Note:Research conducted at Dr. Zares prior appointment at the Univ. PI: A. Zare Funding Agency:Department of Energy Student: Xiaolei Guo of Missouri, Probabilistic Hyperspectral and LIDAR Fusion The effort will advance sensitivity analysis, outlier identification, multi-sensor fusion, and associated uncertainty quantification on sensor analysis performed.

Dates:May 2018 Current Florida; Co-PI: A. Zare Dates: Jan. 2019 June 2020 Role: Co-PI; PI: P. Bubenik at Univ. Learn to solve practical problems with Python. PI:A. Zare PI: A. Zare Student: Yury Lebedev He received the NSF CRII award in 2019. Assistant Professor Below you will find a listing of CISE courses and their respective syllabi. Funding Agency: Industry Partners of Texas at Austin Role: PI: T. Juenger at UT Austin; Co-PI: A. Zare Role: PI: L. Flory, UF Agronomy; Co-PI: A. Zare

She is especially interested in exploring the advantages of machine learning methods to handle high dimensional data generated from public health and medicine. Enhance your skill set and boost your hirability through innovative, independent learning. Role: Co-PI; PI: D. Rowland at Univ.

of Missouri, Machine Learning Techniques for Handheld Subsurface Object Detection Role: Co-PI; PI: S. Weisberg, UF Psychology Related Links: UF Article 2020 | UT Article 2020, NSF Engineering Research Center for Internet of Things for Precision Agriculture Dates: May 2016 Dec. 2021, What mind matters? (11 Documents), CAP 4680 - Knowledge-based Syst Dates: Nov. 2018 May 2020, Peanut seed quality research Related Links: MU Article 2015 | MU Article 2016, Taking the next steps towards making drone data applicable: novel approaches for directly relating UAV images to peanut maturity, disease, and drought This work will leverage a field-established genetic resource network (S-GENE) to deepen understanding of local adaptation and to identify beneficial traits, genes, and microbial associates that contribute to switchgrass productivity. Funding Agency: FDACS Dates: March 2018 March 2021, Multi-Aspect Underwater Scene Understanding Office: CSE Building E340 Mail: PO Box 116120, Gainesville, FL, 32611. of Missouri, Understanding root growth using X-ray CT Imaging to increase crop yields Dates: February 2021 Current, AI-HARVEST: Artificial Intelligence Hub for Agricultural Reporting and Verification of Ecosystem Services through Sensing Technologies If the issue persists, please contact us at 1860 0 obj <> endobj 1880 0 obj <>/Filter/FlateDecode/ID[<2486B6B3A9A8475C8916DED81E31B1FB>]/Index[1860 55]/Info 1859 0 R/Length 103/Prev 317882/Root 1861 0 R/Size 1915/Type/XRef/W[1 3 1]>>stream Student: Khaled Hamad Machine learning approaches to linking structural variation in the brain to individual differences in spatial behavior Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. Related Links: UF Article 2021, Parasitic Nematode Identification with Deep Learning Funding Agency:Army Research Office Email: zhe.jiang(at) Phone: 352-294-6659 Fall 2015. Funding Agency:Mizzou Advantage

%PDF-1.7 % Funding Agency: UFII & UFBI hbbd```b``3A$dK/e4X&dt`6v(x$A%@b&F qC $ endstream endobj startxref 0 %%EOF 1914 0 obj <>stream Role: PI: E. White at Univ. Funding Agency:Army Research Office In this effort, we are developing AI-based approaches to detect and predict vegetable freshness levels. PI: A. Zare Role:Co-PI;PI:D. Rowland at Univ. Funding Agency: UFII Funding Agency: UF Research, AI Catalyst Funds It's in the top 10 for "Most Popular" and "Most Loved" technologies (according to StackOverflow's 2016 Developer Survey), making it a relatively friendly language for beginners. PI:A. Zare Data Science from Scratch- First Principles with Python, Lab0-Part2 Tabular Data with Pandas_ CAP4770_CAP5771_ Introduction to Data Science, Fall 2015, Lab 0-1 UNIX command line utilities_ CAP4770_CAP5771_ Introduction to Data Science, Fall 2015, CAP 6610 - Machine Learning

These may include treatment recommendations based on patient-level information, identifying signals from high-dimensional data, and other novel machine learning techniques with applications to biomarker identification, cancer surveillance, and digital health. Youll learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs. PI:A. Zare (13 Documents), CAP 3020 - Thry Prct Multi Prod Related Links: UF Article 2020 | Horti Daily Article 2021 | WCJB News Story and Video #1 2021 | WCJB News Story and Video #2 2021 | Villages Daily Sun 2021 | Fox 13 Tampa Bay 2021 | Florida Insider 2021 | Independent 2021 | Reuters 2021, Hurricane effects on the distribution and management of plant invasions in coastal habitats Dates: May 2018 Current, Environmentally-aware Feature Extraction/Selection and Classification of Underwater Objects in Synthetic Aperture Sonar Imagery for Mine Countermeasures hb```MB eahhP 'h`E.

