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This article advocates for government sponsored research internships for undergraduates, similar to the National Science Foundation's (NSF's) Research Experiences for Undergraduates program, collectively referred to as REU programs, as essential for promoting equity in computing education and research. It emphasizes that such programs offer vital research experience and opportunities for students who face institutional or financial barriers, and highlights how well-designed REUs with strategic recruitment, mentorship, and evaluation can significantly boost diversity and prepare students for advanced academic and professional paths. The article also calls for increased investment and support from faculty and industry to expand these valuable programs.

The article explores the emergence of machine learning as a society-changing technology, which has triggered concerns about humanity's ability to understand the reasoning of increasingly complex models. Interpretable machine learning (IML) is an attempt to respond to these concerns with the goal of empowering stakeholders. Various methodologies and a workflow for establishing IML diagnostics are also offered.

The article explores FPGAs, field-programmable gate arrays, and how they might be used in a variety of applications and industries, including client compute hardware. FGPAs are used in the early stages of hardware design include rapid prototyping, testing, and development. Challenges to using FPGAs are also noted as are benefits.

The article looks at mentoring in the computer science fields of programming languages and computer architecture. The authors outline two volunteer-based multi-institution mentoring programs they were involved in creating, SIGPLAN-M and Computer Architecture Long-term Mentoring (CALM). Topics include how the programs recruit mentors and match them with mentees; how mentees say they have benefited from their relationships with mentors; and challenges they faced in setting up and administering the programs.

The article presents a selection of research papers focusing on the theme of convergence, also known as eventual consistency, and specific computer science topics including systems, programming languages, human-computer interaction, and data management. Topics include conflict-free replicated data type (CRDT), consistency as logical monotonicity (CALM), and mergeable replicated data types (MRDTs).

This article looks at future research into computer science with an emphasis on preventing further climate change. The author details how future computer technology, both hardware and software, should have limits in place to minimize environmental impact. As well, the existing digital world needs to be evaluated and potentially modified significantly if there is proof it is negatively impacting the environment.

A personal narrative is presented in which the author discusses her experiences with imposter syndrome, the necessity for computer science researchers to be familiar with it, and its potential impact upon research.

The article explores how data thinking can can be incorporated into computer science education. Particular focus is given to data science, which the authors describe as a new research and applications field that is comprised of computer science, mathematics, statistics and real-world domain knowledge. The importance of understanding data and data thinking in the 21st century is also discussed.

The article profiles the Qatar Computing Research Institute computer science laboratory since its founding by the Qatar Foundation in 2010. Alleged difficulties in attraction and retention of researchers, interns, and graduate students are described, the mission and philosophy of the lab to advance the prominence of Arabic-language computer science research is outlined, and information is offered on the establishment of scientific advisory committees on topics including artificial intelligence, social computing, and Arabic language technologies.

We envision a new generation of computation devices, computational materials, which are self-sustainable, cheaply manufactured at scale and exhibit form factors that are easily incorporated into everyday environments. These materials can enable ordinary objects such as walls, carpet, furniture, jewelry, and cups to do computational things without looking like today's computational devices. Self-powered Audio Triboelectric Ultra-thin Rollable Nanogenerator (SATURN) is an early example of a computational material that can sense vibration, such as sound. SATURN can be manufactured from inexpensive components, is flexible so that it can be integrated into many different surfaces, and powers itself through the sound or vibration it is sensing. Using radio backscatter, we demonstrate that SATURN's sensed data is passively transmitted to remote computers, alleviating the need for batteries or any wired power for the material itself. The proliferation of these types of computational materials ushers an era of Internet of Materials, further blurring the distinction between the physical and digital worlds. [ABSTRACT FROM AUTHOR]

The authors discuss the problem of replication in computer science research. They mention the typical format for periodical articles reporting on a hypothesis and its testing, the effects of publication biases particularly on articles that present a null hypothesis, and present suggestions for improving the process.

The article considers how indistinguishability is central to the abstraction and interaction inherent to computer science, and gives four specific examples of this phenomena in which components of a program lack knowledge or awareness of other components. It notes the topological nature of indistinguishability and reports it is often the source of lower bounds and impossibility reports.

The article provides an answer to a question concerning pursuing a doctoral degree in midlife in order to move from working in development to working in research.

