Graphic courtesy of the Center for Statistics and Machine Learning
Ten interdisciplinary research projects have won funding fromPrinceton Universitys Schmidt DataX Fund, with the goal of spreading and deepening the use of artificial intelligence and machine learning across campus to accelerate discovery.
The 10 faculty projects, supported through a major gift from Schmidt Futures, involve 19 researchers and several departments and programs, from computer science to politics.
The projects explore a variety of subjects, including an analysis of how money and politics interact, discovering and developing new materials exhibiting quantum properties, and advancing natural language processing.
We are excited by the wide range of projects that are being funded, which shows the importance and impact of data science across disciplines, saidPeter Ramadge, Princeton's Gordon Y.S. Wu Professor of Engineering and the director of the Center for Statistics and Machine Learning (CSML).These projects are using artificial intelligence and machine learning in multifaceted ways: to unearth hidden connections or patterns, model complex systems that are difficult to predict, and develop new modes of analysis and processing.
CSML is overseeing a range of efforts made possible by the Schmidt DataX Fund to extend the reach of data science across campus. These efforts include the hiring of data scientists and overseeing the awarding of DataX grants. This is the second round of DataX seed funding, with thefirst in 2019.
Discovering developmental algorithmsBernard Chazelle, the Eugene Higgins Professor of Computer Science;Eszter Posfai, the James A. Elkins, Jr. '41 Preceptor in Molecular Biology and an assistant professor of molecular biology;Stanislav Y.Shvartsman,professor of molecular biology and the Lewis Sigler Institute for Integrative Genomics, and also a 1999 Ph.D. alumnus
Natural algorithms is a term used to described dynamic, biological processes built over time via evolution. This project seeks to explore and understand through data analysis one type of natural algorithm, the process of transforming a fertilized egg into a multicellular organism.
MagNet: Transforming power magnetics design with machine learningtools and SPICE simulationsMinjie Chen, assistant professor of electrical and computer engineering and the Andlinger Center for Energy and the Environment;Niraj Jha, professor of electrical and computer engineering; Yuxin Chen,assistant professor of electrical and computer engineering
Magnetic components are typically the largest and least efficient components in power electronics. To address these issues, this project proposes the development of an open-source, machine learning-based magnetics design platform to transform the modeling and design of power magnetics.
Multi-modal knowledge base construction for commonsense reasoningJia Deng andDanqi Chen, assistant professors of computer science
To advance natural language processing, researchers have been developing large-scale, text-based commonsense knowledge bases, which help programs understand facts about the world. But these data sets are laborious to build and have issues with spatial relationships between objects. This project seeks to address these two limitations by using information from videos along with text in order to automatically build commonsense knowledge bases.
Generalized clustering algorithms to map the types of COVID-19 responseJason Fleischer, professor of electrical and computer engineering
Clustering algorithms are made to group objects but fall short when the objects have multiple labels, the groups require detailed statistics, or the data sets grow or change. This project addresses these shortcomings by developing networks that make clustering algorithms more agile and sophisticated. Improved performance on medical data, especially patient response to COVID-19, will be demonstrated.
New framework for data in semiconductor device modeling, characterization and optimization suitable for machine learning toolsClaire Gmachl, the Eugene Higgins Professor of Electrical Engineering
This project is focused on developing a new, machine learning-driven framework to model, characterize and optimize semiconductor devices.
Individual political contributionsMatias Iaryczower, professor of politics
To answer questions on the interplay of money and politics, this project proposes to use micro-level data on the individual characteristics of potential political contributors, characteristics and choices of political candidates, and political contributions made.
Building a browser-based data science platformJonathan Mayer,assistant professor of computer science and public affairs, Princeton School of Public and International Affairs
Many research problems at the intersection of technology and public policy involve personalized content, social media activity and other individualized online experiences. This project, which is a collaboration with Mozilla, is building a browser-based data science platform that will enable researchers to study how users interact with online services. The initial study on the platform will analyze how users are exposed to, consume, share, and act on political and COVID-19 information and misinformation.
Adaptive depth neural networks and physics hidden layers: Applications to multiphase flowsMichael Mueller,associate professor of mechanical and aerospace engineering; Sankaran Sundaresan, the Norman John Sollenberger Professor in Engineering and a professor of chemical and biological engineering
This project proposes to develop data-based models for complex multi-physics fluids flows using neural networks in which physics constraints are explicitly enforced.
Seeking to greatly accelerate the achievement of quantum many-body optimal control utilizing artificial neural networksHerschel Rabitz, the Charles Phelps Smyth '16 *17 Professor of Chemistry; Tak-San Ho, research chemist
This project seeks to harness artificial neural networks to design, model, understand and control quantum dynamics phenomena between different particles, such as atoms and molecules.(Note: This project also received DataX funding in 2019.)
Discovery and design of the next generation of topological materials using machine learningLeslie Schoop,assistant professor of chemistry; Bogdan Bernevig, professor of physics; Nicolas Regnault, visiting research scholar in physics
This project aims to use machine learning techniques to uncover and develop topological matter, a type of matter that exhibits quantum properties, whose future applications can impact energy efficiency and the rise of super quantum computers. Current topological matters applications are severely limited because its desired properties only appear at extremely low temperatures or high magnetic fields.
