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Shanghai, Sept. 30, 2022 (GLOBE NEWSWIRE) -- The 2022 WLA Prize Laureates are:

--"For fundamental contributions to the foundations of machine learning and its application."

About the Laureate

Prof. Michael I. Jordan has been a world-leading researcher in the field of statistical machine learning for nearly four decades. His contributions to the interface between computer science and statistics include the variational approach to statistical inference and learning, inference methods based on graphical models and Bayesian non-parametrics, and characterizations of trade-offs between statistical risk and computational complexity.

He has also worked at the interface between optimization and machine learning, where he is well known for his development of continuous-time models of gradient-based optimization and sampling, and his work on distributed systems for optimization. He has built bridges between machine learning and control theory, contributing to the theory of reinforcement learning, learning-based model predictive control, and optimality principles for human motor control.

He has also led the way in bringing microeconomic concepts into contact with machine learning, developing learning methods that incentivize learners to share data, showing how contract theory can be employed for statistical inference, and contributing to the study of learning-based matching markets.He has also pursued numerous high-impact applications of machine learning in domains such as single-molecule imaging, protein modeling, genetic admixture modeling, and natural language processing.

Prof. Jordan's contributions to computer science are also evident in education. He has mentored over 80 PhD students and over 60 postdoctoral researchers, an influential cohort who are now professors at the world's leading academic institutions and leaders in the industry.

--"For key discoveries elucidating the mechanism and selectivity of protein transport between the cytoplasm and nucleus."

About the Laureate

Dr. Dirk Grlich was born in Halle/Saale in Germany and studied biochemistry at Martin Luther University in Halle. For his Ph.D., he joined Tom Rapoport's lab in Berlin, where he identified the heterotrimeric Sec61 complex as a receptor for translating ribosomes and protein-conducting channels of the endoplasmic reticulum (ER). He also succeeded in reconstituting a fully functional "translocon" from purified components and demonstrated its capacity to transport secretory proteins across the ER membrane and to integrate type I and type II membrane proteins into the lipid bilayer.

In 1993, Dr. Grlich joined Ron. Laskey's lab at the University of Cambridge, where he discovered the first importins as mediators of protein import into the cell nucleus.

In 1996, he became an independent group leader and later a professor of molecular biology at the ZMBH (University of Heidelberg). During this time, he developed the RanGTP-gradient model to explain the directionality and energetics of nuclear transport. His group first described chaperone functions of importins and was instrumental in discovering and characterizing exportins that mediate export from the cell nucleus.

Dr. Grlich is now a director at the Max Planck Institute for Multidisciplinary Sciences in Gttingen, focusing on the question of how nuclear pore complexes function as highly efficient transport machines. His team discovered that intrinsically disordered FG domains assemble into a condensed (selective) FG phase that serves as a highly selective permeability barrier of extreme transport capacity. His group also develops nanobodies as cell biological tools and, more recently, also as therapeutics for treating diseases such as Covid-19, malaria, bacterial infections, sepsis, and autoimmune conditions.

Roger KORNBERG, Chairman of the WorldLaureatesAssociation and 2006 Nobel Laureate in Chemistry, said that The WLA Prize advocates for original basic science and encourages scientific researchers to be better committed to the common well-being of human beings. It is believed that the WLA Prize, established in China through multi-lateral efforts, will become one of the world's globally influential awards.

Michael LEVITT, Vice Chairman of the World Laureates Association and 2013 Nobel Laureate in Chemistry announced the 2022 WLA Prize laureates.YANG Wei, Member of the Chinese Academy of Sciences, Foreign Member of the National Academy of Engineering (USA), and Fellow and Treasurer of the World Academy of Sciences (TWAS) also attended the press conference.

Global technological development has brought revolutionary and far-reaching impact since the start of this century, and the pace of development is only accelerating, said Neil SHEN, StewardofSequoiaCapitalFoundingandManagingPartnerofSequoiaChina, which is the exclusive sponsor of the WLA Prize. Sequoia China is committed to supporting cutting-edge technology and fundamental research and encouraging those who push forward the frontiers of science.

