Conference Information
FMLDS 2025: IEEE International Conference on Future Machine Learning and Data Science
https://www.fmlds.org/
Submission Date:
2025-06-15
Notification Date:
2025-07-31
Conference Date:
2025-11-02
Location:
Los Angeles, California, USA
Viewed: 2342   Tracked: 1   Attend: 0

Call For Papers
As an interdisciplinary international conference this conference welcomes ideas outside of the box, interdisciplinary collaborations as well as new topics for research which may be outside of mainstream.

Conference Tracks

(It will of course welcome papers on but by no means restricted to in existing disciplines, e.g.)

Future Machine Learning

    Explainable Artificial Intelligence
    Quantum Computing
    Big Data Modeling
    No-Code Development Environments
    Reinforcement Learning

Machine Learning in Engineering Applications

    Construction Engineering
    Water Engineering

Computer Vision and Graphics

    Biometrics
    Aqua Farming Technologies
    Low- Level Vision and Image Processing
    Motion and Tracking Technologies

Bioinformatics and Biomedical Applications

    Bioinformatics
    Video Analysis and Event Recognition
    Signal Processing
    Support Vector Machines (SVM)
    Bayesian Belief Networks

Data Classification and Regression

    Denoising and Functional Recovery
    Interpretation and Approximation
    Spectral and Area Based Methods
    Data and Image Compression

Cyber Security and Privacy for Big Data

    Cyber-attacks
    Cyber Security

Machine Learning in Social Media and Social Network

    Classification of Diseases and Genomic Sequencing
    Social Network Analysis

Machine Learning in Internet of Things (IoT)

    Artificial Intelligence Techniques in IoT

Advancements of Machine Learning

    Improved Internet Search
    Chatbots and Conversational AI (e.g., ChatGPT)
    Applications in Transportation
    Applications in Music, Art and Leisure

Pattern Recognition

    Fuzzy Logic, Learning Theory
    Reasoning with incomplete data
    Set Theory and Probabilistic Approaches Affective Computing
    Statistical Methods in Motion Tracking

Robotics and Automation

    Robotics Application
    Testing and Performance Evaluation

Data Science and Big Data

    Cloud Computing and High Performance Computing
    Scalable Computing and Computations on GPU
    Information Retrieval

Knowledge Discovery, Integration and Transformation

    Social Epidemiology, Algorithms in Neuroscience
    Neuro-psychoanalysis

Machine Learning in Finance and Data Mining

    Financial Engineering & Economics Applications
    Portfolio Optimization and Asset Allocation
    Algorithmic and Quantitative Trading
    Financial Data Analysis

Machine Learning in Language Models

    Large Language Models (LLMs)
    Vision Language Models (VLMs)
Last updated by Dou Sun in 2025-05-01
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