Collaborating Authors


Learning New Things and Avoiding Obstacles

Communications of the ACM

ACM A.M. Turing Award recipient Jack Dongarra never intended to work with computers. Initially, the Distinguished Professor at the University of Tennessee and founder of the Innovative Computing Laboratory (ICL) thought he would be a high school science teacher. A chance internship at the Argonne National Laboratory kindled a lifelong interest in numerical methods and software--and, in particular, in linear algebra, which powered the development of Dongarra's groundbreaking techniques for optimizing operations on increasingly complex computer architectures. Your career in computing began serendipitously, with a semester-long internship at Argonne National Laboratory. As an undergraduate, I worked on EISPACK, a software package designed to solve eigenvalue problems.

Global Big Data Conference


Researchers at Duke University have demonstrated that incorporating known physics into machine learning algorithms can help the inscrutable black boxes attain new levels of transparency and insight into material properties. In one of the first projects of its kind, researchers constructed a modern machine learning algorithm to determine the properties of a class of engineered materials known as metamaterials and to predict how they interact with electromagnetic fields. Because it first had to consider the metamaterial's known physical constraints, the program was essentially forced to show its work. Not only did the approach allow the algorithm to accurately predict the metamaterial's properties, it did so more efficiently than previous methods while providing new insights. The results appear online the week of May 9 in the journal Advanced Optical Materials.

Widely Available AI Could Have Deadly Consequences


In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands. In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity--acting only on desired or targeted cells or neuroreceptors, for instance--and low toxicity to reduce ill effects.

Best unexpected double majors for computer science students


Genevieve Carlton holds a Ph.D. in history from Northwestern University. After earning her doctorate in early modern European history, Carlton worked as an assistant professor of history. Did you know that double majors report higher earnings? They also report greater satisfaction with their college experience. But what are the best double majors for computer science?

The most badass careers in computer science


Genevieve Carlton holds a Ph.D. in history from Northwestern University. After earning her doctorate in early modern European history, Carlton worked as an assistant professor of history. Computer science majors work as software developers, security analysts, and web developers. But what if you want something a little different? The most badass jobs in computer science will push the field's boundaries and challenge you.

Toward Justice in Computer Science through Community, Criticality, and Citizenship

Communications of the ACM

Neither technologies nor societies are neutral, and failing to acknowledge this, results at best, in a narrow view of both. At worst, it leads to technology that reinforces oppressive societal norms. We agree with Alex Hanna, Timnit Gebru, and others who argue individual harms reflect institutional problems, and thus require institutional and systemic solutions. We believe computer science (CS) as a discipline often promotes itself as objective and neutral. This tendency allows the field to ignore systems of oppression that exist within and because of CS. As scholars in educational psychology, computer science education, and social studies education, we suggest a way forward through institutional change, specifically in the way we teach CS.

ACM's 2022 General Election

Communications of the ACM

The ACM constitution provides that our Association hold a general election in the even-numbered years for the positions of President, Vice President, Secretary/Treasurer, and Members-at-Large. Biographical information and statements of the candidates appear on the following pages (candidates' names appear in random order). In addition to the election of ACM's officers--President, Vice President, Secretary/Treasurer--two Members-at-Large will be elected to serve on ACM Council. The 2022 candidates for ACM President, Yannis Ioannidis and Joseph A. Konstan, are working together to solicit and answer questions from the computing community! Please refer to the instructions posted at Please note the election email will be addressed from Please return your ballot in the enclosed envelope, which must be signed by you on the outside in the space provided. The signed ballot envelope may be inserted into a separate envelope for mailing if you prefer this method. All ballots must be received by no later than 16:00 UTC on 23 May 2022. Validation by the Elections Committee will take place at 14:00 UTC on 25 May 2022. Yannis Ioannidis is Professor of Informatics & Telecom at the U. of Athens, Greece (since 1997). Prior to that, he was a professor of Computer Sciences at the U. of Wisconsin-Madison (1986-1997).

13 Free Model Zoos for Deep Learning and Computer Vision Models


Computer vision is a fast-growing subfield of AI and deep learning. From cashierless stores in retail to crop detection in agriculture, there's an increasing interest in CV applications. This has created a vibrant community that gladly shares architectures, codes, pre-trained models, and even tips for every stage of the development cycle. Starting a CV project from scratch takes time. So, the usual process is, given a problem or a use case, you look for models that partially solve it.

Why We Need Ethical AI: 5 Initiatives to Ensure Ethics in AI


Artificial intelligence (AI) has already had a profound impact on business and society. Applied AI and machine learning (ML) are creating safer workplaces, more accurate health diagnoses and better access to information for global citizens. The Fourth Industrial Revolution will represent a new era of partnership between humans and AI, with potentially positive global impact. AI advancements can help society solve problems of income inequality and food insecurity to create a more "inclusive, human-centred future" according to the World Economic Forum (WEF). There is nearly limitless potential to AI innovation, which is both positive and frightening.

Machine learning engineering: The science of building reliable AI systems


Machine learning engineering aims to apply software engineering and data science methods to turn machine learning models into usable functions for products and consumers. Artificial intelligence technology is created using machine learning engineering with massive data sets. Machine learning engineering develops AI systems and algorithms to learn and ultimately make predictions. Machine learning engineers are competent software developers who research, design, and implement autonomous programs to create predictive models. Engineers must evaluate, analyze, and organize data, execute experiments, and optimize the training procedure to construct high-performance machine learning models.