Gaurav Mittal | Data Science | Digital Education Tools Award

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Mr. Gaurav Mittal | Data Science | Digital Education Tools Award

Mr. Gaurav Mittal – Manager IT, Thermo fisher Scientific, United States.

Gaurav Mittal is a highly accomplished IT Manager with over 18 years of professional experience driving innovative solutions across diverse industries such as biopharmaceuticals, insurance, fraud detection, and healthcare. Renowned for his strategic vision and technical leadership, Gaurav specializes in data science, AI/ML, cloud platforms, and automation. He currently serves as Manager IT – Data Science at Thermo Fisher Scientific, where he leads the development of high-impact technologies including secure AI agents and ML frameworks. Gaurav is known for his hands-on approach to problem-solving, mentoring, and fostering cross-functional collaboration, consistently aligning technological innovation with business objectives.

Publication Profile

Google Scholar

🎓 Education Background

Gaurav Mittal holds a B.Tech degree in Electronics and Communication (2003–2007), laying the foundation for his career in software engineering and IT innovation. Further advancing his leadership and managerial skills, he earned an MBA in Information and Technology from 2017 to 2019. He is also a Sun Certified Java Programmer and has acquired professional certifications including AWS Cloud Practitioner and Lean Six Sigma Green and Yellow Belts. Gaurav’s educational journey reflects a strong combination of technical expertise and strategic acumen, enabling him to lead and influence in dynamic, fast-paced environments.

💼 Professional Experience

With a career spanning nearly two decades, Gaurav Mittal has held progressive roles in reputed organizations such as Thermo Fisher Scientific, Asurion, Dell Services, Zensar, and Mphasis. As a Manager at Thermo Fisher Scientific since 2022, he spearheads data science and automation initiatives, saving thousands in costs through AI-driven tools and ML model deployment. His past roles include developing intelligent automation scripts, containerized deployments, and predictive utilities using Python, AWS, and TensorFlow. Gaurav has consistently driven value through innovations in security, DevOps, QA automation, and cloud architecture, setting industry benchmarks for IT delivery excellence.

🏆 Awards and Honors

Gaurav Mittal’s contributions have been widely recognized within his organizations. He received the Golden Lever Award – Teams Category for his pivotal role in the “Tosca Validation” project at Thermo Fisher Scientific in Q1 2023. He was also a Finalist for the Golden Lever Award – Individual Category for his development of an “AWS IAM Keys Rotation Utility” the same quarter. These accolades underscore his expertise in regulatory compliance, secure automation, and cross-functional team leadership. His commitment to innovation and quality in IT service delivery continues to earn him accolades across his professional journey.

🔬 Research Focus

Gaurav Mittal’s research and development efforts focus on the intersection of data science, machine learning, and cybersecurity. He has designed and deployed advanced ML models for applications such as email classification using Named Entity Recognition (NER), SQL optimization, and security utilities that align with industry GxP compliance. His work emphasizes “Shift-Left Testing,” white-box techniques, and defect prediction to drive cost-effective quality assurance. Gaurav’s innovations bridge theoretical AI research with real-world implementation in enterprise IT systems, making him a thought leader in deploying AI solutions within secure, large-scale environments.

📌 Conclusion

Gaurav Mittal exemplifies technical leadership, innovation, and cross-domain expertise. From automating QA processes to pioneering ML model deployments and ensuring regulatory compliance, his career reflects a blend of deep technical proficiency and strategic IT vision. With numerous awards, published articles, and a track record of driving measurable outcomes, Gaurav stands as a dynamic professional continually pushing the boundaries of data science and enterprise technology. His role in transforming business operations through smart automation and secure digital frameworks marks him as a leader and visionary in the modern IT landscape.

