Artificial Intelligence, Machine Learning, and Data Science Journal
Editorial Board
Artificial Intelligence, Machine Learning, and Data Science Journal is guided by a distinguished international panel of AI researchers, machine learning scientists, and data science experts committed to the highest standards of rigour and reproducibility.
Editorial Structure
Editor-in-Chief
Sets the research direction of the journal, makes final acceptance decisions, and upholds standards of reproducibility and open science.
Senior Editors
Domain leads overseeing manuscript handling for core thematic areas including deep learning, NLP, computer vision, and data science.
Associate Editors
Manage the double-blind peer-review process, curate qualified reviewers, and provide detailed editorial recommendations.
International Board
A worldwide network of AI specialists ensuring global diversity of perspective and alignment with international research standards.
Editor-in-Chief
Prof. Andrew Liu, PhD
MIT Computer Science & Artificial Intelligence Laboratory (CSAIL), Cambridge, USA
Expertise: Deep Learning & Neural Architecture Design · Foundation Models · Scalable AI Systems
Prof. Liu is a leading figure in deep learning research with over 25 years of experience spanning academia and industry. He has authored more than 180 peer-reviewed papers and holds 14 patents in neural architecture design. A former research director at a top AI laboratory, he is deeply committed to open-access, reproducible AI research.
Senior Editors
Prof. Sarah Mitchell, PhD
Stanford AI Lab (SAIL), Stanford University, USA
Expertise: Natural Language Processing · Large Language Models · Computational Linguistics
Prof. Raj Patel, PhD
Robotics Institute, Carnegie Mellon University, Pittsburgh, USA
Expertise: Computer Vision · Robotic Perception · 3D Scene Understanding
Prof. Elena Volkova, PhD
Department of Computer Science, ETH Zurich, Switzerland
Expertise: Reinforcement Learning · Multi-Agent Systems · Control Theory & AI
Prof. Chen Wei, PhD
Institute for Artificial Intelligence, Tsinghua University, Beijing, China
Expertise: Big Data Analytics · Distributed Machine Learning · Data Engineering
Associate Editors
Dr. James Okafor, PhD
Department of Computer Science, University College London, UK
Expertise: Federated Learning · Privacy-Preserving ML · Differential Privacy
Dr. Priya Sharma, PhD
Department of Computational & Data Sciences, Indian Institute of Science, Bengaluru, India
Expertise: AI Ethics · Algorithmic Fairness · Responsible AI
Dr. Marcus Bauer, PhD
Max Planck Institute for Intelligent Systems, Tübingen, Germany
Expertise: Generative Models · Variational Autoencoders · Diffusion Probabilistic Models
Dr. Yuki Tanaka, PhD
Graduate School of Information Science, University of Tokyo, Japan
Expertise: Time Series Analysis · Forecasting with Deep Learning · Sequential Data Modelling
Dr. Sofia Alvarez, PhD
Artificial Intelligence Research Lab, University of Barcelona, Spain
Expertise: Graph Neural Networks · Geometric Deep Learning · Relational Reasoning
Dr. David Mensah, PhD
Department of Computer Science, University of Ghana / Google Research, Accra, Ghana
Expertise: AI for Development · Low-Resource NLP · Sustainable Machine Learning
International Editorial Board
Prof. Li Fang, PhD
School of Computer Science, Peking University, China
Expertise: Knowledge Graphs · Semantic AI · Ontology Engineering
Dr. Fatima Al-Hassan, PhD
Computer Science Program, King Abdullah University of Science & Technology, Saudi Arabia
Expertise: Bayesian Deep Learning · Uncertainty Quantification · Probabilistic ML
Prof. Alexandre Dupont, PhD
INRIA Paris & École Normale Supérieure, France
Expertise: Optimisation Theory · Mathematical Foundations of ML · Convex Analysis
Dr. Nadia Kovacs, PhD
Faculty of Electrical Engineering & Informatics, Budapest University of Technology, Hungary
Expertise: Anomaly Detection · AI for Cybersecurity · Intrusion Detection Systems
Prof. Samuel Osei, PhD
Department of Computer Science, University of Cape Town, South Africa
Expertise: African NLP · Low-Resource Language Modelling · Transfer Learning
Dr. Isabella Romano, PhD
Department of Computer, Control and Management Engineering, Sapienza University of Rome, Italy
Expertise: Explainable AI (XAI) · Model Interpretability · Human-Centred ML
Prof. Arun Krishnamurthy, PhD
Department of Computer Science & Engineering, IIT Bombay, India
Expertise: Scalable ML Systems · MLOps · High-Performance Computing for AI
Dr. Hannah Schmidt, PhD
Chair of Artificial Intelligence & Machine Learning, RWTH Aachen University, Germany
Expertise: AI in Healthcare · Medical Imaging · Clinical Decision Support Systems
Prof. Carlos Mendoza, PhD
Instituto de Investigaciones en Matemáticas Aplicadas, UNAM, Mexico City, Mexico
Expertise: Quantum Machine Learning · Hybrid Classical-Quantum Algorithms · Complexity Theory
Dr. Min-jun Park, PhD
School of Computing, KAIST (Korea Advanced Institute of Science and Technology), South Korea
Expertise: Autonomous Systems · Deep Reinforcement Learning · Sim-to-Real Transfer
Represented Institutions & Labs
North America
- MIT CSAIL
- Stanford AI Lab (SAIL)
- CMU Robotics Institute
- University of Toronto Vector Institute
- University of California, Berkeley
- University of Washington Allen School
Europe
- ETH Zurich
- Max Planck Institute for Intelligent Systems
- INRIA Paris
- University College London
- University of Oxford — Future of Humanity Institute
- RWTH Aachen University
Asia & Pacific
- Tsinghua University AI Institute
- Peking University
- University of Tokyo
- IIT Bombay
- KAIST
- National University of Singapore
Global & Industry Labs
- DeepMind Research
- Google Research
- KAUST
- Sapienza University of Rome
- University of Cape Town
- UNAM Mexico City
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