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Chenyang Lu is not a civil engineer.

For a computer scientist, though, he builds a lot of bridges. Particularly between the fields of computer science and health care.

Lu is the Fullgraf Professor in the Department of Computer Science & Engineering at Washington University in St. Louis McKelvey School of Engineering. His research is concerned with the Internet of Things (IoT), cyber-physicalsystems and artificial intelligence, and he is particularly keen on how these technologies can improve healthcare.

As part of several teams with surgeons and physicians, Lu has been testing Fitbit activity trackers in studies that have shown that these relatively inexpensive wearable devices can play a valuable role in improving patient health.

We can collect data such as step count, heart rate and sleep cycles, which we use with our machine-learning models to predict deterioration or improvement in a patients health status. Lu said. These efforts demonstrate tremendous potential for wearable and machine learning to improve health care.

Using data from Fitbits, for example, Lu and his collaborators have demonstrated the ability to predict surgical outcomes of pancreatic cancer patients with higher success than the current risk assessment tool.

The goal is improved health care, but where some of the most challenging problems arise, Lu finds engineering solutions. Obstacles can include subpar data, or simply not enough data to get useful information from wearable devices.

You have to extract features using engineering techniques, Lu said. How do we take this noisy, lousy data from wearables and extract robust and predictive features to generate something clinically meaningful and informative so we can actually predict something?

Getting useful information from messy data is one of the reasons his colleagues at the School of Medicine value his partnership.

Chenyang has established himself as an expert in how to interpret and connect the dots for this high-dimensional data. Thats why I think hes so prolific, said Philip Payne, the Janet and Bernard Becker Professor and director of the Institute for Informatics, associate dean for health information and data science and chief data scientist at the School of Medicine.

Prolific he may be, but Lu is eager to do more.

We can scale this up to perfect the technology and broaden the scope so it can be used on larger groups of different types of patients, Lu said. I look forward to collaborating with even more physicians and surgeons to expand this work.

Read more on the engineering website.

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Washington People: Chenyang Lu - The Source - Washington University in St. Louis - Washington University in St. Louis Newsroom

Self-service data science capabilities and integrations with Slack highlight the latest Tableau analytics platform upgrades.

Tableau, founded in 2003 and based in Seattle, unveiled new capabilities -- not all of which are generally available -- on Tuesday during Tableau Conference 2021, the vendor's virtual user conference.

Both the self-service data science capabilities and Slack integrations are slated for general availability in 2022. And according to Francois Ajenstat, Tableau's chief product officer, the impetus for developing both was Tableau's mission of enabling people to better see and understand data.

"What we're trying to do is make analytics easier to use for anyone, anywhere, with any data, and we're trying to do that by broadening access to analytics so that it's available to everyone," he said on Nov. 8 during a virtual press conference. "We need to make analytics dramatically easier to use -- more accessible and more collaborative."

The self-service data science capabilities aim to extend predictive analytics capabilities beyond data scientists while the integrations with Slack enable collaboration, Ajenstat continued.

"We're going to extend the advanced capabilities of the platform, [and] and we're going to bring analytics in the flow of business so that everyone can be a data person," he said.

Tableau, which was acquired by Salesforce in June 2019, introduced the concept of business science in March 2021 when it unveiled its first integration with Salesforce's Einstein Analytics in Tableau 2021.1. Business science, as defined by Tableau, is enabling business users without training in statistics and computer science with data science capabilities using augmented intelligence and machine learning.

The integration added Einstein Discovery -- a no-code tool in Salesforce's Einstein Analytics platform -- to Tableau to give Tableau customers the ability to do predictive modeling and generate prescriptive recommendations.

In 2022, Tableau analytics platform updates will build on the initial business science capabilities enabled by Einstein Discovery with the additions of Model Builder and Scenario Planning.

Model Builder is designed to help teams collaboratively develop and consume predictive models within their Tableau workflows using Einstein Discovery. Scenario Planning, meanwhile, takes advantage of Einstein's AI capabilities to enable users to compare scenarios, build models and understand expected outcomes to better make data-driven decisions.

