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EY announces winners of EY NextWave Global Data Science Challenge launched to connect STEM students worldwide

Vlad Poptamas

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EY today announces the launch of the initiative to connect Science, Technology, Engineering and Mathematics (STEM) students worldwide, with the winners of the first EY NextWave Global Data Science Challenge.

The Challenge provides STEM students with the opportunity to analyze real-world problems through data and develop initiatives that will help build a better working world. Top participants received an EY Badge, recognizing their knowledge and skills in data science. The EY Badges program supports EY people in shaping their own careers by earning credentials in skills that differentiate them in the market, such as data analytics or artificial intelligence (AI).

For this year’s Challenge, the students used real-world data from Skyhook, a pioneer in location technology, to help tackle the task of smart mobility in cities as the urban population rises across the globe. Future challenges will continue to mirror the EY focus on building a better working world for all people, clients and communities.

The EY NextWave Global Data Science Challenge attracted more than 4,500 students from nearly 500 universities. A judging panel comprised of EY leadership and data science professionals assessed in-person presentations of more than 50 of the top performing teams in the competition. The three global winners were chosen among those who combined the best results with in-depth insights and contributions to building a better working world. Of the 12,000 entries received, the 2019 EY NextWave Data Science Challenge winners are:

First placeSergio Banchero. Sergio is from Argentina, pursuing his Master’s degree in Data Science at the University of Western Australia in Perth. Sergio analyzed the data created by devices as they moved from the city center to the city border. He created models that could be used for real-time decision making, such as identifying issues in transportation networks; identifying blocked roads and the impact on city traffic; and identifying common travel patterns to extend and enhance the public transportation network.

Second placeKatherine Edgley and Philipp Barthelme. Katherine is from the US and is pursuing her Master’s degree in Computational Applied Mathematics at the University of Edinburgh; Philipp is from Germany and is pursuing his Master’s degree in Statistics with Data Science at the University of Edinburgh. Katherine and Philipp used recurrent neural networks – which use sequential formation to make predictions – to create models that could provide companies and people with optimal traffic routes and parking, for example.

Third place: Chia Yew Ken. Chia is from Singapore and is currently pursuing an Engineering Bachelor’s degree in Information Systems Technology and Design with a specialization in Artificial Intelligence at the Singapore University of Technology and Design. Chia used long-short-term-memory (LSTM), a special form of recurrent neural networks that can retain memory over long periods of time and are used to classify, process and make predictions. Chia developed models that could be used to identify over-crowded roads and intersections, reschedule traffic or schedule road work.

Future for the EY NextWave Data Science Challenge

Moving forward, EY teams are implementing an enhanced EY NextWave Data Science Challenge that deepens their relationship with students and will enable students to participate in potentially world-transforming initiatives and earn EY Badges.

The new program will publish challenges on an ongoing basis and students will achieve EY Badges by solving the issues and participating in innovative crowdsourcing initiatives. For example, an online marketplace and a discussion board will help students connect and create inclusive, global teams to tackle the challenges. University faculty can also create challenges to motivate students with real-world issues, either as an assignment or to propose competitions to the global community of students.

Beatriz Sanz Saiz, EY Global Advisory Data Analytics Leader, says:

“Our goal is to mobilize millions of students worldwide through this network, so that they contribute, together with EY teams, to build a better working world, with a sense of purpose, belonging and reciprocity as they develop their skills in data science. The EY NextWave Data Science Challenge connects students with academic leaders, industry professionals and real-world challenges to foster future career development. We are proud of today’s EY NextWave Data Science Challenge winners, who have demonstrated innovative approaches to creating smarter cities and improving mobility. We hope that their projects, and the new Challenge we’re announcing today, will inspire even more students to embark on STEM careers.”

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Artificial Intelligence

Mercari Opens Cambridge Engineering Offices

Vlad Poptamas

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Mercari, The Selling App, today announced the opening of engineering offices in Cambridge, MA, advised by two renowned professors at the adjacent Massachusetts Institute of Technology (MIT).

Mercari is the number-one marketplace in Japan. Since entering the U.S. in 2014, more than 45 million Americans have downloaded the app.

At the moment, Mercari’s team in Cambridge is focused on better understanding sellers and buyers, and predicting their intentions ahead of their actions. This helps Mercari deliver a more personalized experience using its recommendation engine. The team is applying machine learning on massive amounts of data to better personalize the user experience based on their preferences, history and interactions.

More broadly, this team is pursuing applied research projects in machine learning, computer vision and other emerging technologies that can help Mercari to make selling even easier than buying.

“Opening the Mercari engineering offices in Cambridge is an important addition to our global technology centers in Palo Alto and Tokyo,” said Dr. Mok Oh, chief technology officer for Mercari U.S. “The expectations of Mercari sellers and buyers are always evolving, so it’s vital that we harness emerging technologies to continuously improve our app and services.”

