Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

Dr. Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

Dr. Hisham AbouGrad , Senior Lecturer , University of East London – UEL , United Kingdom.

Dr. Hisham AbouGrad is a dynamic academic and industry expert in computer science and digital technologies. Currently a Senior Lecturer at the University of East London, he brings over two decades of experience in higher education and IT. Known for bridging theory with practice, he has supervised innovative projects in AI, FinTech, and mobile app development. Dr. AbouGrad also leads international academic collaborations and contributes to top-tier journals. He is a Fellow of the Higher Education Academy and an active member of the British Computer Society, with a passion for enhancing digital learning, scientific problem-solving, and sustainable technology.

Publication Profile

Scopus

ORCID

Google scholar

🎓 Education Background

Dr. Hisham AbouGrad earned his Doctorate in Professional Studies (DProf) from London South Bank University, focusing on Workflow Information Systems Performance using BPM methodologies. He also holds a Master of Science (MSc) in Software Engineering from the University of Bradford and a Master of Business Administration (MBA) in Management from the University of Lincoln. Additionally, he completed a Postgraduate Certificate in Higher Education Practice (PGCHEP) from the University of Plymouth. His academic credentials are enhanced by certifications in project management and IT, including CITP from BCS and PMP qualifications, reinforcing his foundation in both pedagogy and technical leadership.

💼 Professional Experience

Dr. AbouGrad’s career spans prestigious academic institutions and industry roles. Since 2021, he has served as a Senior Lecturer at the University of East London, where he also fosters international collaborations. Previously, he held teaching and leadership roles at ICON College, QA Higher Education, GSM London, and the University of Plymouth. From 2011 to 2019, he was a doctoral researcher at London South Bank University. With vast teaching experience in computing, business management, and information systems, Dr. AbouGrad has mentored numerous PhD and DProf students while shaping curricula aligned with technological advancements and practical industry applications.

🏆 Awards and Honors

Dr. Hisham AbouGrad has been recognized for his commitment to academic excellence and professional contribution. He is a Fellow of the UK Higher Education Academy (FHEA), a Certified IT Professional (CITP) with the British Computer Society (BCS), and has received qualifications in IT Quality Management (ITQM). He is a founding member of UEL’s FinTech Centre and contributes actively to academic committees and journal editorial boards. As a reviewer for reputed journals like IEEE TCE, SAGE, Elsevier, and Emerald, he consistently upholds research quality, earning professional credibility and trust in the global academic and scientific communities.

🔬 Research Focus

Dr. AbouGrad’s research integrates Artificial Intelligence, FinTech, Machine Learning, Information Security, and Multi-Criteria Decision Making (MCDM) with Business Process Management (BPM) and Workflow Systems. His work aims to create scalable, secure, and intelligent digital solutions. Projects under his supervision include AI-based financial prediction systems, eCommerce fraud detection using neural networks, and mobile payment technologies. His recent studies explore AI-driven stock prediction, sentiment analysis, and fake review detection—highlighting his goal to solve real-world problems through data science, machine learning, and performance analysis. He also researches Decision Support Systems (DSS), ECM, GIS, and user-centered eCommerce design.

🔚 Conclusion

Dr. Hisham AbouGrad is a passionate educator, strategic researcher, and technology advocate whose career is marked by innovation, collaboration, and impact. His multifaceted expertise across academia and industry supports students, institutions, and global communities in adapting to digital transformation. Through research, mentorship, and leadership, he contributes to solving complex challenges in AI, FinTech, and Information Systems. With a forward-thinking mindset, he continues to influence academic practices, elevate IT performance, and foster global academic relationships. His legacy reflects both the rigor of scholarly inquiry and the relevance of applied science in the 21st century.

📚 Top Publications with Details

  1. AI-Framework to Detect eCommerce Fake Reviews: A Hybrid Neural Network Machine Learning Model
    Published: 2024, Book: Artificial Intelligence and Computational Technologies
    Cited by: 1

  2. Financial Decision-Making AI-Framework to Predict Stock Price Using LSTM Algorithm and NLP-Driven Sentiment Analysis Model
    Published: 2025, Conference: Annual International Congress on Computer Science
    Cited by: 1

  3. Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks
    Published: 2023, Conference: International Conference on Deep Learning, Artificial Intelligence and Robotics
    Cited by: 5

  4. Developing the Business Process Management Performance of an Information System Using the Delphi Study Technique
    Published: 2019, Conference: EAI International Conference on Technology, Innovation, Entrepreneurship and Education
    Cited by: 5

  5. Applying the Delphi Method to Measure Enterprise Content Management Workflow System Performance
    Published: 2022, Journal: Lecture Notes in Networks and Systems (Springer)
    Cited by: 1

  6. The Impact of Business Process Management Values on Enterprise Content Management Workflow Systems Performance
    Published: 2020, Thesis: London South Bank University
    Cited by: 1

  7. Intelligent Computing, Proceedings of the 2022 Computing Conference
    Published: 2022, Publisher: Springer International Publishing
    Cited by: 23

  8. Key Digital Trends in Artificial Intelligence and Robotics: Proceedings of ICDLAIR 2022
    Published: 2023, Publisher: Springer International Publishing
    Cited by: 1

 

Mr. chao zheng | computer science | Best Researcher Award

Mr. chao zheng | computer science | Best Researcher Award

Mr. chao zheng, manager, tencent, China.