The business science capabilities are very interesting to me. With solutions that enable business agility being so important today, Model Builder and Scenario Planning will prove to be a difference-maker in the future direction of modern businesses. Mike LeoneAnalyst, Enterprise Strategy Group

Once generally available next year, the two capabilities will be significant for users, according to Mike Leone, an analyst at Enterprise Strategy Group.

"The business science capabilities are very interesting to me," he said. "With solutions that enable business agility being so important today, Model Builder and Scenario Planning will prove to be a difference-maker in the future direction of modern businesses."

The key to their effectiveness will be their ability to simplify what are otherwise complex tasks, Leone continued.

"What-if analysis can be a difficult endeavor without the right data and tools, but with Tableau expanding their business science capabilities, they are looking to drastically simplify planning, prediction and outcome analysis in a collaborative way rooted in AI and self-service," he said.

Likewise, Boris Evelson, an analyst at Forrester Research, noted that Tableau is at the forefront of adding augmented analytics capabilities to its platform, but noted that the vendor is not alone in that respect.

"What we now call Augmented BI -- BI infused with AI -- is a capability that most modern BI platforms have already invested in," he said.

"In our recent [research], Tableau was found as one of the leaders in that evaluation, but so were Microsoft, Oracle, Tibco, Sisense and Domo," Evelson said, referring to other tech giants and independent vendors with popular analytics systems.

In addition to the added business science capabilities, Tableau analytics platform updates next year will include three new integrations with Slack, which Salesforce acquired for $27.7 billion in December 2020.

When ready for release, Tableau users will have access to Ask Data in Slack, Explain Data in Slack and Einstein Discovery in Slack.

Ask Data is an AI capability that enables users to query data using natural language rather than requiring them to write code, while Explain Data is automatically generates explanations of data points. Both were first introduced in 2019 and were upgraded in Tableau's June 2021 analytics platform update.

"The Slack integration is very notable," Evelson said.

It's notable, he continued, because most people who use data to inform their decisions don't spend the majority of their time in their analytics platform environments. Instead, they spend most of their time in work applications and collaboration platforms.

"BI platforms are not what we call systems of work -- digital workspaces where people live 9 to 5," Evelson said. "These decision-makers' systems of work are ERP, CRM, planning/budgeting or other business applications, or productivity applications such as email, calendar, and increasingly -- due to remote work -- collaboration tools like Slack."

Similarly, Leone noted that Tableau's integrations with Slack are in line with what data workers now require and have the potential to enable new discovery.

"I think collaboration enablement is critical to the next level of data-centric adoption, and Tableau's announcements are aligned perfectly," he said. "Imagine being in a Slack channel and seeing a team member ask a data question with an instant answer. That answer could introduce a new data angle to attack a problem or spark an open discussion that leads down a new innovation path."

Beyond the expansion of its business science capabilities and Slack integrations, Tableau unveiled a host of other features both generally available now and scheduled for upcoming analytics platform updates.

Among them are security, administration, community engagement and collaboration tools, including:

Virtual Connections, Centralized Row-Level Security, the Tableau Exchange and Hire Me button in Tableau Public are now generally available.

Connected Applications will be available with the release of Tableau 2021.4 before the end of the year, and all other capabilities are expected to be generally available in 2022, according to Tableau.

Beyond helping users better see and understand their data, data governance is a priority for Tableau, according to Ajenstat. Features such as Centralized Row-Level Security and Share Prep Flows are aimed at addressing the trustworthiness and security of data.

"Having access to data is really important, but we need to also make sure people can trust the data," Ajenstat said. "If you can't trust the data, you can't trust the insight, and this is why we need to make trust a fundamental part of the Tableau platform."

Enterprise Strategy Group is a division of TechTarget.