The article discusses qubit computing research, particularly efforts to scale qubit devices while simultaneously reducing errors and noise in order to maximize the usefulness of such devices. The article also examines the technological development of qubit devices.

The author discusses the issue of neural computing on computer science research. He mentions the slowing of Moore's law as it pertains to computer research, the advances in neurocomputing which enable the use of faster algorithms, and the relation between neurosciences and machine learning.

The author discusses the concept of edge computing which brings computing closer to the sources of data. He mentions its relation to cloud computing and the Internet of Things, its use in named data networking, and the potential applications for such computing as well as the need for further research.

The authors discuss the issue of embedded computer systems in modern devices. They mention the use of embedded technology in the Internet of Things and cyber physical systems, the operating systems and wide area networks that such technology requires, and the ongoing computer research in Europe to support the technology.

A unique perspective on experiences encouraging students to focus on further education. [ABSTRACT FROM AUTHOR]

The authors argue in favor of automating declarations of conflicts of interest in academic discourse about computer science research. They argue that the growth of academic computer science research requires a scaling up of bibliographic data sources and manuscript management systems. They also make several proposals such as self-reporting requirements, the establishment of conflict-of-interest-free committees, and an updated definition of conflict of interest.

The article discusses the notion of limits in relation to computing research. Topics include the notion of economic growth within industrial civilizations, ecological constraints affecting human life and technology, and the notion of Sustainable Human-Computer Interaction. The notions of crisis informatics and Information and Communication Technology for Development (ICTD) are addressed.

The authors present their thoughts on the field of computer science following the advent of more unconventional computing such as quantum computing, DNA processors, and human social machines. They argue more emphasis should be placed on the physical computers, noting that one computational model no longer encompasses all the field's necessities. Comparing computer science to natural science, they suggest that new computers could inform new computational theories.

The article discusses research articles on topics including tracing and debugging of distributed systems and the use of programming by examples. Articles cited include "Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems" in the publication "Proceedings of the 25th Symposium on Operating Systems Principles," "Automating Failure-Testing Research at Internet Scale" in the 2016 publication "Proceedings of the 7th ACM Symposium on Cloud Computing," and "Scaling Up Superoptimization" in the 2016 publication "Proceedings of the 21st International Conference on Architectural Support for Programming Languages and Operating Systems."

The article discusses the challenges and strategies for the widespread adoption of service computing. Topics include the role of service computing in cloud computing, big data, the Internet of Things (IoT), and social and mobile computing, organizations' addition of service interfaces to their online services to improve accessibility and agility, and the emergence of web service technologies as a cross-disciplinary research field studying the science and technology underlying the IT service industry.

The article offers research related to CS (Computer Science) as of 2017. Particular focus is given to research relating to using computer networks as physical sensors to monitor breathing and even look through walls. The use of atomic clocks, high-performance read-write transactions and Wi-Fi technology.

We present a novel imaging technique, which we call femtophotography, to capture and visualize the propagation of light through table-top scenes with an effective exposure time of 1.85 ps per frame. This is equivalent to a resolution of about one half trillion frames per second; between frames, light travels approximately just 0.5 mm. Since cameras with such extreme shutter speed obviously do not exist, we first re-purpose modern imaging hardware to record an ensemble average of repeatable events that are synchronized to a streak sensor, in which the time of arrival of light from the scene is coded in one of the sensor's spatial dimensions. We then introduce reconstruction methods that allow us to visualize the propagation of femtosecond light pulses through the scenes. Given this fast resolution and the finite speed of light, we observe that the camera does not necessarily capture the events in the same order as they occur in reality: we thus introduce the notion of time-unwarping between the camera's and the world's space-time coordinate systems, to take this into account. We apply our femto-photography technique to visualizations of very different scenes, which allow us to observe the rich dynamics of time-resolved light transport effects, including scattering, specular reflections, diffuse interreflections, diffraction, caustics, and subsurface scattering. Our work has potential applications in artistic, educational, and scientific visualizations; industrial imaging to analyze material properties; and medical imaging to reconstruct subsurface elements. In addition, our time resolved technique has already motivated new forms of computational photography, as well as novel algorithms for the analysis and synthesis of light transport. [ABSTRACT FROM AUTHOR]

The article examines natural language understanding as it relates to computer science. Particular focus is given to how this relates to artificial intelligence (AI) and its long-standing goals. Additional topics discussed include semantic parsing framework, compositionality, a principle attributed to the philosopher Gottlob Frege, and context as it relates to language.