WU Xiangdong , Executive Director of the World Laureates Association and Chairman of the WLA Prize Management Committee announced that the Award Ceremony of the inaugural WLA Prize will be solemnly held at the Opening Ceremony of the 5th WLA Forum in early November 2022; both of the laureates are on schedule to Shanghai to accept their awards.

About the WLA Prize

The World Laureates Association Prize (WLA Prize) is an international science prize established in Shanghai, in 2021, initiated by World Laureates Association (WLA), managed by the WLA Foundation, and exclusively funded by Sequoia China.

The WLA Prize aims to recognize and support eminent researchers and technologists worldwide for their contributions to science. It is intended to support global science and technology advancement, address the challenges to humanity, and promote society's long-term progress.

Each year, the WLA Prize is awarded in two categories: the "WLA Prize in Computer Science or Mathematics" and the "WLA Prize in Life Science or Medicine."

The total award for each Prize, which may be divided among up to four laureates, is RMB 10 million.

More info about the WLA Prize:

http://www.wlaprize.org

About Us

World Laureates Association

The World Laureates Association (WLA) is a non-governmental and non-profit international organization. It is one of the world's highest profile organizations of laureates with three missions: advocacy for basic science, promotion of international cooperation, and support for young scientists. Upholding the vision of "Science and Technology for the Common Destiny of Mankind," the WLA is committed to enhancing the academic exchange of ideas and research among scientists and scholars in China and the world.

Follow Us for updates on Facebook and Twitter@wlaforum

WLA Foundation

The WLA Foundationsupports all WLA activities and is funded entirely by donations from private sources.

Sequoia China

Sequoia China helps daring founders build legendary companies. In partnering with Sequoia, companies benefit from its unmatched community and the lessons Sequoia has learned over the years. As "The Entrepreneurs Behind The Entrepreneurs", Sequoia China focuses on three sectors: tech, consumer and healthcare. Over the past 17 years, Sequoia China has had the privilege of working with more than 900 companies. It is committed to advancing innovation in science and technology. It actively supports scientists and entrepreneurs, promotes technological innovation, and nurtures leading tech-enabled enterprises, with a concern for corporate social responsibility. As the exclusive sponsor of the World Laureates Association (WLA) Prize, Sequoia China hopes that its support will encourage the pursuit of innovative scientific developments and drive growth across the world.

Link:
Winners of the Inaugural WLA Prize Announced RMB 10 Million for Each Prize - GlobeNewswire

From taking home gold in the Delaware Valley Science Fair competition his sophomore year to having one of his most time-consuming and difficult research papers rejected at a regional competition Yash Prabhu turns his failure into a success story.

Yash Prabhu starts the school year strong with one of his research papers being published at a conference called IEEE. IEEE is an organization dedicated to assisting humanity through enhancing technology. The organization sponsors over 2,000 events yearly and organizes top-tier conferences with published papers being recognized by academia and industries. Prabhu recently had a paper published called A CNN Based Automated Stuttering Identification System, where he uses machine learning to detect different types of stuttering in audio segments.

Stuttering affects a lot of people around the world and its a surprisingly ignored issue. Some people who stutter receive speech therapy but a lot of people dont. Stuttering can damage the quality of life for people. It makes it harder to speak and harder to interact with people. You could get bullied, teachers could get frustrated speaking to you [and] it gets worse when youre older because you have to give meetings and presentations, explained senior Yash Prabhu.

The goal for his research paper revolves around his wish to make low-cost automation available to people worldwide, mainly in developing countries such as India where resources are scarce.

I am trying to design a model that can classify stuttering. By classifying stuttering it can help keep data. In an area where theres a lack of speech pathologists like in India, this model can have a big impact by keeping diagnostics on stuttering and also helping speech pathologists do a better and faster job so they can treat more people, Prabhu said.

The model Prabhu used is called a machine learning model. Machine learning creates functions to help make predictions.

I found a data set provided by Apple called SEP-28k and this data set [consists] of many examples of stuttering. I chose 5 different speech disfluencies and I trained my model to detect the speech disfluencies, Prabhu added.

Prabhu took the initiative to explore a data set that had not been extensively researched leading to hardships.

