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

 

Dr. Jiaheng Peng | Data Science | Best Researcher Award

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Dr. Jiaheng Peng | Data Science | Best Researcher Award

PhD Candidate, East China Normal University, China

Jiaheng Peng is a dedicated Ph.D. candidate at East China Normal University, specializing in Open Source Ecosystem, Natural Language Processing, and Evaluation Science. With a strong academic record and a passion for research, he has contributed significantly to understanding Open Source dataset evaluation. His work bridges the gap between academic research and real-world Open Source applications, earning him recognition in the field.

Publication Profile

Google Scholar

🎓 Academic Background

Jiaheng Peng is pursuing his Ph.D. at East China Normal University, focusing on innovative methods to assess Open Source datasets. His research emphasizes citation network analysis, evaluating long-term dataset usage, and developing advanced Natural Language Processing (NLP) models. His academic journey is marked by high-impact publications in top-tier journals and international conferences, reflecting his expertise in computational analysis and data evaluation.

👨‍💼 Professional Experience

Although Jiaheng does not have industry consultancy or ongoing research projects, his scholarly contributions have made a substantial impact on Open Source ecosystem analysis. He actively publishes in high-impact scientific journals and conferences, ensuring that his findings help enhance dataset evaluation metrics. His commitment to advancing data-driven methodologies sets a solid foundation for future research in Open Source analysis.

🏆 Awards and Honors

Jiaheng Peng’s research excellence has been acknowledged with the Best Paper Award at the 1st Open Source Technology Academic Conference (2024). His publications in Q1-ranked journals further highlight his academic impact. His continuous contributions to the Open Source community demonstrate his dedication to advancing research and innovation in Open Source evaluation.

🔬 Research Focus

Jiaheng’s research primarily addresses the limitations of traditional Open Source data insight metrics. His work connects Open Source datasets with their corresponding academic papers, evaluating their significance through citation network mining. By bridging Open Source data with academic insights, he introduces novel evaluation methodologies that enhance dataset usability and long-term impact analysis. His research also extends into Aspect-Based Sentiment Classification, employing advanced Graph Attention Networks and NLP models to extract meaningful insights.

📌 Conclusion

Jiaheng Peng is a rising scholar in the Open Source and NLP domains, with a keen focus on dataset evaluation, citation network analysis, and sentiment classification. His academic contributions, recognized through prestigious awards and top-tier publications, establish him as a promising researcher dedicated to advancing Open Source dataset analytics. With a commitment to scientific excellence, his work continues to influence the global research community.

📚 Publication Top Notes

Evaluating long-term usage patterns of open source datasets: A citation network approach
BenchCouncil Transactions on Benchmarks, Standards and Evaluations (2025)
Cited by: Pending

DRGAT: Dual-relational graph attention networks for aspect-based sentiment classification
Information Sciences (2024)
Cited by: Pending

Data Driven Visualized Analysis: Visualizing Global Trends of GitHub Developers with Fine-Grained Geo-Details
International Conference on Database Systems for Advanced Applications (2024)
Cited by: Pending

ASK-RoBERTa: A pretraining model for aspect-based sentiment classification via sentiment knowledge mining”
Knowledge-Based Systems (2022)
Cited by: Multiple researchers in NLP and sentiment analysis

Prof. Dr. Hamid Arabnia | Data Science | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Dr. Hamid Arabnia | Data Science | Best Researcher Award

Professor Emeritus, University of Georgia, United States

Dr. Hamid R. Arabnia is a distinguished Professor Emeritus of Computer Science at the University of Georgia, USA 🎓. With a Ph.D. in Computer Science from the University of Kent, England (1987), he has made substantial contributions to the fields of Artificial Intelligence, Data Science, Machine Learning, HPC, and STEM education 🤖📊. Over his career, he has mentored 23 Ph.D. students and played a vital role in advancing computational science and intelligence. He has been an active advocate against cyber-harassment and cyberbullying, winning a landmark lawsuit in 2017–2018, securing a $3 million ruling ⚖️. Prof. Arabnia has an extensive publication record with 300+ peer-reviewed papers and 200+ edited research books, establishing himself among the top 2% most impactful scientists, as recognized by Stanford University 🌍📚.

Publication Profile

🎓 Education

Dr. Arabnia earned his Ph.D. in Computer Science from the University of Kent, England (1987) 🏛️. His research during his doctoral studies laid the foundation for his pioneering contributions in supercomputing and artificial intelligence 🤖💡.