In this article, various experts on computer science (CS) offer guides relating to the best of CS research. Particular focus is given to how to determine what papers are worth taking the time to read. Additional topics discussed include the ACM (Association for Computing Machinery), how datacenters are changing the way Web servers are designed and the notion of Network Functions Virtualization (NFV).

The article discusses the development of quantum computing in relation to early development of conventional computing. Topics include the role of qubits as circuits in quantum computers, applications for quantum computing, and the significance of quantum encryption and secure communications in relation to quantum computing.

The article discusses various issues related to academic computer science research. Topics include debates on software-development methodology in relation to independent faults, a debate on the evaluation of file system performance, and the use of software-based attestation (SWATT) as a protocol for checking memory images from remote systems.

The article examines a dataset of 1.5 million computer science research papers maintained by Microsoft Academic Search. The authors found that the citation count of the articles over the years follows diverse patterns. Each article included bibliographic information such as title, unique index, author affiliation, abstract and keywords, year of publication, and publication place. The authors' findings increase the scope for reinvestigation of bibliometric indices for scientific research, not just for computer science.

The article focuses on artificial intelligence (AI) and human-computer interaction (HCI). In the beginning, HCI focused more on empirical approaches to usability and human factors, which aim to make machines more useful for human beings. The authors discuss natural language processing as an intersection between AI and HCI. According to them, human translators are using the output of machine translation systems like Google Translate into their work. J.C.R. Licklider's research paper "Man-Computer Symbiosis," discusses introduction of human factors in computing.

The widely studied I/O and ideal-cache models were developed to account for the large difference in costs to access memory at different levels of the memory hierarchy. Both models are based on a two level memory hierarchy with a fixed size fast memory (cache) of size M, and an unbounded slow memory organized in blocks of size B. The cost measure is based purely on the number of block transfers between the primary and secondary memory. All other operations are free. Many algorithms have been analyzed in these models and indeed these models predict the relative performance of algorithms much more accurately than the standard Random Access Machine (RAM) model. The models, however, require specifying algorithms at a very low level, requiring the user to carefully lay out their data in arrays in memory and manage their own memory allocation. We present a cost model for analyzing the memory efficiency of algorithms expressed in a simple functional language. We show how some algorithms written in standard forms using just lists and trees (no arrays) and requiring no explicit memory layout or memory management are efficient in the model. We then describe an implementation of the language and show provable bounds for mapping the cost in our model to the cost in the ideal-cache model. These bounds imply that purely functional programs based on lists and trees with no special attention to any details of memory layout can be asymptotically as efficient as the carefully designed imperative I/O efficient algorithms. For example we describe an o(...logM/B...) cost sorting algorithm, which is optimal in the ideal cache and I/O models. [ABSTRACT FROM AUTHOR]

Computer scientist Juris Hartmanis reflects on his career in the field of computational complexity theory. Topics include reflection on his childhood in Latvia in the interwar period, and in Germany at the end of World War II and in the post-War period; his experience as a graduate student and immigrant in the U.S.; and his experience researching partition lattices and inventing the theory of generalized partitions with algebraist Robert Dilworth. A reflection on his time as a computer technology researcher with multinational conglomerate General Electric is included.

The article looks at the intersection of computing and biology, focusing on the implications of the presence of distributed algorithms of control and information processing in both computational and biological systems. It notes that researchers in each discipline are making use of models from the other and discusses how the most useful topics of such intersecting studies can be identified. Topics include the network of finite state machines (nFSM)-based communication model, shared memory models, and stochastic decision-making.

The article offers an overview and analysis of research done in the field of computer hardware architecture between 1997 and 2011. It discusses a keyword analysis of a large number of journal articles in the field published during that period, noting keywords whose frequency rose over the period including wireless sensor network and reliability, and keywords whose frequency fell over the period, including neural network and fault tolerance. It discusses the representation of various countries and various institutions among the authors of the papers analyzed as well as the change in the share of papers involving international collaboration.