I emailed professors, I called doctors, I asked for access to data sets. Nothing really [worked] out because it was hard to find someone who could help me get access to data. A lot of doctors and professors are busy, they dont have time to talk to you, Prabhu said disappointed.

Nonetheless, his chances of success improved when Dr. Naeem Seliya, a professor at the University of Wisconsin Eau Claire, agreed to assist him.

I emailed him my credentials and asked him if I could work with him. He is actually a stutterer and he told me about a device he uses for stuttering. From there this idea was born in my mind. I can use my machine learning skills to have an impact in this area. At that point, I had no clue how to do it. I had absolutely no clue, I just knew I wanted to. For months I did research. I tried finding different ways to do it, but I failed a lot of times, Prabhu explained.

The difficulties he encountered while working with audio data resulted in poor models that produced faulty results.

When I submitted this to the local science fair it didnt go through which was a disappointment. I thought this was the most difficult project I have ever done to this day, Prabhu said disheartened.

He reflected back on his Sophomore year, where he designed a Covid-19 screener using machine learning and hardware. The project was inspired by the pandemic and received gold at the Delaware Valley Science Fair. However, his recent paper was rejected by the local science fair.

Being rejected by the local science fair was a big bruisebut I think it was a blessing in disguise because I got to make this whole paper. This paper was born from the science fair project failing. I made my models better, I trained them with more data, [and] I ended up submitting them to the conference, Prabhu added.

In the future, Prabhu plans to attend a four year university and continue doing research while immersing himself in robotics, engineering, and programming.

Continued here:
Yash Prabhu celebrating victory after publication of research paper - Knight Crier

Cybernetics will drive the future of robotics by empowering them with human intelligence

Robotics Industry is constantly rising in this automation world. According to reports, the Indian industrial robotics market is predicted to grow at a CAGR of 13.3% between 2019-2024. With its rising industry applications and productivity benefits, the study of cybernetics is likely to be a vital element in the advancement of robotics.

The craving for gadgets or machines that can keep up with the challenges of the present world and largely function in simpler and smarter ways is evident. Automation and autonomy have offered this by producing and delivering products and services that contain the least amount of human intervention, making certain jobs more convenient than ever before even when information is incomplete and uncertain. The appearance of new service robots and their wide evolution into new applications has further facilitated the world of automation. Due to the dynamic nature of robotics, numerous application sectors are now using robotics to perform predetermined tasks and enhance human efforts in both physical and analytic ways. Robotics has enhanced task efficiency, dependability, and quality, all of which were earlier, products of a laborious procedure. Being a critical component of automation, robotics is currently used in an ever-growing variety of fields, like manufacturing, transportation, healthcare & medical care, utilities, defence, facilities, operations, and more recently, information technology. Here Cybernetics enters as a primary element as robots need to be advanced.

Cybernetics is a study of science that focuses on developing technologies that act or think like humans by researching how electrical devices or machines and the human brain function to enhance the value of the job to be performed. Cybernetics is the best workaround physical embodiment of Artificial Intelligence (AI), Machine Learning (ML), and predictive analysis and control, investigating underlying systems/structures, possibilities, and limitations of complex mechanisms, including robotics, and generating an autonomous environment that uses minimal to no human interaction. AI and cybernetics are two dissimilar perspectives on intelligent systems or systems that may act to achieve an aim. Making computers imitate intelligent behavior using pre-stored world representations is the primary goal of AI. In general, cybernetics tells us how systems control themselves and can take actions autonomously based on environmental signals even when the information is minimal and subject to significant uncertainty or noise. These systems go beyond simple computation; they can also control biological (body temperature regulation), mechanical (engine speed regulation), social (managing a huge workforce), and economic (controlling a national economy) systems.

Every cybernetic systems aim is to be set up so that its operations are linked in a variety of input-output system configurations which are normally driven with reference control signs. This is achieved by processing feedback-based automatic closed-loop control systems that can decide which behaviors should be changed, which actions should be tracked, how to compare the actions to the reference, and how to adapt the application behaviors in the most effective way. In natural cybernetic systems, this regulatory mechanism generates or organizes by itself with the help of self-learning. On the other hand, artificial cybernetic systems behave or are influenced by human-implemented automatic control systems. Essential elements of cybernetic systems are sensors, the controller, actuators and the system to be controlled.

