What next-generation scholars need to know in order to thrive, and how they can actively participate in shaping the academic research enterprise. The academic research enterprise is highly complex, involving multiple sectors of society and a vast array of approaches. In Demystifying the Academic Research Enterprise, Kelvin K. Droegemeier shows next-generation scholars across all disciplines how to become more productive earlier in their career, as well as how to help shape the academic research enterprise. The topics covered include public perceptions of scholarly work and its use in policy; understanding the big picture of funding and national priorities as well as identifying funding sources; research methods; collecting data and materials; writing grant proposals; publishing results; ethical conduct; bias and peer review; intellectual property and compliance regulations; partnerships and collaboration; diversity, equity, and inclusion; and the future of research. Droegemeier’s two principal goals are to enhance and accelerate scholars’ understanding of the academic research process and to democratize that understanding, particularly at institutions that traditionally are underrepresented or lack robust resources. While intended for undergraduate and graduate students, postdoctoral scholars, and early career faculty, Demystifying the Academic Research Enterprise is also relevant to mid-career and senior faculty, research administrators, funding organizations, congressional staff, policymakers, and the general public. Droegemeier places scholars in a broader national and international context—not as passive recipients of the existing system but as key actors who actively participate in helping to set priorities, determine policies, drive systemic change, and advance knowledge.

What next-generation scholars need to know in order to thrive, and how they can actively participate in shaping the academic research enterprise. The academic research enterprise is highly complex, involving multiple sectors of society and a vast array of approaches. In Demystifying the Academic Research Enterprise, Kelvin K. Droegemeier shows next-generation scholars across all disciplines how to become more productive earlier in their career, as well as how to help shape the academic research enterprise. The topics covered include public perceptions of scholarly work and its use in policy; understanding the big picture of funding and national priorities as well as identifying funding sources; research methods; collecting data and materials; writing grant proposals; publishing results; ethical conduct; bias and peer review; intellectual property and compliance regulations; partnerships and collaboration; diversity, equity, and inclusion; and the future of research. Droegemeier’s two principal goals are to enhance and accelerate scholars’ understanding of the academic research process and to democratize that understanding, particularly at institutions that traditionally are underrepresented or lack robust resources. While intended for undergraduate and graduate students, postdoctoral scholars, and early career faculty, Demystifying the Academic Research Enterprise is also relevant to mid-career and senior faculty, research administrators, funding organizations, congressional staff, policymakers, and the general public. Droegemeier places scholars in a broader national and international context—not as passive recipients of the existing system but as key actors who actively participate in helping to set priorities, determine policies, drive systemic change, and advance knowledge.

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

The former president of MIT discusses challenges and policy issues confronting academia, science and technology, and the world at large. In his fourteen years as president of MIT, Charles Vest worked continuously to realize his vision of rebuilding America's trust in science and technology. In a time when the federal government dramatically reduced its funding of academic research programs and industry shifted its R&D resources into the short-term product-development process, Vest called for new partnerships with business and government. He called for universities to meet the intellectual challenges posed by the innovation-driven, globally connected needs of industry even as he reaffirmed basic academic values and the continuing need for longer-term scientific inquiry. In Pursuing the Endless Frontier, Vest addresses these and other issues in a series of essays written during his tenure as president of MIT. He discusses the research university's need to shift to a broader, more international outlook, the value of diversity in the academic community, the greater leadership role for faculty outside the classroom, and the boundless opportunity of new scientific and technological developments even when coupled with financial constraints. In the provocative essay "What We Don't Know," Vest reminds us of what he calls "the most critical point of all," that science is driven by a deep human need to understand nature, to answer the "big questions"—that what we don't know is more important than what we do. In another essay, on the future of MIT, he celebrates MIT's strengths as being extraordinarily well-suited to the needs of an era of unprecedented change in science and technology. In "Disturbing the Educational Universe: Universities in the Digital Age—Dinosaurs or Prometheans," he describes MIT's innovative OpenCourseWare initiative, which builds on the fundamental nature of the Internet as an enabling and liberating technology. Vest, who is stepping down from MIT's presidency in the fall of 2004, writes with clarity and insight about the issues facing academic institutions in the twenty-first century. His essays in Pursuing the Endless Frontier offer inspiration to educators and researchers seeking the way forward.

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

"The book is a guide for academic researchers, especially scientists and engineers, on how to move their discoveries to the marketplace. Few academics understand what tech transfer is or how it works, and many shy away from it because they equate commercialization with starting a company. Yet those same individuals can be intrigued to learn of additional pathways that enable discoveries to be translated into marketable products or services. We help researchers explore multiple routes for commercialization, guides them through the personal decisions they must face, describes programs designed to help them, and provides advice to avoid common problems. We frame commercialization as the primary (often the only) way for research to solve societal problems. Impact can best be achieved if, a discovery leads to an invention/ that fills an unmet need in the marketplace. The range of entities that support technology transfer are described, and we offer best practices for researchers to maximize support the process. Engaging researchers effectively requires that institutions themselves adapt. Aligning commercialization with the rewards system is crucial, and integrating commercialization training into graduate and postdoctoral programs will produce the next generation of academic inventors. Furthermore, women and minorities face special challenges that must be overcome so that everyone's discovery receives support for commercialization. Woven through the book are profiles of academic inventors, which illustrate key points and help researchers to visualize themselves in such a role"--

This book brings together the lessons of research on both the nature of learning and different educational applications, and it summarises these as seven key concluding principles.