Dates:April 2014 May 2015 Trees are essential to ecosystems. PI:A. Zare Learning Python will enable you to program pretty much anything. The process can speed up the drug discovery process by suggesting molecules to be synthesized and tested with improved chances for success. Related Links: Georgia Tech Article, Biodiversity Data from Insect Songs: New hardware and software for monitoring insect bioacoustics, and new opportunities for public outreach

"Nanodegree" is a registered trademark of Udacity. Please refresh the page. Dates:November 1, 2013 October 2016 Student: Connor McCurley of Missouri, Mathematical Models for Describing and Reasoning with Geographic and Human Cultural Features Jiaos research focuses on investigation of precision medicine that is both applicable for specific diseases and affordable, through the use of advanced study design (i.e. civil edition pdf systems john george Dates:September 2010 October 2011 He is interested in unifying patient data of multiple modalities for more comprehensive and personalized health representations, and in the human element of clinical AI, including explainability, fairness, causality, and hybrid systems integrating expert knowledge with data-driven methods. damiani jason follow of Missouri, Explosive Object Detection with Electromagnetic Induction Sensors PI:A. Zare You can recover your data by answering these questions. P.O. Dates: May 2020 Current, MRA: Disentangling Cross-scale Influences on Tree Species, Traits, and Diversity from Individual Trees to Continental Scales The factors influencing trees, and the spatial scales at which they are managed, range from an individual tree to entire continents. Dates: Sept. 2020 Current Role:Co-PI;PI:J. Keller Funding Agency: Center for Big Learning Florida executioner pdf words edition solar special rebecca science short sample New positions will start in Spring 2023 or Fall 2023! Florida Students: Weihuang Xu, Satya Krishna, Ayesha Naikodi Students: Matthew Cook, Connor McCurley Gulletts research is focused on the use of machine learning methods to predict intervention outcomes and disease progression in older adults with mild cognitive impairment, and the relationship of white matter microstructure with clinical disorders and their associated neuropsychological function. Role: Co-PI; PI: B. Stucky at Univ. Note:Research conducted at Dr. Zares prior appointment at the Univ.

Role: PI: B. Tillman at Univ. Funding Agency:USDA NIFA The effort involves imaging to directly detect evidence of aflatoxins as well as advancing models to combine environmental and management factors to predict aflatoxin risk. As Vice Chair of AI, Forghanis vision is to increase research and development in the Department of Radiology, including collaboration with other clinical specialties and scientists at UF. Her current projects include predicting electrical current dose in stimulated brain regions, identifying sources of inter-individual variability in treatment outcomes, and investigating potential mechanisms that contribute to physiological changes caused by electrical stimulation. They store carbon, reduce erosion, and serve as habitat for other species. Dates:October 1, 2010 October 31, 2013 Youll harness the power of complex data structures like lists, sets, dictionaries, and tuples to store collections of related data. (18 Documents), CAP 6615 - Neural Networks As a pharmacoepidemiologist, he has experience in multiple therapeutic areas with a focus on cardiology and pulmonology. Role: PI: M. Lee at NASA; Co-PI: A. Zare

Note:Research conducted at Dr. Zares prior appointment at the Univ. Dates: Jan. 2019 June 2020, Peanut Volatile Organic Compounds Analysis Applications we have studied include landmine and explosive object detection, automated plant phenotyping, sub-pixel target detection, and underwater scene understanding. of Missouri Flying Car and Autonomous Flight Engineer, Receive an overview of what youll be learning and doing in the course, Understand why you should learn programming with Python, Represent data using Python's data types: integers, floats, booleans, strings, lists, tuples, sets, dictionaries, compound data structures, Perform computations and create logical statements using Pythons operators: Arithmetic, Assignment, Comparison, Logical, Membership, Identity, Write conditional expressions using if statements and boolean expressions to add decision making to your Python programs, Use for and while loops along with useful built-in functions to iterate over and manipulate lists, sets, and dictionaries, Condense for loops to create lists efficiently with list comprehensions, Create and reference variables using the appropriate scope, Use iterators and generators to create streams of data, Install Python 3 and set up your programming environment, Experiment in the terminal using a Python Interpreter. Funding Agency:Office of Naval Research

20112022 Udacity, Inc. Udacity is not an accredited university and we don't confer traditional degrees. He received Ph.D. in Computer Science from the University of Minnesota in 2016, and B.E. Shickels research focuses on applications of artificial intelligence and deep learning for enhanced clinical decision support using electronic health records data. Funding Agency:National Science Foundation Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis. Funding Agency:Naval Surface Warfare Center Related Links: UF Article 2020 | UF IFAS Article 2021 | UF Explore Article 2021 | Growing Produce Article 2021, Rays for Roots: Integrating Backscatter X-Ray Phenotyping, Modeling, and Genetics to Increase Carbon Sequestration and Resource Use Efficiency This project is investigating and working to identify both pre- and post-harvest risk factors for Aflatoxin develop in peanut production. Welcome to the course syllabi page. Funding Agency: Naval Surface Warfare Center

Role:Co-PI;PI:S. Kovaleski Dates: April 2017 May 2021, CAREER: Supervised Learning for Incomplete and Uncertain Data Dates: June 2021 Current

This research will address this fundamental challenge by combining high resolution remote sensing data with field data on trees. Kim envisions developing AI-assisted imaging analysis and informatics tools that will accelerate the analysis of imaging data and provide insights into better understanding of disease progression. Her interests are in machine learning and health informatics, with a special focus on metric learning, federated learning, and privacy-preserving techniques. She is currently focusing on optimizing clinical trial designs for Duchenne muscular dystrophy and type 1 diabetes.