Cybernetics in robotics systems main objective is to use AI and machine learning in the sense-plan-act paradigm normally used to develop robots so they can operate productively in real-world scenarios. Developing a robot to understand and differentiate complex situations every day is highly demanding and getting the situation awareness correctly identified is crucial to ensuring the desired reference control signal can be identified for implementation. This can make sure an industrial robot recognizes and picks up the correct item for the next stage of the manufacturing process from a selection of parts to ensure the requests of the human to be served a variety of beverages will get the correct drink. Sensors and sensor systems that are perfectly calibrated are necessary for ensuring the situation awareness is achieved perfectly and in real-time using AI-based models which can be learned and applied in various situations such as driverless cars, medical robots, automated manufacturing, and home care robots.

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Cybernetics is the Only Way Robots Can Achieve Human Intelligence - Analytics Insight

The Wikipedia project is a way to have students reflect back on everything theyve done in their coursework and then go to the deepest levels of Blooms Taxonomy of Learning to edit the articles, Lonnie Welch, Charles R. Jr. and Marilyn Stuckey professor in the School of Electrical Engineering and Computer Science, said.

In fall 2021 and spring 2022, computer science students in Data Mining and Data Science worked toward the same goal to complete their course to improve a Wikipedia page with more robust descriptions, key visuals and reliable sources. This common goal was part of a final project, allowing students the opportunity to revise and edit their page drafts before their final submission.

A Wikipedia-based writing activity offers a more authentic learning experience than a traditional term paper and provides students with the opportunity to practice disseminating domain-specific knowledge to a broad audience while navigating the complexity and ambiguity of working through a real-life problem, Welch wrote in the projects description.

Hunter Burden, BSCS 21, participated in this project in both the Data Mining and Data Science course. In his final semester of his undergraduate degree in computer science, Burden worked collaboratively with his teammates to improve an article on Radar Charts, a type of graph that measures multivariate data, like performance metrics, where at least three variables are represented like spokes or points on a wheel. The culmination of his teams hard work resulted in a first-place win in the International Society for Computational Biologys Wikipedia Competition. The competition supports the ISCB's mission by promoting the improvement of topics relevant to computational biology on Wikipedia, which is widely accessed around the world as a free-to-use educational resource. Since Wikipedia is often the first port of call for someone learning about a new topic, ensuring that computational biology is well-represented on Wikipedia helps maximize the visibility and impact of the field on society, Alastair Kilpatrick, competition organizer and bioinformatician at the University of Edinburgh, said.

While winning the competition was a benefit of this project, perhaps more importantly, the project helped assess learning outcomes, indicating that students not only learned key topics in computer science, but were also able to communicate about those topics in an informative and reliable way.

Before we won, I felt like we did great work. Dr. Welch asked us honest questions throughout the semester about our process and the contents of the page. When we presented everything in the end, we felt really good about the result, Burden said.

This assessment strategy was not accidental. Through collaborative work with instructional designer, Audra Anjum, Welch decided to plan his class around learning outcomes and objectives. Then he devised assessment strategies informed by his intended outcomes. He used the example of tying one's shoes to communicate his vision for his course structure.

If someone is learning how to tie their shoes, you can either ask them a series of questions about tying shoes or you can simply ask them to tie their shoes to show you that they have learned that skill, Welch explained.

By authoring Wikipedia pages, students were demonstrating that they learned valuable topics in computer science by writing about those topics for the layperson, creating visuals, incorporating data and identifying reliable sources that bolster their edits to the page.

We specifically developed the Wikipedia project to not only create a unique and interesting experience [for] students, but also to demonstrate that they met the learning outcomes, Anjum said.

Additionally, this project allowed students to practice critical written communication, a skill that is often underemphasized in both engineering and computer science coursework.

Theres an art to writing things that are concise. You dont want to overload people with jargon. This is an important skill in computer science when writing comments or updates on your work, so another party knows whats going on and what their task is, Burden said.

You need to be able to communicate your ideas to get people excited about what you are doing. Much of the written communication we do is to sell things, ideas and ourselves. In computer science, you need to be effective at communicating requirements, designs and test plans, Welch said.

