The best books about mathematical models

19 authors have picked their favorite books about mathematical models and why they recommend each book.

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Consumption Takes Time

By Ian Steedman,

Book cover of Consumption Takes Time: Implications for Economic Theory

This looks like it’s the sternest and most boring book ever, but I love Steedman’s cool-and-collected ability to address the implications of the obvious: You can only do one thing at a time. You only have two hands. And when you’re with one set of belongings, you’re neglecting all the other stuff you own.

Consumption Takes Time

By Ian Steedman,

Why should I read it?

1 author picked Consumption Takes Time as one of their favorite books, and they share why you should read it.

What is this book about?

Standard economic theory of consumer behaviour considers consumers' preferences, their incomes and commodity prices to be the determinants of consumption. However, consumption takes time and no consumer has more - or less - than 168 hours per week. This simple fact is almost invisible in standard theory, and takes the centre stage in this book.


Who am I?

I’m an archaeologist, which means that I’ve been lucky enough to travel to many places to dig and survey ancient remains. What I’ve realized in handling those dusty old objects is that all over the world, in both past and present, people are defined by their stuff: what they made, used, broke, and threw away. Most compelling are the things that people cherished despite being worn or flawed, just like we have objects in our house that are broken or old but that we keep anyway.


I wrote...

Book cover of Cities: The First 6,000 Years

What is my book about?

Cities are such a strange concept that they had to be invented: in the deep past, everyone lived in villages. Yet cities provide so many things that a village cannot: diversity, entertainment, higher education, economic opportunities, and a sense of excitement accompanied by ever-increasing quantities of stuff. How did cities get started? What characteristics do modern cities share with ancient ones, both positive and negative? And what is it like to actually dig a city as an archaeologist, going down to the very bottom of the earliest urban centers to find out what made them so attractive to ancient inhabitants? 


Book cover of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

The more data the better? Not necessarily. Cathy O’Neil, an academic mathematician turned Wall Street quant turned data scientist, shows again and again how big data “threatens democracy." The ‘weapons of math destruction’ are models or algorithms that claim to quantify important human traits but can harm the poor, reinforce racism, and amplify inequality. Her glimpse of the dark side of big data shows how computers are only smart as the people who use them, the people who write their algorithms, the people who supply their data, and the people who curate all those data and algorithms. The old saw still holds true: garbage in, garbage out.

Weapons of Math Destruction

By Cathy O’Neil,

Why should I read it?

6 authors picked Weapons of Math Destruction as one of their favorite books, and they share why you should read it.

What is this book about?

'A manual for the 21st-century citizen... accessible, refreshingly critical, relevant and urgent' - Financial Times

'Fascinating and deeply disturbing' - Yuval Noah Harari, Guardian Books of the Year

In this New York Times bestseller, Cathy O'Neil, one of the first champions of algorithmic accountability, sounds an alarm on the mathematical models that pervade modern life -- and threaten to rip apart our social fabric.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives - where we go to school, whether we get a loan, how much we pay for insurance - are being made…


Who am I?

I’m the Science Director of the Science Museum Group, based at the Science Museum in London, and visiting professor at the Dunn School, University of Oxford, and Department of Chemistry, University College London. Every time I write a book I swear that it will be my last and yet I'm now working on my ninth, after earlier forays into the physics of Christmas and the love life of Albert Einstein. Working with Peter Coveney of UCL, we're exploring ideas about computation and complexity we tackled in our two earlier books, along with the revolutionary implications of creating digital twins of people from the colossal amount of patient data now flowing from labs worldwide.


I wrote...

The Dance of Life: Symmetry, Cells and How We Become Human

By Magdalena Zernicka-Goetz, Roger Highfield,

Book cover of The Dance of Life: Symmetry, Cells and How We Become Human

What is my book about?

The Dance of Life is the autobiography of a scientist – Magda Zernicka-Goetz – whose research on early human development was partly inspired by challenging events in her personal life. But our book is more than that, providing a biography of all human life, explaining the extraordinary events that turn all the information held in our DNA into flesh and blood, and showing how a newly fertilized egg becomes 40 trillion cells that ‘know’ how to make a human, from lips to heart to toes. In short, we describe how the body builds itself and the extraordinary implications of this new understanding.

Book cover of Advances in Financial Machine Learning

By now, you may notice that I like to recommend textbooks. I use this bestseller for my course in Financial Machine Learning at Northwestern University, but really, nobody interested in financial machine learning hasn’t read this book. The topics are highly relevant to every investor or trader – I read it at least 5 times to digest every nugget and have put them to very productive use in my trading as well as in my fintech firm predictnow.ai. It covers basic techniques such as random forest to advanced techniques such as Hierarchical Risk Parity, which is a big improvement over traditional portfolio optimization methods.