- PhD Program | ML (Machine Learning) at Georgia Tech - January 20th, 2022
- Dask-ML dask-ml 2021.11.31 documentation - January 20th, 2022
- How Snapchat Is Using AI And Machine Learning To Thwart Drug Deals - Hot Hardware - January 20th, 2022
- Data Vault Holdings Expands Expertise In Artificial Intelligence, Machine Learning, and Big Data; Appoints Tony Evans of C3 AI To Advisory Board -... - January 20th, 2022
- Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction | Scientific Reports -... - January 20th, 2022
- The 6 Best Deep Learning Tutorials on YouTube to Watch Right Now - Solutions Review - January 20th, 2022
- Agnostiq Announces Partnership With Mila to Bridge the Quantum Computing and Machine Learning Communities - PRNewswire - January 20th, 2022
- Machine learning assisted real-time deformability cytometry of CD34+ cells allows to identify patients with myelodysplastic syndromes | Scientific... - January 20th, 2022
- 6 Ways Machine Learning Can Improve Customer Satisfaction - TechSpective - January 20th, 2022
- Analyzing Twisted Graphene with Machine Learning and Raman Spectroscopy - AZoNano - January 20th, 2022
- Cloudian Partners with WEKA to Deliver High-Performance, Exabyte-Scalable Storage for AI, Machine Learning and Other Advanced Analytics -... - January 20th, 2022
- Klika Tech Joins tinyML Foundation to Accelerate Development of Machine Learning at the Edge - PR Web - January 20th, 2022
- From Coffee Cart to Educational Computing Platform - UC San Diego Health - January 20th, 2022
- Five Machine Learning Applications in Healthcare - CIO Applications - January 20th, 2022
- Global Machine Learning in Automobile Market Size 2021-2029 Trend and Opportunities Discovery Sports Media - Discovery Sports Media - January 20th, 2022
- AI and Advance Machine Learning in BFSI Market Global Report 2021-2030 Featuring Leading Players - Cisco, SAP, Microsoft and IBM Among Others -... - December 22nd, 2021
- Machine Learning Democratized: Of The People, For The People, By The Machine - Forbes - December 22nd, 2021
- Top Python Machine Learning Libraries to Explore in 2022 - Analytics Insight - December 22nd, 2021
- Grants totaling $4.6 million support the use of machine learning to improve outcomes of people with HIV - Brown University - December 22nd, 2021
- Chat Commerce, machine learning and a stronger privacy focus eCommerce predictions for 2022 - BetaNews - December 22nd, 2021
- New platform uses machine-learning and mass spectrometer to rapidly process COVID-19 tests - UC Davis Health - December 22nd, 2021
- Machine Learning as a Service (MLaaS) Market will witness a CAGR of 49% 2021: Global Industry Insights by Global Players, Regional Segmentation,... - December 22nd, 2021
- Top Computer Vision Jobs to Apply in December 2021 - Analytics Insight - December 22nd, 2021
- LiveFreely Announces Apple Watch Version of 'BUDDY,' the Predictive AI-Driven Digital Health Assistant for Seniors and Their Loved Ones - Yahoo... - December 22nd, 2021
- These are the top priorities for tech executives in 2022, survey reveals - CNBC - December 22nd, 2021
- Machine Learning as a Service (MLaaS) Market 2021: Big Things are Happening in Development and Future Assessment by 2031 - Digital Journal - December 22nd, 2021
- Revisit Top AI, Machine Learning And Data Trends Of 2021 - ITPro Today - December 16th, 2021
- The automated machine learning market is predicted to reach $14,830.8 million by 2030, demonstrating a CAGR of 45.6% from 2020 to 2030 - Yahoo Finance - December 16th, 2021
- Human-centered AI can improve the patient experience - Healthcare IT News - December 16th, 2021
- Continual Launches With $4 Million in Seed to Bring AI to the Modern Data Stack - Business Wire - December 16th, 2021
- Artificial intelligence accurately predicts who will develop dementia in two years - EurekAlert - December 16th, 2021
- Real World Application of Machine Learning in Networking - IoT For All - December 16th, 2021
- Machine learning predicts risk of death in patients with suspected or known heart disease - EurekAlert - December 16th, 2021
- Reasons behind the Current Hype Around Machine Learning - CIO Applications - December 16th, 2021
- They test a machine learning system with 530,000 million parameters and this warns of the dangers of artifi... - Market Research Telecast - December 16th, 2021
- Quantum Mechanics and Machine Learning Used To Accurately Predict Chemical Reactions at High Temperatures - SciTechDaily - December 16th, 2021
- AWS re:Invent: How to Use Machine Learning and Other Technology to Make the Most of Your Data - Inc. - December 3rd, 2021
- A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation |... - December 3rd, 2021
- Mindtree has Earned the Al and Machine Learning on Microsoft Azure Advanced Specialization - PRNewswire - December 3rd, 2021
- AFTAs 2021: Most innovative third-party technology vendor (AI, machine learning and analytics)Moody's Analytics - www.waterstechnology.com - December 3rd, 2021
- Machine Learning Clarifies Stress-Based Degradation of Biosimilars - The Center for Biosimilars - November 25th, 2021
