SAS announces winners of 2024 SAS Hackathon

Innovative solutions to business and social challenges driven by access to SAS Viya and its new AI tools

CARY, N.C., Nov. 20, 2024 /PRNewswire/ -- SAS, a leader in data and AI, has announced the winners of the 2024 SAS Hackathon across 25 regional, industry, technology, specialty and student categories. These winning teams represent businesses, government agencies, nonprofits, universities and SAS Partners.

This year's SAS Hackathon boasted 1,731 registrants from more than 70 countries. This led to an all-time high of 145 approved teams that participated in the month-long hack, supported by 110 SAS mentors. SAS produces the annual SAS Hackathon, which was sponsored this year by long-time SAS Partners Microsoft and Intel.

During the SAS Hackathon, teams of data scientists, business analysts, technology enthusiasts and students come together – often virtually across continents – to network, learn from each other and from a SAS mentor, and experiment with new technologies that spark innovation and improve lives.

Cutting-edge tech
The 2024 SAS Hackathon offered hands-on experience with a host of new technologies, including the very latest from SAS^® Viya^®, SAS' cloud-native, massively parallel data and AI platform. Four new Viya offerings were available to SAS Hackathon teams:

• SAS Viya Workbench – a self-service, on-demand compute environment for conducting data preparation and exploratory data analysis and developing AI models.
• Model Cards – best described as "nutrition labels" for AI models, they highlight indicators like accuracy, fairness and model drift. With emerging AI rules, it is crucial to understand and share with regulators how models are performing.
• SAS Data Maker – a synthetic data generator, it addresses data privacy and data scarcity challenges by generating high-quality synthetic data without compromising sensitive information.
• SAS Viya Copilot – a personal AI assistant, it enhances productivity for developers, data scientists and business users by accelerating code generation, data cleaning and exploration, marketing planning and more.

"Hackathons are a fantastic way to advance novel ideas and explore new methods. And with hands-on access to SAS Viya and its powerful new AI tools, the winning teams in this year's SAS Hackathon have raised the bar of innovation to new heights," said Jennifer Chase, Chief Marketing Officer at SAS.

"Their projects will have a substantial impact on many of today's business and societal challenges. Congratulations to the winners and all SAS Hackathon participants for inspiring us."

Preventing heat stroke and saving lives
An example of a SAS Hackathon team effectively using these new technologies is team StaSASticians. Team members are experts in data analytics, mathematical modeling and health care. Using SAS Viya Workbench and SAS Data Maker, along with SAS Viya and Python tools, they developed an AI-enabled Heat Stroke Prevention System for construction workers.

The system analyzes real-time weather data and sensor information from IoT-equipped smart helmets from IoT company (and team member) BeeInventor that monitor factors such as workers' heart rate and core body temperature. The system then provides real-time warnings of potential heat stroke to protect high-risk workers. This can save lives and enhance safety, productivity and regulatory compliance while also reducing health care costs.

In a world warming due to climate change, this Heat Stroke Prevention System is a very timely and targeted innovation. For the 2024 SAS Hackathon, team StaSASticians won in three categories: Americas (region), Insurance (industry) and IoT (technology). And its project is typical of the many inspiring stories within this year's SAS Hackathon.

Overall winner?
While SAS announced category winners today, the overall SAS Hackathon winner will be named at SAS Innovate, the SAS data and AI technology conference, May 6-9, 2025, in Orlando, Florida.

2024 SAS Hackathon winners
More than 100 expert judges chose regional winners and global industry, technology, specialty and student winners. To learn more about each winning team and view videos of their projects, visit the SAS Hacker's Hub community and search by team name.

Regional winners

• Americas – StaSASticians [U.S.] Using SAS Viya, SAS Viya Workbench, SAS Data Maker and Python tools, this team developed an AI-enabled Heat Stroke Prevention System for construction workers. See above for more details.
• Asia-Pacific – Nupeak Neurons [India]. This team from IT services provider and SAS Partner Nupeak Group applied computer vision and machine learning to create a new approach to quality inspection in the pharmaceutical industry. Using SAS Visual Data Mining and Machine Learning and Python tools, the team created an automated system for inspecting injectable pharmaceuticals that quickly detects defects, improves manufacturing quality and ensures product safety.
• EMEA – Butterflies [U.K.] The flood of data, misinformation and disinformation are becoming major problems, often negatively influencing decisions and causing harm. SAS Partner Butterfly Data has developed a tool to help analysts assess data sources for their reliability and credibility. The tool uses advanced natural language processing (NLP) and classification models to check the trustworthiness of news and open source data. Built with SAS Viya, Viya Workbench, and Viya Copilot, as well as open-source tools like Git and Python, the tool helps verify data sources, spot unreliable information and ensure the use of ethical information to make decisions.