Marcos used to be Head of Machine Learning at AQR (AUM=$143B), and now is the Global Head of Quant Research at Abu Dhabi Investment Authority. He is also very approachable to his readers and students. There was seldom an email or message from me to which…

Advances in Financial Machine Learning

By Marcos Lopez de Prado,

Why should I read it?

1 author picked Advances in Financial Machine Learning as one of their favorite books, and they share why you should read it.

What is this book about?

Learn to understand and implement the latest machine learning innovations to improve your investment performance

Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that - until recently - only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest.

In the book, readers will learn how to:

Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives

Advances…


Who am I?

A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.


I wrote...

Quantitative Trading: How to Build Your Own Algorithmic Trading Business

By Ernest P. Chan,

Book cover of Quantitative Trading: How to Build Your Own Algorithmic Trading Business

What is my book about?

Can a robot take over your trading while you sip Tequila at the poolside? This book will show you how. You only need rudimentary programming skills, a tiny dose of math, and a healthy dose of grit.

In the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, I show you how to apply both time-tested and novel quantitative trading strategies. You’ll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as updated back tests on a variety of trading strategies, which included Matlab, Python, and R code examples. You will also find a guide to selecting the best traders and advisors to manage your money.

Option Trading

By Euan Sinclair,

Book cover of Option Trading: Pricing and Volatility Strategies and Techniques

Disclaimer: I like Euan’s books not because he is a friend and has endorsed my books. Long before we became friends, I have bought his book, and said to myself “Wow! This is the first book about options trading that is not just a bunch of trite statements about payouts from various straddles and spreads positions!” It talks about some unique arbitrage opportunities that only professionals knew about. On the other hand, the amount of mathematics is very manageable, and can largely be skipped without affecting the practical applications of the concepts. 

Option Trading

By Euan Sinclair,

Why should I read it?

1 author picked Option Trading as one of their favorite books, and they share why you should read it.

What is this book about?

An A to Z options trading guide for the new millennium and the new economy Written by professional trader and quantitative analyst Euan Sinclair, Option Trading is a comprehensive guide to this discipline covering everything from historical background, contract types, and market structure to volatility measurement, forecasting, and hedging techniques. This comprehensive guide presents the detail and practical information that professional option traders need, whether they're using options to hedge, manage money, arbitrage, or engage in structured finance deals. It contains information essential to anyone in this field, including option pricing and price forecasting, the Greeks, implied volatility, volatility measurement…


Who am I?

A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.


I wrote...

Quantitative Trading: How to Build Your Own Algorithmic Trading Business

By Ernest P. Chan,

Book cover of Quantitative Trading: How to Build Your Own Algorithmic Trading Business

What is my book about?

Can a robot take over your trading while you sip Tequila at the poolside? This book will show you how. You only need rudimentary programming skills, a tiny dose of math, and a healthy dose of grit.

In the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, I show you how to apply both time-tested and novel quantitative trading strategies. You’ll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as updated back tests on a variety of trading strategies, which included Matlab, Python, and R code examples. You will also find a guide to selecting the best traders and advisors to manage your money.

Algorithmic and High-Frequency Trading

By Alvaro Cartea, Sebastian Jaimungal, Jose Penalva

Book cover of Algorithmic and High-Frequency Trading

Finally, for those who are not afraid of math, they should read this book because there is a lot of heavy-duty math. The good news for the rest of us is you can ignore all the math and still get a lot out of it, especially knowledge about market microstructure and how to find the theoretically optimal trading strategies given some assumptions about the price dynamics. Even if you don’t want to or can’t solve those darn stochastic differential equations, you can still implement a numerical approximation. At the minimum, you will learn common trading lingo such as “walking the book” or “the ITCH feed”.

Algorithmic and High-Frequency Trading

By Alvaro Cartea, Sebastian Jaimungal, Jose Penalva

Why should I read it?

1 author picked Algorithmic and High-Frequency Trading as one of their favorite books, and they share why you should read it.

What is this book about?

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and…


Who am I?

A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.


I wrote...

Quantitative Trading: How to Build Your Own Algorithmic Trading Business

By Ernest P. Chan,

Book cover of Quantitative Trading: How to Build Your Own Algorithmic Trading Business

What is my book about?

Can a robot take over your trading while you sip Tequila at the poolside? This book will show you how. You only need rudimentary programming skills, a tiny dose of math, and a healthy dose of grit.

In the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, I show you how to apply both time-tested and novel quantitative trading strategies. You’ll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as updated back tests on a variety of trading strategies, which included Matlab, Python, and R code examples. You will also find a guide to selecting the best traders and advisors to manage your money.

