Welcome to the

Artificial Intelligence Management Institute

" AI will change and transform management models. ADSM supports Abu Dhabi's vision in creating a strong and interdisciplinary AI-related research environment that will benefit the UAE and its society"
President , ADSM

Supporting UAE
AI Strategy 2031

ADSM strives in achieving UAE AI strategy with its Artificial Intelligence Management Institute (AIM).
Rapid advancements in AI create new economic and social opportunities for most organizations in the UAE. ADSM’s AIMI will contribute to develop emerging AI Technology ecosystems to solve complex management problems. The institution will support AI management research, academic programs and training to educate new generations on the crucial role played by AI in business and management.The AIMI will facilitate the creation of a strong and interdisciplinary AI-related research environment beyond Machine Learning and Pattern Analysis. It will stimulate new proposals to answer local and international research calls and foster the creation of flagship AI academic programs for managers. Such initiatives will motivate and provide structure to ADSM faculty in their internal and international research initiatives. The AIMI will seek to create an international network of institutions from both academia and industry to support the management of AI.Students acquiring knowledge towards their life-long learning can especially benefit from ADMS’ unique Business Analytics program. The introduction of program concentrations in Business Analytics and Artificial Intelligence allows students to specialize in their area of interests. Furthermore, the AIMI will offer certificates in AI related topics, which can be fully customizable for the audience needs.

AIMI Overview

The ADSM Artificial Intelligence for Management Institute (AIMI) is a research institute of ADSM located in Abu Dhabi whose main mission focuses on Artificial Intelligence and Analytics.
The AIMI Institute focuses on Artificial Intelligence and Data Analytics techniques for problem-solving and decision-making with applications to a variety of domains, including energy, health, finance, supply chain, and operations. Areas of interest also includes data and information systems, business analytics and data intelligence, machine learning, deep learning, neural networks, interpretable AI, data science, ethics, engineering, and many others. The AIMI Institute fosters the creation of partnerships and joint projects with organisations specialized in AI, analytics, business intelligence solutions or in adapting such solutions, and focuses on the development of tools, algorithms, methodologies, models, and solutions for companies. Beyond internships and job opportunities, the typical outcome of joints projects is the ad-hoc development and implementation of innovative AI models and analytics techniques.The AIMI Institute supports the understanding and the usage of AI and analytics tools through focused conferences, workshops, certificates and seminars. It provides insights and contributes to the debate on the impact of AI methods and technologies through press releases, media coverage and scientific articles.


Dr. Ishtiaq Rasool Khan

Full Professor of Business Analytics, Abu Dhabi School of Management, UAE

Dr. Neda Abdelhamid

Associate Professor of Business Analytics, Abu Dhabi School of Management, UAE

Dr. Evi Mansor

Associate Professor of Business Analytics, Abu Dhabi School of Management, UAE


Prof. Francesco Appio

Full Professor of Artificial Intelligence for Management, Paris School of Business, France

Prof. Enrico Formenti

Full Professor of Computer Science, Université Cote d’Azur, France

Prof. Vassilios Kovanis

Full Professor of Quantum Engineering, Virginia Tech, US

Prof. Davide La Torre

Full Professor of Applied Mathematics and Artificial Intelligence, SKEMA Business School, Université Côte d'Azur, France

Prof. Hatem Masri

Full Professor of Business Analytics, Applied Science University, Kingdom of Bahrain

Prof. Giancarlo Succi

Full Professor of Computer Science, University of Bologna, Italy

Professor Masahiro Okuda

Full Professor, Doshisha University, Japan

Professor Wajid Aziz

Full Professor or Data Analytics, Azad Jammu and Kashmir University, Pakistan


Adam Riccoboni

CEO, Critical Future, UK


Revitalife Compounding Pharmacy, UAE

Marco Repetto

CERTX, Freibourg, Switzerland

Dr. Naveed Afzal

Director of Data Science and Analytics, and Global head of Cybersecurity Analytics, Takeda, USA.

Main Research

Machine Learning Applications Medical Images’ Quality Assessment

Accurate evaluation of medical image quality is indispensable for ensuring reliable diagnosis. However, subjective assessments often require substantial time and expertise, making them impractical in many clinical settings. Consequently, there has been a growing interest among researchers in developing objective metrics aligned with medical standards and evaluation by medical professionals. In our approach, we extract a range of features from medical images and assess their effectiveness and relevance in determining image quality. These features encompass various aspects such as information quantity (entropy), structural intensities, and gradients. Leveraging these features, we train machine learning models capable of assessing image quality accurately. These trained models can serve as valuable tools for assisting medical professionals. They can be used to swiftly evaluate the quality of new images, which can lead to development of better algorithms for medical image formation and enhancement, and ultimately aid in more precise medical diagnoses.

Role of Artificial Intelligence in the Enabling Sustainable Supply Chain Management during Pandemics, Disruption, and Resilience

AI and ML tools have had a great impact on supply chain from different perspectives. Advantages to applying AI to modern supply chain challenges include: end-to-end visibility enhanced with near real-time data, actionable analytic insights based on pattern identification, reduced manual human work,  informed decision making augmented by machine learning, AI-driven predictions and recommendations, accurate demand forecasting and warehouse supply and demand management, routing efficiency and delivery logistics, health and longevity of transportation vehicles, efficiency and profitability of loading processes, cost-saving and revenue-increasing methods.

Neural Network Architecture for Financial Forecasting

The development of machine learning based models to predict the movement of a financial market has been a challenging problem due to the low signal-to-noise ratio under the effect of an efficient market. This project focuses on new neural architectures for the movement prediction of stock market indices using technical indicators as inputs. The new proposed approach formulates the neural architecture search as a multi-criteria optimization problem to balance the efficacy with the complexity of architectures.

Machine Learning Algorithms for Electricity Forecasting

Large-scale data analysis is growing at an exponential rate as data proliferates in our societies. This abundance of data has the advantage of allowing the decision-maker to implement complex models in scenarios that were prohibitive before. At the same time, such an amount of data requires a distributed thinking approach. In fact, Deep Learning models require plenty of resources, and distributed training is needed. We propose a Multicriteria approach for distributed learning. This project focuses on new  Deep Learning approach in electricity demand forecasting.

Federated Machine Learning with Multiple Datasets in Cancer Detection and Prediction

Cancer detection has been improved using a variety of Machine Learning and Deep Learning techniques. Federated Learning is a distributed learning technique that allows models to be trained on a vast set of decentralized data. This project focuses on a new Multiple Criteria Optimization approach for Federated Learning. Numerical experiments also demonstrate the efficacy of this strategy in terms of performance and accuracy.

Certificates and

The AIMI Institute at ADSM School of Management offers training in AI for Management and any related domains. Each of the following program can be customized on specific applications of AI to different domains.

Executive Certificate in AI for Business

Executive Certificate in AI for Healthcare and Medicine

Executive Certificate in AI for Finance

Executive Certificate in AI for Supply Chain Management


Driving technology for leading brands


Artificial Intelligence Technologies

This workshop will introduce AI concepts, how it can help managers, and how to deploy AI in organizations. It will cover machine learning, ethics, risks, and explainability. Participants will learn how to create effective strategies and how customer profiling can prolong customer lifecycles. Industry leaders will share insights on how AI is revolutionizing business. ADSM will also introduce its AI Management Institute.

22 Jun


Get In touch

Submit your industry problem.

+971 2 691 7811

available from 09:00 – 18:00

P.O. Box 6844
Abu Dhabi, United Arab Emirates

Email aimi@adsm.ac.ae

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