Navigating investigations in oceans of data and making discoveries is possible only with the use of efficient algorithms. As data grows in volume, velocity, variety, and veracity, so does the demand for efficiency in data science applications. Artificial Intelligence (AI) and Machine Learning (ML), will streamline algorithms based on algorithmic and methodological developments from the field of AI. The computational methods of AI aim to mimic human intelligence but also exceed human capabilities, assisting humans in decision making and in solving complex problems.
The numerous branches of AI encompass ML, natural language understanding (spoken and written), computer vision, data mining, human-computer interfaces, data visualization, and, more recently, deep learning. In all these areas, data plays a crucial role as algorithmic innovations are developed from within while taking inspiration from mathematics, statistics, and physics. The applications of these major branches of AI are broad, reaching far beyond the traditional realm of science and engineering, and ushering in crucial advances in medicine, the social sciences, business, and even the arts and the humanities.
Yelena Yesha, PhD
Knight Foundation Endowed Chair of Data Science and AI
Director, IDSC AI + Machine Learning
IDSC Innovation Officer
Professor, Department of Computer Science, College of Arts and Science
Professor, Department of Radiology, Miller School of Medicine
Founding Director, NSF CARTA
About Dr. Yesha
At the University of Miami, Dr. Yelena Yesha is the Knight Foundation Endowed Chair of Data Science and AI at the Frost Institute for Data Science and Computing (IDSC). At IDSC, Dr. Yesha is also the Innovation Officer and Head of International Relations. In this role, Dr. Yesha assists faculty in engaging government and industrial partners to collaborate with the University and consults with faculty on developing research ideas into innovations.
Dr. Yesha was the Founding Director of the National Science Foundation Center for Accelerated Real Time Analytics (CARTA), an NSF-funded Industry/University Cooperative Research Center (I/UCRC) that aims to develop long-term partnerships among industry, academia, and government. CARTA partners with Rutgers University New Brunswick, North Carolina State University, the University of Maryland Baltimore County (UMBC), Tel Aviv University, and the University of Miami.
Dr. Yesha received her B.Sc. degrees in Computer Science and in Applied Mathematics from York University, Toronto, Canada, and her M.Sc. degree and Ph.D. degree in Computer Science from The Ohio State University She has published 11 books as author or editor, and more than 200 papers in prestigious refereed journals and refereed conference proceedings, and she has been awarded external funding in a total amount exceeding $50 million dollars. She is currently working with leading industrial companies and government agencies on new innovative technology in the areas of blockchains, cybersecurity, and big data analytics with applications to electronic commerce, climate change, and digital healthcare. Dr. Yesha is also a Fellow of the IBM Centre for Advanced Studies.
Forbes magazine highlighted Dr. Yesha’s accomplishments in technology in a two-part profile:
- Part I: Dr. Yelena Yesha: Meet The Tenacious Pioneer Pushing Innovation To Address Real World Problems and
- Part II: Dr. Yelena Yesha: Pushing Technology Boundaries To Solve The World’s Biggest Problems.
News + Events
- GovExec SLG Tech Summit Takeaway: Don’t Fear AI, Prepare for its Wider Use (VIDEO)
- Dr. Yelena Yesha speaks at Data Science Conference on 10/10
- Experts Explore Technology’s Potential to Bolster Democracy and Education at eMerge
- The U Recognizes 10 Women in Technology at eMerge Americas 2022
- Dr. Yelena Yesha Featured Speaker at FLAIRS-35 5/15-18
- UM at eMerge 4/18+19 Showcases Innovation and Recognizes Women in Tech
- Catch the Replay: Take Action! Bias in Technology with Yelena Yesha
- Dr. Yelena Yesha to Speak on Trusted AI at “Hack the Port 22” in FTL Monday 3/21
- Yelena Yesha: Keynote Speaker at Take Action! Bias in Technology 3/17
- Drs. Yelena Yesha and Pierre-François d’Haese Speak at FDA AI/ML Meeting 11/29
- Dr. Yelena Yesha spoke at 9/28 State of the University Town Hall Panel on Innovation
- NIH Funds New Consortium Aimed at Advancing Health Equity and Researcher Diversity
- Women in Academia Looks at Female Endowed Chairs
- Dr. Yesha speaks at NANS Neuromodulation Society Meeting 7/15-17
- Dr. Yelena Yesha Named First Knight Foundation Chair of Data Science and AI
- Using Data and Digital Tools to Improve Health and Well-Being
- Catch the Replay: Smart Cities MIAMI 2021 Reimagines Healthcare
- Catch the Replay: Meet a Data Scientist with Yelena Yesha
- Using Blockchain to Empower Digital Government
- Yelena Yesha Receives IEEE Lifetime Achievement Award
- New Book: Exploring Data Science with R and the Tidyverse
- Computational Approaches to Understanding Interaction and Development
- IEEE Computer Journal: Challenges and Issues in Data Science Education
- Frontiers in Psychology: Remote Data Collection During a Pandemic
- Early Interaction: New Approaches
- Remote Data Collection During a Pandemic: A New Approach for Assessing and Coding . . .
- Recommendations for the Safe, Effective Use of Adaptive CDS in the US Healthcare System
- Yearbook of Medical Informatics: Ethics in Health Informatics
- Inference From Complex Networks: Role of Symmetry and Applicability to Images
- iDEC: Indexable Distance Estimating Codes for Approximate Nearest Neighbor Search
- Balancing Risks and Benefits of Artificial Intelligence in the Health Sector
- Hoshi: A Japanese Morphological Adorner for TEI XML
- Stigma, Biomarkers, and Algorithmic Bias: Recommendations for Precision Behavioral Health with AI
- Long-Duration Waveform Descriptive Grammar for Consumer Electronics Design, Diagnosis, and Validation
- Machine and Deep Learning Approaches for Cancer Drug Repurposing
- Scaling Up Heterogeneous Waveform Clustering for Long-Duration Monitoring Signal Acquisition, Analysis, and Interaction
- Ren, Ogihara, and Johnson Present Papers at IEEE 2019 in Beijing
- The “Dark” Energy Between Sonic Partials: Parametrics Estimation and Analysis of . . .
- A New Auditory Image for Social Media: Moving Towards Correlation of Spectrographic Analysis . . .
- Multi-Scale Auralization for Multimedia Analytical Feature Interaction