Book cover of An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/CRC Mathematical and Computational Biology)

One of the earliest books on this subject, Uri Alon presents an engaging account of biological networks. Focussing on transcriptional networks, and their motifs, the book illustrates the nexus between network structures and functions. The second edition of the book launched a few years ago and has some updated content and new material on interesting functionalities such as fold change detection. Uri Alon is a very accomplished scientist, mentor, and a leader in the field of biological networks/systems biology.

An Introduction to Systems Biology

By Uri Alon,

Why should I read it?

1 author picked An Introduction to Systems Biology as one of their favorite books, and they share why you should read it.

What is this book about?

Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles.

An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.


Who am I?

Ever since I studied control theory as an undergrad chemical engineer, mathematical models of complex phenomena have fascinated me. Mathematical models have the uncanny ability to uncover key aspects of biological systems, whose complexity poses a great challenge for understanding. As a researcher in systems biology for over 15 years, I have enjoyed reading several books that explore the exciting interface between computation and biology, trying to capture the burgeoning literature on this rapidly advancing field. I hope you enjoy these books and will join these authors on an exciting journey into the cartography of molecular networks underlying every living cell, using a variety of mathematical models!


I wrote...

An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks

By Karthik Raman,

Book cover of An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks

What is my book about?

This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. The book adopts a hands-on approach to modelling, covering a broad spectrum of paradigms, from static networks to dynamic models and constraint-based models. Every chapter includes thoughtful exercises to test and enable understanding of concepts.

The book has a rich companion website featuring lecture videos, codes, supplementary exercises, further reading, and appendices. Much like the field itself, the book is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians, and others.

Vision

By David Marr,

Book cover of Vision: A Computational Investigation into the Human Representation and Processing of Visual Information

David Marr shaped the field of computer vision in its early days. His seminal book laid the structure for interpreting images and one which is still largely followed. He popularised notions of the primal sketch and his work on edge detection led to one of the most sophisticated approaches. His work and influence continue to endure despite his early death: we missed and miss him a lot.

Vision

By David Marr,

Why should I read it?

1 author picked Vision as one of their favorite books, and they share why you should read it.

What is this book about?

Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions.

David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This…


Who am I?

It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.


I wrote...

Feature Extraction and Image Processing for Computer Vision

By Mark S. Nixon,

Book cover of Feature Extraction and Image Processing for Computer Vision

What is my book about?

Computer Vision now helps society in many ways: we use face recognition on our phones and we can identify plants too (though we sometimes get fined when our number/ license plate goes past a camera too quickly). The advance has been due to faster computers, cheaper memory, better sensors, and better techniques. Back in 1997 I and Alberto found that no book covered feature extraction in-depth, so we rectified that. Our book is pretty much the only one describing computer vision via techniques for finding and describing shapes and structure. Many of these now find use in the systems applied in medicine and in industry – and in current deep learning-based systems. I’ll next be listing some of the great books that have moved this fascinating field forwards.

Fortune's Formula

By William Poundstone,

Book cover of Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street

The subtitle is The Untold Story of the Scientific Betting System that Beat the Casinos and Wall Street. This book is an easy-to-read narrative of the intersection of the grimy underbelly of betting--with high-minded math. It reminds you that trading is not conducted in a clean little bubble. Technical analysis can give you an edge, but trading is still engaging in battle with opposing forces; strategy and tactics can count as much as building an elegant technical system. 

Your opponent on the trading battlefield will try to trick you, like a general in real warfare. He may keep selling and selling after you have bought, triggering a sell signal in your trading system. He is hunting for your sell signal. The mechanical response is to sell—your system says sell, and you should follow your system. To exit a position when the market goes against you is named a stop,…

Fortune's Formula

By William Poundstone,

Why should I read it?

1 author picked Fortune's Formula as one of their favorite books, and they share why you should read it.

What is this book about?

In 1956, two Bell Labs scientists discovered the scientific formula for getting rich. One was mathematician Claude Shannon, neurotic father of our digital age, whose genius is ranked with Einstein's. The other was John L. Kelly Jr., a Texas-born, gun-toting physicist. Together they applied the science of information theory—the basis of computers and the Internet—to the problem of making as much money as possible, as fast as possible.

Shannon and MIT mathematician Edward O. Thorp took the "Kelly formula" to Las Vegas. It worked. They realized that there was even more money to be made in the stock market. Thorp…


Who am I?

Economics isn't really a good starting point for financial market analysis for the simple reason that its models are wildly inaccurate. As behaviorial economists like Daniel Kahneman have been showing, irrationality and the inability to measure risk properly are a very big component of the investment and trading decisions. But statistical risk management is also sloppy when applied to human behavior because people are not objects that reliably behave the same way under similar circumstances. So when you read an economist about markets or an engineer about risk management, you're missing a lot of the story. In the end, technical analysis is fascinating because how and why humans behave is an enduring mystery.


