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Simonian J: FOUNDATIONS OF FINANCIAL
DATA SCIENCE: METHODS, MODELS, AND APPL

FOUNDATIONS OF FINANCIAL DATA SCIENCE: METHODS, MODELS, AND APPLICATIONS

This accessible and thought-provoking book offers a critical exploration of global health philanthropy, blending personal narrative with a rigorous examination of the field's challenges and opportunities. Grounded in the authors' decades of experience, Crossroads in Global Health reflects on the transformative power of medicine, the complexities of global health engagement, and the enduring human impulse to alleviate suffering. The authors examine the tension between short-term relief and durable system change, and show how reframing global health as a marketplace, powered by data, analytics, and AI, can better match resources to need and turn goodwill into measurable impact.Key Features:· Explores the history, evolution, and critiques of global health, with a focus on discrete philanthropic medical missions.· Examines the landscape of global health needs and resources, shaped by logistics, incentives, and institutional structures.· Reflects on the authors' personal journeys in global health, offering insights into the challenges and lessons learned from decades of experience.· Proposes innovative approaches to harnessing data and technology to create a more efficient and accountable marketplace for global health philanthropy.· Balances the importance of systemic solutions with the moral imperative of immediate care, emphasizing the enduring value of direct human connection in medicine.Building on the authors' previous works, including the World Compendium of Healthcare Facilities and Nonprofit Organizations, this book is an essential resource for medical practitioners, academics, and professionals in the non-profit, public, and private sectors. It offers a compelling call to action for those seeking to make a meaningful impact in global health, while honoring the profound responsibility and transformative potential of the medical profession.

Pragmatic Solutions in a Complex World

Crossroads in Global Health

A USA Today Bestseller. A dramatic new future of work in which managers assemble exactly the expertise they need—within minutes. 2026 PROSE Award Winner: Business, Finance, and Management "If you’ve ever wished you could assemble your version of The Avengers at work, this book will help you make it happen.” —Adam Grant, #1 New York Times-bestselling author of Think Again and host of the podcast Re:Thinking Gone are the days of static organizational charts and staffing based on the manager’s rolodex and intuition. Now you can recruit any expertise you need from a global online network within minutes: an on-demand, on-the-spot expert at the exact moment that you need their help. You can right-size their involvement, too; some of those experts give a second opinion or a moment of brainstorming, whereas others join as full-fledged team members for a sustained collaborative effort. This is the future promised by flash teams, a model that The New York Times has already praised for its “revolutionary potential”: a world where experts are available anytime and everywhere, where remote work has become a norm, and where AI is in the loop to guide team decisions. In Flash Teams, award-winning management scholar Melissa Valentine and computer scientist Michael Bernstein chart the opportunities of flash teams and navigate the challenges that teams and managers will face. They distill lessons from their own work assembling and managing flash teams on demand that every manager can learn from so they can successfully use flash teams in their own organizations. Drawing on original research and industry examples, this book will help readers to: <ul><li>Recognize and source needed expertise within minutes</li><li>Anticipate and plan team designs with AI</li><li>Redesign team structures on the fly as projects evolve</li></ul> Industries are already being transformed by this new approach to teaming. Flash Teams arms leaders, managers, and entrepreneurs with the tools they need to accomplish their goals with confidence, speed, and agility.

Leading the Future of AI-Enhanced, On-Demand Work

Flash Teams

Econometric Society Monographs

A Framework for Economists with Policy Aspirations

Minimalist Market Design

Risk, Governance and Society

From Data Analytics to Global Risk Governance

Evolution of Anomaly Detection

Tech, War and the Fight for Humanity

Thundercloud

Springer Series in Supply Chain Management

This book analyzes the transformative potential of blockchain technology for supply chains operating under uncertainty, offering actionable frameworks and strategies for sustainable, transparent, and data-driven business networks.It analyzes how blockchain technology can optimize supply chains in uncertain environments. It explores strategic implementations across industries such as oil and gas, renewables, and omni-channel retail, addressing challenges like efficiency, transparency, security, and environmental impact. The book introduces frameworks for component vs. product tracing, two-step authentication models, integrated network design, and traffic uncertainty modeling. Each chapter presents concepotual models and decision-making tools tailored for practitioners and researchers. It examines the use of smart contracts in blockchain-enabled supply chains, showcasing their potential to automate compliance, lower transaction costs, and build trust, while addressing key challenges such as legal enforceability, code vulnerabilities, and cross-jurisdictional governance. Furthermore, it explores synergies between blockchain and complementary technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT), demonstrating how integrated systems can enable real-time tracking, predictive analytics, and autonomous decision-making in complex supply networks. It critically addresses adoption barriers and evaluates sustainability trade-offs, suggesting that these may incentivize green blockchain innovations to mitigate energy consumption concerns. By bridging theoretical foundations with real-world case studies, this book provides actionable strategies for adopting blockchain in complex, dynamic environments.This book is structured to take the reader on a journey from the fundamental concepts of blockchain in supply chains, through its practical applications and optimizations in various industries, and finally to the specific challenges and innovative solutions for implementation.

Strategies, Barriers, and Innovations in Sustainable and Secure Network Design

Blockchain-Driven Supply Chain Management Transformation

In 1977, The Economist coined the term "Dutch disease" to describe the damage to the real economy when wealth derives from resource exports rather than productive work. On April 1, 1978, the Second Amendment to the IMF's Articles of Agreement came into force, ending gold's monetary role within the IMF system and consolidating the transition to pure fiat money. With "money" no longer backed by anything real, the alchemists' dream of a "Philosopher's Stone"--the ability to create seemingly limitless wealth out of nothing--appeared to have been realized. But while real wealth produced by human labor is finite, fiat money creation is not subject to the same physical constraint. The result was a new and far more powerful variant of Dutch disease: the Philosopher's Stone Disease. The Money Powers' financialization of economies and imposition of neoliberalism increasingly privileged finance over production. Over the next four decades, the consequences extended beyond economics, eroding the cultural and civilizational heritage and traditions of large swaths of the global population. The socioeconomic impact of this pure fiat-money regime, globally and within the United States, has been an across-the-board deterioration, while its benefits accrued overwhelmingly to less than 0.01 percent of the population. Yet creating money cannot create the real goods it commands. The system therefore depends upon a steady external supply of real goods and the recycling of part of the resulting surpluses into U.S. financial assets. Energy revenues from West Asia have been key to sustaining it. A resurgent Iran thus posed an existential threat to the UK-established and U.S.-dominated oil order. Sanctions, assassinations, proxy wars, color revolutions, terrorist attacks and mass psychological manipulation followed, but failed to achieve their objective. If Iran emerges victorious from the war launched against it in 2026 and breaks U.S. control over the oil-rich Levant, the petrodollar recycling system will suffer a massive blow, accelerating withdrawal from U.S. Treasuries. The dilemma is stark: financial dominance ultimately requires real power to enforce it, while the Philosopher's Stone Disease has hollowed out the productive and military foundations of that power. Why the West Can't Recover: The Philosopher's Stone Disease explains why there may be no way back.

The Philosopoher's Stone Disease

Why the West Can't Recover

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

ADVANCED MACROECONOMICS: AN INTRODUCTION FOR UNDERGRADUATES (SECOND EDITION)

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms. The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

Towards an AI Algorithm for Multiple Objectives in Imperfect Markets

Legal Data, Digital Assets and Smart Contracts for Capital Markets

FOUNDATIONS OF FINANCIAL DATA SCIENCE: METHODS, MODELS, AND APPLICATIONS

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