Using their written communication skills, students collaboratively enhanced articles to improve the general landscape of Wikipedia a resource that is often stigmatized due to the user-editable nature of each page. In this circumstance, however, students demonstrated that thoughtful, informed editing can improve the landscape of Wikipedia.

Wikipedia has a reputation for being unreliable since so many individuals can contribute to the content. Wikipedia is a widely accessible open education resource for students and faculty, however. Experts have a responsibility to their professions to make sure that their fields are represented accurately and broadly on Wikipedia to discourage the spread of misinformation, Anjum said.

Editing a Wikipedia page well can be a significant undertaking, but the final product results in a more informative and accessible resource for people around the globe.

It's important for university students (and academics in general) to edit Wikipedia pages, as they possess important domain knowledge that can vastly improve Wikipedia's coverage of their subject of interest. They also should have some vested interest in ensuring that Wikipedia articles describing their subject of interest are accurate and up to date, Kilpatrick said.

Explore the winning teams Wikipedia articles in Radar Charts (first place), Biological Networks (second place) and Cosegregration (third place).

To learn more about how to incorporate Wikipedia editing into curriculum design, read this article by Anjum, Kilpatrick and Welch.

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OHIO students place first, second and third in international Wikipedia editing competition - Ohio University

As the Supreme Court prepares to begin its next term, experts in privacy and national security law are watching closely for hints about whether justices will take up a potentially precedent-setting challenge to the governments use of a state secrets law to avoid scrutiny of its surveillance programs.

The Wikimedia Foundation, the organization that runs Wikipedia, last month asked the nations highest court to hear arguments on its lawsuit over the National Security Agencys warrantless surveillance of Americans international phone and email communications. The organization, represented by the American Civil Liberties Union, has been fighting the NSA in court over such upstream surveillance for the past seven years.

At the heart of the case is a question about how broadly the government can invoke its state secrets privilege to block civil cases from moving forward if they involve disclosing information that is reasonably likely to cause significant harm to the national defense or the diplomatic relations of the United States. The NSAs critics argue that the agencys definition of such information has expanded over time, without apparent justification.

On one side, there is one of the largest archives of human information, maintained and edited by millions of people across the world. On the other is the U.S. government invoking a law that is specifically designed to curtail the spread of information or at least information it deems unfit to be shared.

Corbin Barthold, internet policy counsel at the nonprofit group TechFreedom, said that the focus of the case on the scope and expansion of the state secrets privilege makes it catnip for the Supreme Court, with potential interest from both members of the courts conservative majority and its liberal minority. For example, Justice Neil Gorsuch, appointed by then-President Donald Trump, has pushed for stronger protections under the Fourth Amendment, which protects people from unreasonable searches and seizures. Moreover, the 4th Circuit Court of Appeals the last body to weigh in on the case split on the matter.

Barthold also noted that it has been years since the high court has heard a case examining how broadly the government can apply the national security law.

But as with most things when it comes to the Supreme Court, nothing is a given.

Weve always seen mass surveillance as a really significant threat to the privacy and free expression rights not just of Wikimedia users, but internet users in general, said James Buatti, senior manager for legal, governance and risk at Wikimedia. Weve always believed that nobody should have to worry about their government looking over their shoulder when theyre deciding whether to read an article or contribute to a controversial topic. So filing this case back then was kind of an easy decision.

The Department of Justice declined to comment, citing the ongoing litigation.

Details of the NSAs behind-the-scenes practices and its exhaustive surveillance of people in the U.S. and elsewhere burst into public view in 2013, when former intelligence contractor Edward Snowden disclosed them to multiple news organizations.

The Wikimedia suit centers on one of these methods, upstream surveillance. It entails collecting all communications that people in the U.S. have with parties outside of the country. This type of dragnet, authorized under Section 702 of 2008 amendments to the Foreign Intelligence Surveillance Act of 1978, pulls in things like emails, search engine entries and what people browse online. The government is able to collect this information by tapping into the internet backbone, which includes the high-capacity cables and routers our data travels across to make the internet function around the world. The NSA searches this information using thousands of keywords, the results of which the government says it further analyzes to pick up on potential threats to national security. But thats not always where use of the information stops.