📚 Publication Highlights

  1. Implementing Email Attachment Security
    Published Year: 2023 | Journal: Secure Systems Review

  2. Time-Cost Effective ML Model Deployment Using AWS Lambda
    Published Year: 2023 | Journal: Cloud AI Innovations

  3. Cracking the Code: Why White-Box Testing is the Key to Better Bug Hunting
    Published Year: 2023 | Journal: Software Test Engineering Journal

  4. Shift-Left Testing Benefits: Reduce Costs and Boost Collaboration
    Published Year: 2022 | Journal: Agile QA Digest

  5. Digital Arrest Scams: Understanding the Rise in Cyber Fraud
    Published Year: 2024 | Journal: Cybersecurity Watch

  6. Unpacking Shift-Left Testing Benefits: Key to Reducing Costs and Boosting Collaboration
    Published Year: 2023 | Journal: DevOps Insights Monthly

  7. Unlocking the Code for Defect Analysis: Moving from Black-Box Testing to White-Box Testing
    Published Year: 2024 | Journal: Software Quality Review

 

Mr. chao zheng | computer science | Best Researcher Award

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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

 

Dr. Abiala Alatise Abiala | Technology | Best Researcher Award

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Dr. Abiala Alatise Abiala | Technology | Best Researcher Award

Dr. Abiala Alatise Abiala, University Lecturer, Tai Solarin University of Education, Ijagun, Ogun State, Nigeria.

Dr. ABIALA, Abiala Alatise is a Nigerian academic and agricultural extension expert with over two decades of experience in teaching, research, and community development. Born in Ogun State, he has dedicated his professional life to advancing agricultural science and rural development through education and innovation. He currently serves as a Lecturer II at Tai Solarin University of Education, Ogun State. A multi-talented individual, Dr. Abiala has also made significant impacts in religious, civic, and youth empowerment circles. His commitment to integrating artificial intelligence in agricultural education marks a significant stride in enhancing food security and sustainability in West Africa.

Publication Profile

ORCID

🎓 Education Background

Dr. Abiala holds a Ph.D. in Agricultural Extension from Tai Solarin University of Education (2024), an M.Sc. in Agricultural Extension and Rural Development from the University of Ibadan (2009), and a B.Ed. in Agricultural Science Education from the same university (2004). His academic journey began at African Primary School and Owode Secondary School in Ogun State. He has continuously advanced his professional capacity through specialized certificates in AI integration, copywriting, STEM pedagogy, and theology, reflecting his interdisciplinary approach to education, technology, and spiritual leadership in the evolving academic and development landscape of Nigeria.

👨‍🏫 Professional Experience

Dr. Abiala has held various educational and administrative roles, including Lecturer II at Tai Solarin University of Education since 2025. He previously served as a Science Teacher at Idomila Comprehensive High School (2017–2024), Assistant Lecturer at Ekiti State University (2011–2017), and Subject Teacher at Obanta Comprehensive High School (2007–2017). His early career included administrative duties at TASUED and NYSC service in Anambra State. Through these roles, he has mentored students, facilitated curriculum development, and promoted agricultural practices, earning a reputation for academic diligence and passion for rural development.

🏅 Awards and Honors

Dr. Abiala’s scholarly excellence has been recognized globally. He received the prestigious CORAF Travel Grant (Togo, 2023) and three Society for Conservation Biology Travel Grants for academic activities in Canada, China, and New Zealand between 2009 and 2011. These awards underscore his contributions to agricultural sustainability and biodiversity conservation. His certification as a Microsoft Innovative Educator Expert and participation in World Bank’s ToT in STEM reflect his leadership in educational innovation. These accolades not only celebrate his academic achievements but also support his mission to bridge the gap between research, community empowerment, and technological integration.

🔬 Research Focus

Dr. Abiala’s research focuses on agricultural extension, food security, youth empowerment, and sustainable farming systems in Nigeria. His Ph.D. work examined the impact of the Anchor Borrowers’ Programme on rice farmers’ poverty levels. His studies also investigate agricultural technology use, snail farming, charcoal utilization, and the socio-economic dimensions of agri-business. With interdisciplinary outputs spanning newspapers, environmental conservation, and rural livelihoods, he contributes to both academic literature and policy discourse. He integrates AI and modern pedagogies into agriculture, positioning his research at the intersection of education, technology, and sustainable development in West Africa.

🧾 Conclusion

Dr. ABIALA, Abiala Alatise exemplifies a well-rounded scholar, educator, and community leader committed to agricultural transformation and educational excellence in Nigeria. With a strong foundation in extension services and educational innovation, he actively supports the application of modern technology for sustainable rural development. His publications, global exposure, and community involvement reflect a visionary academic whose contributions continue to inspire change across multiple sectors. Whether in the classroom, research arena, or religious setting, Dr. Abiala brings purpose, leadership, and transformative impact.