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Tableau to add new business science tools to analytics suite - TechTarget

In this male patriarchal society, female achievers are often forgotten by the world. We are well versed with the fact that there are many successful male programmers in the world. But how many of us know about the women programmers whose contribution is incomparable in computer science and technology? Quite a few right? It is true that many female programmers have contributed a lot to computer programming. Women in computing were among the first programmers in the early 20th century who contributed largely to the industry. With the advancement of technology, the role of women as programmers is also increasing enormously but remains obscure. Since the 18th century, women have been dominantly working in the field of programming and scientific computations. Due to the gender disparity, females could never get the limelight in comparison with their male counterparts. Nevertheless, women continue to work hard and make significant contributions to the programming and IT industry. Women also hold significant roles in multi-tech companies such as Yahoo, Google, Microsoft, and many more.

Heres the list of the top 10 best women programmers of all time:

Ada Lovelace is also known as Augusta Ada King is regarded as the first female computer programmer. She was an extremely good mathematician and writer. Ada was an influential pioneer in the field of computer research and programming. She is primarily known for her work on Charles Babbages proposed mechanical general-purpose computer, the Analytical Engine. She was the first person to find out machines can do far more than calculations and also published the first algorithm by such a machine.

Grace Brewster Murray Hopper was an American computer scientist. She was a computer programmer who invented one of the first linkers and discovered bugging for fixing programming errors and technical glitches. She invented a compiler for computer programming language and also publicized the idea of machine-independent programming language. She formed the theory of FLOW-MATIC programming language and later helped in the development of COBOL, a high-level programming language.

Joan Clarke was a cryptanalyst who became famous for her role as a codebreaker in the second world war. She was the only woman who worked on solving the German Enigma messages along with Alan Turing. But due to gender biases, she got less wage even when at the same position along with her male co-workers. She took against this by transforming into a linguist. She is considered as genius British for her code-breaking ground.

Margaret Heafield Hamilton is a well-known scientist for her work in the fields of computer science, system engineer, and business owner. She introduced the term software engineering and became the head of the software engineering division at MIT Instrumentation Laboratory for developing onboard flight software for the Apollo space program. She designed the asynchronous system giving priority to only important functions and rejecting the rest.

Adele Goldberg is a computer scientist known for developing the programming language Smalltalk-80 and various other object-oriented programmings. She introduced a programming environment of overlapping windows on graphics display screens. She was also involved in designing templates and patterns in modern software. Apple implemented her methods in their Macintosh computers

Francis Elizabeth Allen is a computer scientist best known for her work in the field of optimizing compilers, program optimization, and parallelization. She was known for working on programming language compilers for IBM Research. Allen received the IBM fellow title award, regarded as the highest recognition for scientists, engineers, and programmers for the company. She also introduced many algorithms and implementations for automatic program optimization technology.

Barbara Liskov was a successful programmer who also won the Turing award for developing the Liskov Substitution principle. He has worked on various important projects like the Venus Operating system which is an affordable and interactive timesharing system. The first high-level language Argus was created by her and demonstrates the technique of pipelining and Thor, an object-oriented database system. Barbara also led the Programming Methodology Group of MIT.

She was an American computer scientist. She was one of the members of the ten-member team at IBM for the development of FORTRAN, a high-level programming language. She was the only female programmer there. She examined the flow of programs produced by the compilers. She developed the first syntactic analyzer of arithmetic expressions.

Shafrira Goldwasser is an American computer scientist and another winner of the Turning award in 2012 for a number of theories. She is well known for her works in computational complexity theory, cryptography, and computational number theory. She helped in the creation of probabilistic encryption and zero-knowledge proofs, a cryptographical protocol. Currently, she is a professor in the department of electrical engineering and computer science at MIT.

Anita Borg is a reputed American computer scientist and the founder of the Institute for Women and Technology. She is the brain behind the idea of Systers in the year 1987. She worked for Digital Equipment Corporation when she developed a technique for generating, analyzing, and designing a high-speed memory system. Bill Clinton also appointed her as an important member of the Committee on the Advancement of women and minorities in science.

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Top 10 Best Women Programmers of All Time - Analytics Insight