- Artificial Intelligence, Machine Learning, and Biometric Security Technology will be Drivers of Digital Transformation in 2022 And Beyond: IEEE... - November 25th, 2021
- ExoMiner Goes Planet Hunting! NASA's Machine Learning Network Validates 301 New Exoplanets at One Go | The Weather Channel - Articles from The Weather... - November 25th, 2021
- BIS: What Does Machine Learning Say About The Drivers Of Inflation? - Exchange News Direct - November 25th, 2021
- Machine learning can improve your public services. Are you ready to take the red pill? - The Register - November 25th, 2021
- Less energy, better quality PAM images with machine learning - The Source - Washington University in St. Louis - Washington University in St. Louis... - November 25th, 2021
- How AI Is Poised to Help Humanity - Entrepreneur - November 25th, 2021
- Women Innovators And Researchers Who Made A Difference In AI In 2021 - Analytics India Magazine - November 25th, 2021
- Machine learning optimization of an electronic health record audit for heart failure in primary care - DocWire News - November 25th, 2021
- Your neighborhood matters: A machine-learning approach to the geospatial and social determinants of health in 9-1-1 activated chest pain - DocWire... - November 25th, 2021
- Design of AI may change with the open-source Apache TVM and a little help from startup OctoML - ZDNet - November 25th, 2021
- Global Marketing Automation Market Report 2021: Market to Reach $6.3 Billion by 2026 - GlobeNewswire - November 25th, 2021
- IEEE: Most Important 2022 Tech Is AI/Machine Learning, Cloud and 5G - Virtualization Review - November 20th, 2021
- ML Kit | Google Developers - November 20th, 2021
- MCubed does web workshops: Join Mark Whitehorns one-day introduction to machine learning next month - The Register - November 20th, 2021
- DEWC, AIML partner on AI and machine learning to enhance RF signal detection - Defence Connect - November 20th, 2021
- How Machine Learning is Used with Operations Research? - Analytics India Magazine - November 20th, 2021
- Machine learning: Aleph Alpha works on transformative AI with Oracle and Nvidia - Market Research Telecast - November 20th, 2021
- Edinburgh machine learning specialist to add 100 jobs thanks to investment co-venture - The Scotsman - November 20th, 2021
- Brivo Unveils Anomaly Detection, a Revolutionary Technology that Harnesses Access Data and Machine Learning to Strengthen Built World Security - Yahoo... - November 20th, 2021
- Adelaide at the centre of next generation AI research - Newswise - November 20th, 2021
- Research Team Probes History with Cutting-Edge Tech - Bethel University News - November 20th, 2021
- Alphabet is putting its prototype robots to work cleaning up around Googles offices - The Verge - November 20th, 2021
- Red Hat bets on artificial intelligence and ... - BNamericas English - November 15th, 2021
- Top 10 Machine Learning Projects to Boost Your Resume - Analytics Insight - November 15th, 2021
- Exploring the Impact of Machine Learning and Artificial Intelligence in Drug Development from Discovery to Healthcare - PR.com - November 15th, 2021
- Google and AWS harness the power of machine learning to predict floods and fires - ZDNet - November 15th, 2021
- BigBear.ai And Palantir Announce Strategic Partnership, Combining AI-powered Products With Next Generation Operating Platform - Yahoo Finance - November 15th, 2021
- Performance of a machine-learning algorithm to predict hypotension in mechanically ventilated patients with COVID-19 admitted to the intensive care... - November 15th, 2021
- Verizon CIO Shankar Arumugavelu on putting emerging technologies to work - CIO - November 15th, 2021
- Middle East and Africa Machine Learning Market Report by Connectivity Technology, by Application, by Type, by Region Global Forecast to 2026 ... - November 15th, 2021
- Global Machine Learning in Healthcare Market Potential growth, attractive valuation make it is a long-term investment 2027 Energy Siren - Energy... - November 15th, 2021
- Qualcomm is researching machine learning at the edge - Stacey on IoT - November 3rd, 2021
- TrainerRoad Announces Release of Adaptive Training Platform, Making Machine Learning-Powered Training Available to Cyclists - Outside Business Journal - November 3rd, 2021
- Turn your tech skills into machine learning expertise with this book and class bundle - TechRepublic - November 3rd, 2021
- Psychologists use machine learning algorithm to pinpoint top predictors of cheating in a relationship - PsyPost - November 3rd, 2021
- MIT: Forcing ML Models to Avoid Shortcuts (and Use More Data) for Better Predictions - insideHPC - November 3rd, 2021
- Top Machine Learning Tools Used By Experts In 2021 - Analytics Insight - November 3rd, 2021
- New exhibition to investigate the history of AI & machine learning in art. - FAD magazine - November 3rd, 2021
- Machine Learning May Help Predict Success of Prescription Opioid Regulations | Columbia Public Health - Columbia University - November 3rd, 2021