💼 Experience

Dr. Arabnia has been with the University of Georgia since 1987, contributing as a Professor, Graduate Coordinator, and Research Director 🏫. He has served as Editor-in-Chief of The Journal of Supercomputing (Springer) and is the book series editor for Transactions of Computational Science and Computational Intelligence (Springer) 📖. His leadership has also extended to roles as a senior adviser for global corporations and National Science Foundation (NSF) committees for over 10 years 🏆.

🏅 Awards and Honors

Prof. Arabnia has received numerous prestigious awards, including recognitions from IEEE BIBE, ACM SIGAPP, and IMCOM 🏅. His legal victory against cyber-harassment was a landmark case, setting an important precedent in the U.S. legal system ⚖️. His contributions to STEM education and securing $12 million in funding for graduate research at UGA have also been widely recognized 💰📚.

🔬 Research Focus

Dr. Arabnia’s research spans Data Science, AI, HPC, Machine Learning, Imaging Science, and Compute-Intensive Problems 🤖📊. He has been actively involved in cybersecurity legislation advocacy, focusing on cyberstalking and online harassment 🔒. His latest work integrates deep learning, upsampling techniques, and AI-driven smart city applications 🌍.

🔚 Conclusion

Dr. Hamid R. Arabnia is a highly influential researcher, educator, and advocate for ethical AI and cybersecurity 🏆. With over 500 publications and millions in research funding, his contributions have shaped modern supercomputing, artificial intelligence, and digital security 🔬. Recognized among the top 2% impactful scientists globally, his work continues to inspire the next generation of AI and computer science researchers 🚀.

📚 Publications

Comprehensive Analysis of Random Forest and XGBoost Performance with SMOTE, ADASYN, and GNUS Upsampling under Varying Imbalance Levels (2025) – Preprint

A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection (2025) – Technologies | DOI 📑

SWAG: A Novel Neural Network Architecture Leveraging Polynomial Activation Functions for Enhanced Deep Learning Efficiency (2024) – IEEE Access | DOI 📖

Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis (2023) – Technologies | DOI 📜

A Review of Deep Transfer Learning and Recent Advancements (2023) – Technologies | DOI 📘

Embodied AI-Driven Operation of Smart Cities: A Concise Review (2021) – TechRxiv | DOI 🌍

Md. Emran Biswas | Data science | Best Researcher Award

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Mr. Md. Emran Biswas | Data science | Best Researcher Award

Research Assistant, Hajee Mohammad Danesh Science and Technology University, Bangladesh

🌟 Md. Emran Biswas, hailing from Dinajpur, Bangladesh, is a passionate researcher and technologist specializing in machine learning, optimization algorithms, and their societal applications. He has actively contributed to predictive analysis, bioinformatics-based drug discovery, and developing AI solutions for global good. As a skilled programmer and researcher, Emran’s work has earned recognition through multiple publications, accolades, and groundbreaking projects in his field.

Publication Profile

Scopus

Education

🎓 Md. Emran Biswas completed his B.Sc. in Electronics and Communication Engineering at Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh, from March 2019 to November 2024, with an impressive CGPA of 3.412/4.00. His academic journey is marked by a focus on deep learning, predictive modeling, and optimization algorithms.

Experience

💼 Emran served as a Research Assistant at Petarhub and DIOT Lab, HSTU, contributing to machine learning, predictive modeling, and optimization projects. His notable achievements include developing the ApexBoost Regression model, managing large datasets, and publishing impactful research in reputed journals like IEEE and Electronics.

Research Interests

🔍 Emran’s research focuses on machine learning, optimization algorithms, and their transformative applications in areas like bioinformatics-based drug discovery, predictive analysis, and societal challenges. His work aligns with the vision of ‘AI for Good,’ driving impactful innovation.

Awards

🏆 Emran has earned recognition for his innovative projects, including First Runner-Up at the Project Exhibition 2022 for his “Face Detection-Based Attendance System” and Second Runner-Up in 2023 for his “AI-Based Health Checking System.” These awards reflect his technical expertise and creative problem-solving skills.

Publications

Machine Learning Approach to Estimate Requirements for Target Productivity of Garments Employees. IEEE ICEEICT 2024 (Cited by: 5)

An Effective Data-Driven Approach to Predict Bike Rental Demand. Google Scholar (Cited by: 12)

Spatio-Temporal Feature Engineering and Selection-Based Flight Arrival Delay Prediction Using Deep Feedforward Regression Network. Electronics, 13(24), p.4910 (Cited by: 9)