I wrote...

Technical Analysis For Dummies

By Barbara Rockefeller,

Book cover of Technical Analysis For Dummies

What is my book about?

Technical Analysis for Dummies covers the universe of techniques that help traders make gains and avoid losses. These techniques are based mostly on arithmetic but which ones you choose and how you use them makes a big difference in winning or losing. You can design a winning system to get an advantage—and still go broke if you hang on too long (greed) or get out too early (fear). 

In order to trade well, you need to review all the technical methods. Here’s the blessing and the curse—every single technique works. Selecting the techniques that are a fit for your personality and lifestyle is a lot harder. You may think you know yourself going in, but chances are you will be surprised at what fits you best.

The Fundamentals of Heavy Tails

By Jayakrishnan Nair, Adam Wierman, Bert Zwart

Book cover of The Fundamentals of Heavy Tails: Properties, Emergence, and Estimation

What do pandemics, climate change, extreme weather, financial crises, wealth inequality, and social media all have in common? They are all well described by heavy-tail statistics, which you may have never heard about and were almost certainly never taught in your introductory statistics class. The Fundamentals of Heavy Tails is the first text that attempts to close this gap in undergraduate STEM education. This well-written text is a wonderful blend of intuition and rigorous results. The reader will be pleasantly surprised to learn that heavy-tail distributions are neither rare nor mysterious and are a natural result of multiplicative random processes.

The Fundamentals of Heavy Tails

By Jayakrishnan Nair, Adam Wierman, Bert Zwart

Why should I read it?

1 author picked The Fundamentals of Heavy Tails as one of their favorite books, and they share why you should read it.

What is this book about?

Heavy tails -extreme events or values more common than expected -emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks…


Who am I?

Dr. Jeremy Kepner is head and founder of the MIT Lincoln Laboratory Supercomputing Center (LLSC), and also a Founder of the MIT-Air Force AI Accelerator. Lincoln Laboratory is a 4000-person National Laboratory whose mission is to create defensive technologies to protect our Nation and the freedoms enshrined in the Constitution of the United States. Dr. Kepner is one of five Lincoln Laboratory Fellows, a position that "recognizes the Laboratory's strongest technical talent for outstanding contributions to Laboratory programs over many years." Dr. Kepner is recognized as one of nine MIT Fellows of the Society of Industrial Applied Mathematics (SIAM), for "contributions to interactive parallel computing, matrix-based graph algorithms, green supercomputing, and big data." 


I wrote...

Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs

By Jeremy Kepner, Hayden Jananthan,

Book cover of Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs

What is my book about?

Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools—including spreadsheets, databases, matrices, and graphs—developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges.

Algorithms to Live By

By Brian Christian, Tom Griffiths,

Book cover of Algorithms to Live By: The Computer Science of Human Decisions

We have to learn how to properly use the Internet to prevent it from using us. We must comprehend the limits of artificial intelligence to take advantage of what it has to offer. Christian and Griffiths explore how algorithms can help us solve common – decisions and find strategies to humans.

Algorithms to Live By

By Brian Christian, Tom Griffiths,

Why should I read it?

4 authors picked Algorithms to Live By as one of their favorite books, and they share why you should read it.

What is this book about?

A fascinating exploration of how computer algorithms can be applied to our everyday lives.

In this dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show us how the simple, precise algorithms used by computers can also untangle very human questions. Modern life is constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? The authors explain how to have better hunches and when to leave things to chance, how to deal…


Who am I?

During my life, I’ve been told that I was not a true engineer, not a true banker, not a true CEO, not a true entrepreneur, not a true teacher… But one day an executive told me: “I want to work with you because you’re not a true consultant.” I then realized it is was a privilege not to be a true something! I like to call myself a corporate philosopher. Fellow of the BCG Henderson Institute, and co-founder of Cartoonbase, I split my time between the worlds of academia and business. I have published several other books on various subjects such as language, mathematics, humor, or fallacies.


I wrote...

Be Logical, Be Creative, Be Critical: the Art of Thinking in a Digital World

By Luc de Brabandere,

Book cover of Be Logical, Be Creative, Be Critical: the Art of Thinking in a Digital World

What is my book about?

AI and human intelligence. Fine, but who is programming who? The power of the computer should not come as a surprise since it was designed with the purpose of enabling humans to amplify their reasoning skills. But we should be aware that, if it allows us to think ahead, the computer influences our way of thinking as well. Thinking is clearly no longer what it used to be and, in my new book coauthored with Lina Benmehrez, I invite you to rediscover the art of thinking in a digital world through logic, creativity and sound argumentation!

This essay takes us back to ancient Greece where logical and critical thinking were first formalized. It also reminds us of more recent developments in cognitive sciences that include creative thinking. 

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