Advising the team are Dr. Frédo Durand and Dr. Wojciech Matusik of MIT.

Dr. Frédo Durand is a renowned researcher and professor in computer vision and computational photography. He is a professor of Electrical Engineering and Computer Science at MIT, and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

Dr. Wojciech Matusik is widely-recognized professor and entrepreneur in machine learning, 3D vision, and 3D fabrications. He is a professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, where co-directs the Computer Graphics Group and teaches machine learning courses

Mercari is looking for talented people to join its technology teams in Palo Alto and Cambridge. A list of all current U.S. openings is here.

 

SOURCE Mercari

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Artificial Intelligence

Chinsay’s Intelligent Contract Platform Enables Rio Tinto & Cargill to Complete the First Fully Digitalised Iron Ore Trade

Vlad Poptamas

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Photo source: salestechstar.com
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Chinsay, the leading provider of contract digitalisation solutions in the commodity and freight markets, is announcing today the completion of the first fully digitalised iron ore trade, through a trial achieved in partnership with Rio Tinto and Cargill‘s Metals business on Chinsay’s Intelligent Contract Platform (ICP).

In using ICP, Rio Tinto and Cargill collaborated on a single platform to dramatically reduce the time it takes to create, issue and approve commodity contracts from several days to under two hours. The digitalisation of this fundamental trade process creates the opportunity to automate and deliver post-trade efficiencies by linking front-, middle- and back-office functions.

Colin Hayward, Chinsay CEO, said: “This is a technological milestone for the industry, and we are delighted Rio Tinto and Cargill Metals chose to partner with us and use our ICP as the core technology to create this advance. We are constantly collaborating with clients, market participants, tech vendors and industry consortia to extend digitalisation further along the commodity trade lifecycle.”

“The Intelligent Contract Platform is a great tool that has the potential to benefit the entire ferrous industry,” said Lee Kirk, Managing Director for Cargill’s Metals business. “This is a great example of how we can leverage advancements in technology to benefit from increased speed, transparency and efficiencies that enable us to serve our customers and suppliers better.”

ICP is state-of-the-art technology which allows companies to digitalise pre-trade processes early in the deal lifecycle, creating an agreed contract dataset that can be seamlessly integrated with other operational systems, functions and processes, enabling transparency and traceability across the supply chain.  ICP prepares clients for the use of technologies such as blockchain, ML, AI and electronic trade documentation solutions.

 

SOURCE Chinsay

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Artificial Intelligence

Aiozium Launched SaaS-based Marketing Intelligence Tool Powered by AI

Vlad Poptamas

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Aiozium- AI for Marketing
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Aiozium, a new launch of Crowdnik Networks Private Limited, is a SaaS-based platform for marketers powered by machine learning techniques in a different way. The tool has intelligence for self-correction and self-learning for better campaign optimization and high ROI.

Aiozium is a multi-dimensional platform that not only reads the data, makes sense of all the data and generate actionable insights on them, but also gives the real-time information about customer behavior. It builds the trend of the customers based on a various emotional and behavioral algorithm which leads to prediction and results in an increase of leads by selecting the best marketing mix and marketing strategies for optimum use of resources which results in greater ROI.

Reason Why Every Marketer Needs Aiozium

Aiozium is marketing ally, it is a tool for all the marketers which makes life simpler and completes the customer journey with ease.

– Emotional Algo: It is said that the only difference between Robot and Human is the emotions or the feel factor. Emotional algo consists of human psychological ethos. It analyses the behavior basis on different kinds of emotions exhibited by humans. It helps in analyzing the marketing communications, activities and asses their value. It also measures and analyses the emotions of a person towards buying the product.

– Contextual Algo: It analyses the content across various channels viz. website, email and all communication platforms based on multiple parameters such as aggression, transaction, emotion etc. It also analyses whether the user is persuaded with the interaction or not, basis on which it predicts the usefulness of the content.

– Behavior Algo: Based on historical and real-time customer behavior across all channels with prospective data listening mechanism, this model can learn, react and predict the most accurate customer flow for maximum conversion. It predicts the probability of the rate of conversion through Machine Learning, Deep learning, Natural Language processing and Augmented Visualization.

How Is It Going To Benefit The End-users:

On-boarding with Aiozium will reduce the marketing expenses by cutting down the misspend funds and optimizing the campaign to increase the ROI. It remembers and recollects the historical hand burns and successful campaigns and accordingly suggests marketers the most accurate pathway to follow. It also learns the customer behavior towards marketer’s product line. The best part of Aiozium is that it works across channels and sync with all the digital assets in a single click.

Automate, Sit Back and Relax

Aiozium is inviting the industry experts to have a test drive on their AI Marketing Ally. To book a slot, schedule a demo at https://www.aiozium.com/demo.html

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