disciplines where the book would be especially useful include mathematics, statistics, computer science, aerospace, electrical engineering, and operations research. Fundamental to this textbook are the algorithms, which are all implemented in the Julia programming language.

Prof. Kochenderfer also teaches 2 related courses at Stanford.