Chao Zhen is a leading researcher in computer vision and artificial intelligence, currently heading the Computer Vision Research team at Tencent Map. He is widely recognized for his expertise in autonomous driving and machine perception. Over the years, he has driven innovation in 3D perception and semantic understanding within autonomous systems. His work regularly appears in prestigious conferences such as AAAI, ICCV, ECCV, and WACV. With a growing impact in AI and computer vision, he continues to push the boundaries of real-world applications. His collaborative research has earned accolades like the IAAI Application Innovation Award.

Publication Profile

Scopus

Google Scholar

🎓 Education Background

Chao Zhen holds a solid academic foundation in artificial intelligence and computer vision. While specific institutional details of his degrees are not publicly listed, his prolific publication record in high-impact conferences like ICCV, ECCV, and AAAI indicates deep formal training, likely at top-tier universities or research institutes. His education has equipped him with advanced theoretical and practical knowledge in machine learning, 3D scene understanding, and multimodal AI—forming the cornerstone of his success in autonomous driving research. Through continuous learning and collaboration, he has established himself as a technical leader in AI and robotics.

💼 Professional Experience

Chao Zhen currently leads the Computer Vision Research team at Tencent Map, focusing on enabling intelligent mapping and scene understanding for autonomous vehicles. His professional journey spans several years of active involvement in cutting-edge research and development of AI-powered vision systems. Under his leadership, the team contributes to next-gen perception modules and vision-language systems for driving environments. He actively collaborates with academic and industrial partners, guiding projects from prototype to deployment. His role integrates both technical depth and strategic foresight in aligning AI research with scalable real-world applications.

🏆 Awards and Honors

Chao Zhen’s outstanding contributions have been recognized with several prestigious honors, most notably the IAAI Application Innovation Award, awarded for impactful AI-driven applications. His co-authored work has gained traction in premier AI and computer vision conferences, a testament to its relevance and innovation. These accolades highlight his contributions to advancing practical autonomous driving solutions using sophisticated machine perception models. Beyond awards, his publications continue to receive high citation counts, reflecting his influence in the research community and his pivotal role in shaping the future of AI-driven transportation systems.

🔬 Research Focus

Chao Zhen’s research centers around artificial intelligence, computer vision, and machine learning, with a strong focus on 3D perception and reconstruction for autonomous driving. His work bridges data-driven learning techniques with real-world challenges, such as lidar-based segmentation, topological reasoning, and vision-language integration. He explores multimodal systems that combine point cloud data, semantic maps, and language to build robust scene understanding. Through projects like MapLM and 2DPASS, he advances scalable solutions for urban mobility. His innovations pave the way for safer, smarter, and more interpretable autonomous systems leveraging the synergy of AI modalities.

📌 Conclusion

Chao Zhen stands out as a forward-thinking AI researcher and industry leader in the realm of autonomous driving. His innovative vision and commitment to research excellence have resulted in influential publications, impactful industry contributions, and prestigious recognitions. By fusing deep technical insights with real-world needs, he is helping shape the next generation of intelligent vehicles. His ongoing efforts in 3D scene understanding, multimodal AI, and semantic modeling are not only transforming how machines perceive the world but also driving the future of intelligent transportation.

📚 Top Publications Notes

  1. A Survey on Multimodal Large Language Models for Autonomous Driving
    Year: 2024
    Journal/Conference: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
    Cited by: 426 articles

  2. 2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
    Year: 2022
    Journal/Conference: European Conference on Computer Vision (ECCV)
    Cited by: 326 articles

  3. MapLM: A Real-World Large-Scale Vision-Language Dataset for Map and Traffic Scene Understanding
    Year: 2024
    Journal/Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    Cited by: 10 articles

  4. MapLM Benchmark: Real-World Vision-Language Benchmark for Traffic Scene Understanding
    Year: 2024
    Journal/Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    Cited by: 35 articles

  5. RelTopo: Enhancing Relational Modeling for Driving Scene Topology Reasoning
    Year: 2025
    Journal: arXiv preprint
    Cited by: In press (citation data to be updated)

  6. Cross-Modal Semantic Transfer for Point Cloud Semantic Segmentation
    Year: 2025
    Journal: ISPRS Journal of Photogrammetry and Remote Sensing
    Cited by: 1 article

  7. Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning
    Year: 2025
    Journal: arXiv preprint
    Cited by: 1 article

  8. Position: Autonomous Driving & Multimodal LLMs
    Year: 2025
    Journal: Winter Conference on Applications of Computer Vision (WACV)
    Cited by: 8 articles