📚 Top Publications with Notes

  1. Assessment of Local Processing, Packaging and Storage Among Rice Processors in Southwestern Nigeria
    Banjo, S. et al., MDPI Proceedings, 2025
    Cited by: 12 articles
    ➤ A detailed analysis of value-chain improvements in rice processing for food security and trade.

  2. Effects of Agricultural and Technology Usage on the Genetic Selection and Climate Resilience of Fish Farming in Oyo State
    Sanni, M.A. et al., Journal of Theoretical and Empirical Studies in Education, 2025
    Cited by: 8 articles
    ➤ Investigates tech integration in aquaculture for sustainable fishery practices.

  3. Socio-economic Impact of Snail Production and Youth Engagement
    Asamu, Y.I. et al., Journal of Molluscan Research, 2025
    Cited by: 9 articles
    ➤ Highlights the economic potential of snail farming for youth job creation.

  4. Snail Farming as a Means of Wealth Creation in Ogun State
    Jolayemi, J.O. et al., Journal of Molluscan Research, 2025
    Cited by: 5 articles
    ➤ Focuses on value-added practices and entrepreneurship in molluscan farming.

  5. Impact of Anchor Borrowers’ Programme on Smallholder Rice Farmers’ Income
    Banjo, O.S. et al., CYIAP Journal, 2023
    Cited by: 13 articles
    ➤ Examines policy impact on rural rice farmers’ financial stability.

  6. Contribution of NIRSAL to Rice Farmers’ Productivity
    Abiala, A.A. et al., Journal of Agricultural Education Teachers, 2023
    Cited by: 11 articles
    ➤ Links institutional support to yield increase and food security outcomes.

  7. Medicinal Uses of Snail Meat for Boosting Agribusiness
    Oladele, M.N. et al., NMS Conference Proceedings, 2024
    Cited by: 6 articles
    ➤ Presents ethnobotanical insights into snail meat for health-focused agribusiness.

  8. The Impact of Palm Kernel Cake in Resolving Herdsmen-Farmers Conflicts
    Abiala, A.A., IGI Global Journal, 2019
    Cited by: 15 articles
    ➤ Proposes agribusiness solutions to mitigate agricultural land conflicts.

  9. Plant Conservation: Political Harmony for Nature and Society
    Abiala, A.A., Society for Conservation Biology Journal, 2009
    Cited by: 10 articles
    ➤ Connects environmental policy with biodiversity conservation strategies.

  10. Religious Tolerance and Environmental Conservation
    Abiala, A.A., Obeche Journal, 2008
    Cited by: 7 articles
    ➤ Discusses how religious cooperation enhances ecological preservation efforts.

 

Zhe PENG | Data Analytics | Best Researcher Award

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Prof. Zhe PENG | Analytics | Best Researcher Award

Assistant Professor, The Hong Kong Polytechnic University, Hong Kong

Dr. Zhe Peng  is a dedicated Research Assistant Professor at the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. With a strong background in computer science and engineering, he specializes in intelligent supply chains, AI for manufacturing, and blockchain technologies. His contributions to blockchain, federated learning, and decentralized identity systems have earned him global recognition. With extensive academic and industry experience, Dr. Peng has made a significant impact on cutting-edge technological advancements.

Publication Profile

🎓 Education

Dr. Peng holds a Ph.D. in Computer Science from The Hong Kong Polytechnic University (2018), under the supervision of Prof. Bin Xiao (IEEE Fellow). He earned his M.E. in Information and Communication Engineering from the University of Science and Technology of China (2013) and a B.E. in Communication Engineering from Northwestern Polytechnical University (2010). His academic journey reflects his deep expertise in computing, communication, and AI-driven systems.

💼 Experience

Dr. Peng has held multiple research and industry positions. He is currently a Research Assistant Professor at The Hong Kong Polytechnic University. Previously, he served as a Research Assistant Professor at Hong Kong Baptist University (2020-2023) and as an R&D Manager at the Blockchain and FinTech Lab. In the industry, he worked as the Blockchain Technical Director at SF Technology in Shenzhen (2018-2019). Additionally, he was a Visiting Scholar at Stony Brook University, USA, working under Distinguished Prof. Yuanyuan Yang (IEEE Fellow).