Its easy to lose sight of the way that data that was originally collected in the name of national security can potentially flow to police or any number of investigations, said Albert Fox Cahn, founder and executive director of the Surveillance Technology Oversight Project (STOP). All thats stopping it is the belief in the goodwill of agencies that have systematically violated our trust at every turn.

Wikimedia contends that given this surveillance, it cannot ensure the confidentiality of the tens of millions of people who read, edit and communicate about Wikipedia, one of the largest repositories of human information to ever exist.

Aeryn Palmer, legal director of compliance at the Wikimedia Foundation, said that the ability to read and to contribute to Wikipedia under a pseudonym has been important since the projects earliest days.

When we think about what we might be collecting from anyone who visits the site, when we think about how we do research with our readers or with our contributors to better understand what sorts of features they might like to see and how they want the projects to evolve, were continually thinking about how we can best protect their privacy, said Palmer.

Wikimedias suit hinges on state secrets privilege, which the government has repeatedly used to fend off legal challenges to upstream surveillance. It has argued, in this case and others, that upstream surveillance is so secret that legal challenges to it cannot proceed.

The NSA has vacuumed up Americans and international communications using upstream surveillance, and to date not a single challenge to that surveillance has been allowed to go forward, said Patrick Toomey, deputy director of the American Civil Liberties Unions national security project and one of the attorneys representing Wikimedia. The Supreme Court must make clear that NSA surveillance is not beyond the reach of our public courts.

He argued that the government has continued to expand its use of the state secrets law as a cudgel to bat away civil litigation.

Toomey pointed to a lawsuit filed in 2007 by Khaled El Masri, a German citizen with Lebanese roots who was abducted by Macedonian police before they handed him to the CIA, claiming that the CIA kidnapped and tortured him in a case of mistaken identity. An appellate court recognized there was public evidence of El Masris mistreatment but decided that state secrets were too central to the case to allow it to go forward.

Similarly, in 2010, five people filed a lawsuit claiming that one of Boeings subsidiary companies had flown the planes carrying them to the black sites where they were tortured by the CIA. An appeals court dismissed that case as well, along similar lines of reasoning as the El Masri verdict. Both times, the government invoked state secrets privilege.

In Wikimedias current lawsuit, the government has taken the maximalist approach and asked the courts to dismiss the case on state secrets grounds, even though the government itself has released dozens of official reports, court opinions and other documents about upstream surveillance, said Toomey.

One reason that the NSA has successfully fended off lawsuits using state secrets privilege is that in many cases regarding surveillance, plaintiffs were not able to show harm.

The Wikimedia case is different. The foundation has relied on an analysis by Jon Penney, a legal scholar and social scientist at York University in Toronto, that quantifies the impact of government surveillance on Wikipedia articles.

The 2016 analysis measured the chilling effect of surveillance, or how people act differently sometimes including censoring themselves if they have reason to believe they are being watched.

Penney found that following reports of Snowdens exposure, traffic to Wikipedia articles on topics that raise privacy concerns for Wikipedia users decreased in a statistically significant manner.

The researcher arrived at that conclusion by choosing Wikipedia pages based off keywords the Department of Homeland Security uses to monitor social media, such as infrastructure security, terrorism and cybersecurity. Penney honed in on the category terrorism, which included terms like Iran, pirates and suspicious substance.

But he noted that more recent discussions about chilling effects have gone beyond national security issues. In the wake of the Supreme Court decision striking down Roe v. Wade, for instance, civil liberties and pro-choice groups have revived conversations around the chilling effect of government surveillance specifically around cellphone, phone app and web search data that could inadvertently reveal when a person is pregnant or seeking an abortion.

You have a combination of government surveillance combined with overreaching laws combined with governments essentially whipping up harassment campaigns against people who are out there just simply attempting to vindicate their rights, said Penney. So, I think [privacy] is a concept that is in increasingly important.

An earlier version of this story misidentified the genesis of the government's state secret claims. This version has been updated.

Thanks to Lillian Barkley for copy editing this article.

Read more:
NSA and ACLU may face off in the Supreme Court over Wikipedia - Grid