Global industry winners

• Banking – Raffles Vietnam. Many banks face policy complexity that can lead to misunderstanding and misalignment. SAS Partner Raffles Data & Analytics has created RAGI, a generative AI solution built on SAS Viya. With RAGI, banks can automate the extraction of business rules from policy documents and resolve conflicts or gaps in credit policies, saving time and money. By seamlessly integrating with SAS Intelligent Decisioning, RAGI drastically reduces the time-to-market for new policies and products.
• Energy – IAEA: Climate Change and Challenges to Nuclear Plant Safety [U.S., Italy]. As countries confront the climate crisis and energy-security concerns, nuclear energy is increasingly recognized for its potential. But it must demonstrate a proven level of safety. A team from the International Atomic Energy Agency (IAEA), the Pacific Disaster Center, and Oakland University assessed natural hazard risks in nuclear facility site selection. Using SAS Viya and its AI and machine learning capabilities, the team identified various natural hazards (floods, wildfires, severe weather and more), uncovered correlations between hazards, analyzed hazard characteristics and affected regions, and estimated the probability of occurrence and risk to new and existing nuclear facilities.
• Health Care – NEAR Exergame [Malaysia]. A team of researchers from Universiti Sains Malaysia has created a system that delivers engaging and safe rehabilitation for stroke patients and elderly individuals. Powered by AI and SAS Viya, the system offers real-time recovery feedback while tracking progress, predicting outcomes and tailoring a therapy plan for each patient.
• Insurance – StaSASticians [U.S.] See above for more details.
• Life Sciences – RatioTeam [Italy]. This team from SAS Partner Rationence developed Abstract Finder, a solution that exploits generative AI to enhance biomedical literature retrieval. Powered by SAS Viya, the solution helps researchers, medical and health professionals and students quickly find the abstracts they need within the PubMed database to advance scientific discovery.
• Public Sector – Team Only Planet 2120 [Netherlands]. This diverse and dynamic team of experts included specialists in civil engineering (Heijmans and Dura Vermeer), water management (Waterschap Rivierenland and Groene Metropoolregio Arnhem-Nijmegen), data science/GIS (SAS Partner Notilyze) and climate research (Wageningen University). By using SAS Viya, open source tools and GIS mapping and simulation, the team integrated diverse data sources to create comprehensive visualizations of climate scenarios in the Dutch river delta. These helped the team optimize water-management strategies.
• Retail, Consumer Goods & Manufacturing – Supply Chain Resource Cooperative NCSU [U.S.] A team from North Carolina State University has developed a machine learning-based system that grades apparel factory compliance with established labor standards. NCSU used SAS Viya to develop its framework, which creates a more transparent and ethical way to evaluate apparel supply chains.
• Telecom – Advanced Analytics TEF Vivo. [Brazil]. A team from telecom provider Vivo created a solution that automates revenue and profit forecasting in the mobile segment. Using machine learning models and data analysis within SAS Viya led to significant increases in forecasting accuracy, a simplified process, and easy visualization and adjustment. The result? Better strategic planning and resource allocation, reduced manual effort and improved efficiency.

Global technology winners

• Computer Vision – avalanche [Turkey]. A student team from TOBB University of Economics and Technology designed a system to monitor social media platforms and economic and public camera data. The goal? Detect harmful content or dangerous activity and provide timely alerts to relevant authorities to prevent panic and protect public safety.
• Decisioning – Benjamin & Joseph (Benjo) [Singapore]. SAS IoT Partner Ecosystem member Benjamin & Joseph has developed a solution to automate line-by-line auditing of medical bills. Its Sherlock solution, powered by SAS AI and IoT analytics, helps reduce errors in medical billing. These errors lead to billions of dollars in preventable losses for health care providers and payers worldwide.
• Forecasting – Datacurate [India]. SAS Partner Datacurate Technologies created a procurement-planning solution for the food industry using SAS Viya. For a restaurant chain, for example, procurement planning involves determining which ingredients to buy, the optimal time for purchasing, and the precise quantities needed to meet anticipated demand. Effective procurement planning aims to minimize costs and reduce waste while ensuring timely availability of ingredients.
• Internet of Things (IoT) – StaSASticians [U.S.] See description above.
• Models – Butterflies [U.K.] See description above.
• Natural Language Processing (NLP) – Council Insights Heidelberg [Germany]. This team wanted to create a way for Heidelberg's citizens to find out quickly about the work and resolutions of the city's Municipal Council. Using SAS Viya, they built a system that automatically retrieves documents from the Council's website, preps the data, and analyzes it with NLP, large language models (LLMs) and Viya tools so it can be easily accessed and searched. By better presenting the work of city committees, the team helps strengthen citizens' trust in their local government. And this project could be a model for other cities.
• Visualization – Council Insights Heidelberg [Germany]. See description above.

Global special award winners

• Channel Ready – Butterflies [U.K.] See description above.
• Sustainability – Cleaner Commutes [Netherlands]. Employee commuting is a significant part of many companies' carbon footprint. Using SAS advanced analytics and machine learning, this team provides data-driven insights to companies to help them reduce their commuting emissions and comply with environmental regulations. Large volumes of synthetic data (from SAS Data Maker) can also help simulate different commuting scenarios so companies can assess employee impact and develop personalized solutions.
• Data for Good – AbuSearch [U.K.] This team from SAS Partner Katalyze Data and the Child Rescue Coalition used text analytics, NLP and other tools to fight child abuse. They analyzed chat and forums data from Project Nemesis, child-protection software for law enforcement. The goal was to identify users of the chat and forums who share and even produce harmful content on children, as well as those who find, groom and contact potential victims.
• Emerging Talent – NEAR Exergame [Malaysia]. See description above.
• Trustworthy AI – Butterflies [U.K.] See description above.

Global student winners

• Data for Good – ORSOL [U.S.] This team from Purdue University examined how economically disadvantaged populations are disproportionally affected by climate change. It built a system to identify the 50 counties in the U.S. that are most at risk from the combination of climate change and economic vulnerability. And created data-driven insights to help policymakers better allocate resources.
• Ethical Data Analysis – Data Ninjas [U.K.] To develop a data-driven and ethical admissions process for graduate schools, this team from the University of London and the University of Wolverhampton used SAS Viya for Learners to mitigate bias and promote fairness.

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