🏆 Awards and Honors

Dr. Peng has received several prestigious awards, including the World’s Top 2% Scientists by Stanford University (2024) and the Award for High SFQ Score at PolyU ISE (2024). He was recognized with an ESI Highly Cited Paper (2023) and received the DASFAA-MUST Best Paper Award (2021). His work was also nominated for THE Awards Asia – Technological or Digital Innovation of the Year (2021). His numerous accolades highlight his contributions to academia, research, and technological innovation.

🔬 Research Focus

Dr. Peng’s research revolves around intelligent supply chains, AI-driven manufacturing, blockchain applications, and autonomous systems. His work on verifiable decentralized identity management, privacy-aware federated learning, and blockchain security has set new benchmarks in these fields. He continues to explore innovative solutions to improve efficiency, transparency, and security in digital ecosystems.

🔚 Conclusion

Dr. Zhe Peng is a visionary researcher at the intersection of AI, blockchain, and smart logistics. His groundbreaking research, academic excellence, and industry experience make him a leading expert in his field. Through his contributions to intelligent systems, federated learning, and blockchain security, he continues to shape the future of technological innovation. 🚀

🔗 Publications 

Lightweight Multimodal Defect Detection at the Edge via Cross-Modal Distillation

VDID: Blockchain-Enabled Verifiable Decentralized Identity Management for Web 3.0 

SymmeProof: Compact Zero-Knowledge Argument for Blockchain Confidential Transactions 

The Impact of Life Cycle Assessment Database Selection on Embodied Carbon Estimation of Buildings 

EPAR: An Efficient and Privacy-Aware Augmented Reality Framework for Indoor Location-Based Services

VFChain: Enabling Verifiable and Auditable Federated Learning via Blockchain Systems 

VQL: Efficient and Verifiable Cloud Query Services for Blockchain Systems 

Rania Sefti | Data Science | Best Researcher Award

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Ms. Rania Sefti | Data Science | Best Researcher Award

Phd student, Université Mohammed Premier Oujda, Morocco

Sefti Rania is a passionate researcher specializing in numerical analysis, optimization, and image processing. With a robust academic background and extensive teaching experience, she is currently pursuing a Ph.D. in a joint program between Morocco and France. Her research focuses on developing advanced methods for medical image segmentation using deep learning techniques.

Profile

Scopus

 

Education 🎓

Ph.D. in Mathematics and Computer Science (Specialization: Numerical Analysis and Optimization, Image Processing, Deep Learning), Mohammed First University, Oujda, Morocco, University of Orleans, France (Since 2020). Master in Numerical Analysis and Optimization (Honors: Good), Mohammed First University, Oujda, Morocco (2019). Bachelor’s Degree in Mathematical Sciences and Applications (Honors: Fairly Good), Mohammed First University, Oujda, Morocco (2017). High School Diploma in Experimental Sciences (Honors: Good), Ibn El Haytam High School, Nador, Morocco (2012)

Experience 💼

Adjunct Lecturer at Mohammed First University, Oujda, Morocco (2020 – Present). Higher School of Technology (Specialty: MCT and LPMI). Faculty of Sciences (Specialty: SVT and SMPC). Modules taught include Mathematics and Analysis with a total of over 200 hours of instruction. Reviewer for numerous articles in Mathematics and Computer Science since 2022

Research Interests 🔬

Numerical Analysis and Optimization, Image Processing, Deep Learning, Medical Image Segmentation.

Awards 🏆

Numerous Publications in renowned journals and conferences in the field of numerical analysis and optimization. Presentation Awards for contributions at international conferences such as MACMAS, NT2A, and SMAI-SIGMA

Publications

A CNN-based spline active surface method with an after-balancing step for 3D medical image segmentation, Mathematics and Computers in Simulation. Link – Cited by:

C2 composite spline methods for fitting data on the sphere, Springer special volume of the SEMA-SIMAI Springer Series. (Accepted in June 2023) – Cited by:

PID-Snake: Progressive Iterative Deformation of a Snake model for segmentation of a variety of images, Journal of Computational and Applied Mathematics. (Submitted in June 2024) – Cited by:

Fine-tuned cubic generalized composite spline interpolation with optimal parameter, Mathematics in Computer Science. (Submitted in June 2024) – Cited by:

A deep network-based spline active contour method for medical image segmentation, Springer special volume of the SEMA-SIMAI Springer Series. (Submitted in 2024) – Cited by: