Sujeet Kumar at Tripura University, India.
Prof. May El Barachi is a Canadian computer scientist and seasoned academic leader known for her transformative impact on education, research, and innovation. She is currently a Full Professor and Head of the School of Computer Science at the University of Wollongong in Dubai. Over her 15+ year career, she has secured over 5 million AED in research funding, published 110+ high-impact papers, and built a global network of collaborations across academia and industry. Her work bridges cutting-edge AI research with real-world applications in smart systems and sustainable development. A passionate advocate for diversity, inclusion, and lifelong learning, she holds a UAE Golden Visa and is fluent in English, Arabic, and French.
Publication Profile
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Education
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Ph.D. in Computer Science, Concordia University, Montréal, Canada (2004–2009)
Specialization: Next Generation Networks, Service Engineering, Network Intelligence and Adaptation
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M.A.Sc. in Electrical and Computer Engineering, Concordia University, Montréal, Canada (2002–2004)
Specialization: Web Services, IP Telephony, Multimedia Communications
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B.Sc. in Electronics and Communication Engineering, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt (1995–2000)
Graduated Valedictorian with Honors; Specialization in Object Recognition, Remote Sensing, and Neural Networks
Professional Experience
Prof. May El Barachi is a visionary academic leader and full professor of Computer Science with over 15 years of experience across the UAE, Canada, and Europe. She currently serves as the Head of the School of Computer Science at the University of Wollongong in Dubai (UOWD), where she has led transformational initiatives, including a 400% increase in enrollment, the development of innovative Master’s programs in AI and Cybersecurity, and the establishment of a widely recognized Executive Learning Program that has trained over 2,500 professionals.
Previously, she held the roles of Associate Dean of Research and Associate Professor at UOWD, where she restructured research clusters around Sustainable Development Goals, drove multi-million-dirham funding acquisition, and played a pivotal role in Ph.D. program development. At Zayed University, she served as Smart Lab Director and co-founder, pioneering research on smart cities and AI-driven systems, while also leading curriculum development and accreditation efforts. Her earlier experience includes postdoctoral research at the University of Quebec (ETS), and roles in industry-academic collaborations at Ericsson Canada and the Ambient Networks Project in Sweden, focusing on web services, context-aware networks, and next-generation telecom systems.
Research Interests
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Artificial Intelligence and Machine Learning: including deep learning, computer vision, natural language processing (NLP), reinforcement learning, and ethical AI
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Emerging Technologies & Applications: smart cities, smart healthcare systems, autonomous systems, and digital transformation
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Next Generation Networks: context-aware networking, IoT integration, and cloud computing
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Interdisciplinary Innovation: leveraging AI for societal challenges, particularly in sustainable development, cybersecurity, and educational technology
Top Noted Publication
1. Evaluating the Impact of COVID-19 on Multimodal Cargo Transport Performance: A Mixed-Method Study in the UAE Context
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Authors: Rami Aljadiri, Balan Sundarakani, May El Barachi
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Journal: Sustainability
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Volume & Issue: 15(22)
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Article Number: 15703
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Publication Date: November 7, 2023
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DOI: 10.3390/su152215703
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Abstract: This study examines the challenges and opportunities of multimodal cargo transport in the UAE during the COVID-19 pandemic (2020–2022). Utilizing a mixed-method approach, the research involved qualitative interviews with five senior logistics executives and quantitative surveys with 120 participants. Findings indicate a significant relationship between geographical/geopolitical risks and increased shipping costs, emphasizing the need for secure and cost-effective multimodal solutions. The study offers insights for enhancing logistics performance in transit hubs during uncertain times.
2. E2DNE: Energy Efficient Dynamic Network Embedding in Virtualized Wireless Sensor Networks
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Authors: Vahid Maleki Raee, Amin Ebrahimzadeh, Roch H. Glitho, May El Barachi, Fatna Belqasmi
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Journal: IEEE Transactions on Green Communications and Networking
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Volume & Issue: 7(3)
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Pages: 1309–1325
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Publication Year: 2023
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DOI: 10.1109/TGCN.2023.3271230
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Abstract: The paper introduces E2DNE, a novel approach for energy-efficient dynamic network embedding in virtualized wireless sensor networks (VWSNs). By optimizing resource allocation and reducing energy consumption, E2DNE enhances the performance and sustainability of VWSNs, making them more adaptable to varying network demands.
3. Secure Data Access Using Blockchain Technology Through IoT Cloud and Fabric Environment
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Authors: Sangeeta Gupta, Premkumar Chithaluru, May El Barachi, Manoj Kumar
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Journal: Security and Privacy
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Publication Date: November 23, 2023
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DOI: 10.1002/spy2.356
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Abstract: This study addresses the challenges of secure data access in IoT environments by integrating blockchain technology with cloud computing. The proposed framework leverages the Hyperledger Fabric platform to ensure data integrity, confidentiality, and scalability, providing a robust solution for managing IoT data securely.
4. Combining Named Entity Recognition and Emotion Analysis of Tweets for Early Warning of Violent Actions
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Authors: May El Barachi, Sujith Samuel Mathew, Manar AlKhatib
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Conference: 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech)
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Publication Date: July 7–8, 2022
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DOI: 10.23919/SpliTech55088.2022.9854231
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Abstract: The paper presents a proactive framework that combines Named Entity Recognition (NER) and emotion analysis to detect early warning signs of potential violent actions from social media content. By analyzing tweets related to the 2020 US presidential election, the study demonstrates the framework’s effectiveness in identifying negative sentiments associated with specific entities, offering a tool for early intervention strategies.
5. A Green, Energy, and Trust-Aware Multi-Objective Cloud Coalition Formation Approach
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Authors: Souad Hadjres, Fatna Belqasmi, May El Barachi, Nadjia Kara
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Journal: Future Generation Computer Systems
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Volume: 111
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Pages: 52–67
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Publication Date: October 2020
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DOI: 10.1016/j.future.2020.04.030
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Abstract: This research proposes a multi-objective approach for forming cloud coalitions that are energy-efficient and trust-aware. The algorithm considers factors like energy consumption, trust levels among providers, and service quality to form optimal coalitions. Experimental results show improvements in coalition size, provider payoff, and reduced mistrust costs, highlighting the approach’s potential for sustainable cloud computing.
Conclusion
Mr. Sujeet Kumar’s paper on Double Sequence Spaces is a strong contender for a Best Paper Award in a theoretical or mathematical research category. Its specialized and rigorous nature, especially if extended to bi-complex number systems or statistical convergence, makes it well-aligned with academic excellence criteria.
However, to enhance competitiveness:
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Ensure the paper is indexed or published in high-impact journals (e.g., Journal of Mathematical Analysis and Applications, Mathematical Methods in the Applied Sciences).
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Amplify online visibility and articulate real-world applications or theoretical implications more clearly.