GiorgioML
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  • Recent & Upcoming Talks
    • Presentation at the Advances in Adaptive Experimentation Workshop @ UCL
    • Symbolic Regression Talk at EUROMECH Colloquium 662
    • Trustworthy AI Seminar at UPV
    • Presentation at DIGICROP 2025
    • Managing Uncertainty in Regression Neural Networks - From Prediction Intervals to Adaptive Sampling
    • Decomposable Symbolic Regression Using Transformers and Neural Network-Assisted Genetic Algorithms
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    • Presentations at ECML-PKDD 2024
    • Counterfactual Explanations of Nitrogen Response Curves
    • Prediction Software using OFPE and Machine Learning
  • Blog
    • Presentation at Euromech Colloquium 662
    • I've got a paper accepted at IJCNN 2026
    • I've been awarded the Aston AI Fellowship
    • I've got a workshop paper accepted at EurIPS 2025
    • I defended my PhD thesis
    • I received the Gianforte School of Computing's "Outstanding PhD Researcher" Award
    • I received MSU's "Everyday Hero of Research" Award
    • Our J2C presentation was accepted at IJCNN 2025
    • Our AAAI paper was presented in Philadelphia today
    • Blog post - Diffusion Models Background
    • I've got a paper accepted at AAAI 2025
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    • I won the first place in the SMAC competition at ECML PKDD 2024
    • Our IJCNN paper was presented in Yokohama today
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    • I've got a paper accepted at ECML PKDD 2024
    • I've got a paper accepted at IJCNN 2024
    • Blog post - Prediction Intervals Generation in Python
    • I've got a journal paper accepted at IEEE TNNLS
    • I received the Chunzi "Chris" Zhang Award
    • Interview with MSU's Graduate School
    • On-Field Precision Experiment (OFPE) Framework project
    • Blog post - Best hyperspectral bands for Indian-Pines and Salinas datasets
    • Blog post - Linear Regression in PyTorch
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  • Publications
    • Neutrino Oscillation Parameter Estimation Using Structured Hierarchical Transformers
    • Learning Parametric Nitrogen Fertilizer Response Curves Using Neuro Symbolic Regression
    • Towards Uncertainty Quantification in Generative Model Learning
    • Decomposable Neuro Symbolic Regression
    • Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks
    • Univariate Skeleton Prediction in Multivariate Systems Using Transformers
    • Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones
    • Counterfactual Explanations of Neural Network-Generated Response Curves
    • Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation
    • Improved Yield Prediction of Winter Wheat Using a Novel Two-Dimensional Deep Regression Neural Network Trained via Remote Sensing
    • Decision Support From On-Field Precision Experiments
    • Generation of Site-specific Nitrogen Response Curves for Winter Wheat using Deep Learning
    • Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat Production
    • Two-dimensional deep regression for early yield prediction of winter wheat
    • Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks
    • Hyperspectral Dimensionality Reduction Based on Inter-Band Redundancy Analysis and Greedy Spectral Selection
    • Towards reduced-cost hyperspectral and multispectral image classification
    • Reduced-cost hyperspectral convolutional neural networks
    • End-to-end Cloud Segmentation in High-Resolution Multispectral Satellite Imagery Using Deep Learning
    • Estimation of 2D Velocity Model using Acoustic Signals and Convolutional Neural Networks
    • Regression Models between Active Sensor-Measured NDVI and UAV-Acquired Multispectral Images with Positioning Uncertainty
    • Cloud Detection for PERUSAT-1 Imagery Using Spectral and Texture Descriptors, ANN, and Panchromatic Fusion
    • Detecting Violent Robberies in CCTV Videos Using Deep Learning
    • Shadow Removal in High-Resolution Satellite Images Using Conditional Generative Adversarial Networks
    • Automatic Segmentation of Mauritia flexuosa in Unmanned Aerial Vehicle (UAV) Imagery Using Deep Learning
    • PETEFA: Geographic Information System for Precision Agriculture
    • Shadow Detection in High-Resolution Multispectral Satellite Imagery Using Generative Adversarial Networks
    • Cloud Detection in High-Resolution Multispectral Satellite Imagery Using Deep Learning
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Presentation at the Advances in Adaptive Experimentation Workshop @ UCL

Jun 18, 2026·
Giorgio Morales
Giorgio Morales
· 1 min read
Poster Presentation @ UCL
Abstract
Dissemination of our AAAI 2025 paper
Date
Jun 18, 2026 — Jun 19, 2026
Event
Advances in Adaptive Experimentation Workshop
Location

Sainsbury Wellcome Centre

London

Giorgio Morales presenting at an UCL workshop
Poster presentation @ UCL.
Last updated on Jun 18, 2026
Giorgio Morales
Authors
Giorgio Morales
AI Research Associate
Symbolic Regression Talk at EUROMECH Colloquium 662 Apr 28, 2026 →

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