Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award-7820

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Mr. Shishir Tewari | AI/ML | Corporate Leadership Excellence Award

Mr. Shishir Tewari | Computer Science – Senior Manager at Procore Technologies, United States

Shishir Tewari is a distinguished technology leader and Senior Engineering Manager, renowned for his pioneering work in data engineering, AI/ML, and business intelligence systems. With a professional journey spanning nearly two decades, he has made significant contributions to building robust data platforms, streamlining enterprise analytics, and mentoring high-performing engineering teams across some of the world’s top tech firms including Google, Amazon, and Procore Technologies. His forward-thinking approach to intelligent data infrastructure, combined with his proficiency in cloud ecosystems and scalable processing frameworks, has set new benchmarks in operational excellence and digital innovation. Tewari stands out as a forward-thinking engineer and strategic visionary who continuously transforms data into actionable intelligence.

✅🧑‍💼 Professional Profile Verified

Google Scholar

🎓 Education

Tewari’s strong academic foundation has enabled his seamless navigation through complex data and technology landscapes. He earned his Bachelor of Technology degree in Information Technology from U.P.T.U., India (2002–2006), graduating with a commendable performance. To further specialize in the burgeoning field of analytics, he pursued a Data Science and Analytics specialization at Rutgers University, New Jersey (2018–2019). This academic combination has empowered him to integrate advanced analytical methodologies with practical problem-solving in enterprise settings, giving him a competitive edge in today’s data-centric economy.

💼 Experience

With more than 19 years of hands-on experience, Shishir Tewari has held progressively senior roles at globally respected organizations. At Procore Technologies, where he currently serves as Senior Manager, Data Engineering, he led the development of a next-gen Master Data Management and Marketing Analytics platform enriched by AI/ML, enhancing organizational data consistency and insight. Previously at Google, he managed a global team and optimized financial data processing pipelines across Google Finance, handling 100+ petabytes on GCP. His role at Amazon involved constructing large-scale advertising data infrastructure in AWS, directly supporting over $100M in revenue. During his earlier years at Morgan Stanley, JP Morgan Chase, Panasonic, and Tata Consultancy Services, Tewari built scalable ETL pipelines, optimized legacy systems, and created advanced business intelligence frameworks. Each of these roles reflects his unwavering commitment to excellence in data operations, architecture, and leadership.

🔬 Research Interest

Tewari’s research interests lie at the intersection of data engineering, artificial intelligence, and automation. He is particularly passionate about leveraging machine learning to optimize data quality, processing, and decision-making at enterprise scale. His work focuses on improving the performance of large-scale distributed systems, integrating data governance frameworks, and implementing real-time analytics. He is equally invested in enhancing business intelligence solutions through AI-driven innovation, and his hands-on experience with platforms like AWS, GCP, and Databricks has empowered him to experiment with scalable applications of AI in modern enterprises.

🏆 Awards

Shishir Tewari’s groundbreaking work has been recognized globally through several prestigious awards. He received the 2025 Global Leader Award for Excellence in AI/ML-Driven Data Engineering, honoring his transformative contributions to intelligent automation. In 2024, he was the recipient of the ISTRA International Outstanding Technical/Digital Innovation Award for his role in driving technical innovation in AI and Data Engineering. He also earned the 2025 TITAN Business Awards – Gold Winner title in the Artificial Intelligence category for his strategic leadership and engineering excellence. Further recognition came with his inclusion in the Marquis Who’s Who Biographical Listee, highlighting his impact on global technological advancement.

📚 Publications

Tewari has made valuable scholarly contributions to the AI and data engineering community through multiple publications that reflect his expertise and thought leadership. His book, “AI-Driven Enterprise: Scaling Business Success” (2024), offers insightful frameworks for integrating AI into business operations and is available on Amazon. He has authored/co-authored 7 peer-reviewed articles, collectively cited 30 times, underscoring his influence in the academic domain. Selected key publications include:

  • “AI-Driven Master Data Governance for Enterprise Systems” 📘 (2023, Journal of Data Science), cited by 6
  • “Optimizing Cloud Data Warehouses Using ML Models” ☁️ (2023, Big Data Research), cited by 5
  • “Real-Time Analytics in Distributed Finance Systems” 💹 (2022, Financial Computing Review), cited by 4
  • “AI-Powered Marketing Insights Platform: A Scalable Framework” 📊 (2021, International Journal of AI and Data), cited by 6
  • “Data Lakehouse Implementation and Business Impact” 🌊 (2021, Information Systems Journal), cited by 3
  • “Ethical AI in Data Engineering” 🧠 (2020, Journal of Ethics in Technology), cited by 4
  • “Performance Engineering for ETL Pipelines Using Spark” 🔥 (2019, Data Engineering Review), cited by 2

These publications reflect his practical insight into enterprise data systems and his commitment to bridging theoretical research with real-world engineering applications.

✅ Conclusion

In conclusion, Shishir Tewari exemplifies excellence in data engineering, AI/ML innovation, and digital transformation leadership. His visionary mindset, technical expertise, and consistent delivery of impactful solutions have earned him a well-respected place among global leaders in technology. Whether architecting petabyte-scale infrastructures, mentoring next-generation engineers, or judging international innovation awards, Tewari’s work consistently elevates the standards of modern enterprise engineering. Through his continued research, leadership, and commitment to excellence, he remains a driving force in shaping the future of AI-powered data ecosystems.

Shams Al Ajrawi | Computer engineering | Best Researcher Award

Posted on by Academic achievements

Dr. Shams Al Ajrawi | Computer Engineering | Best Researcher Award

Assistant professor at Alliant International University, United States

Shams Al Ajrawi is a Lead Software Engineer and academic researcher with over a decade of experience in web application and backend development. His expertise spans across full-stack development, artificial intelligence (AI), data science, and Brain-Computer Interface (BCI) technologies. With a keen focus on solving intricate challenges, Shams has successfully led numerous industry and academic projects that have resulted in substantial financial savings and technological advancements. He has been actively involved in teaching, curriculum development, and research, playing a pivotal role in mentoring the next generation of engineers and computer scientists. His work bridges the gap between theoretical research and practical implementation, contributing to both corporate innovation and academic progress.

Profile: 

SCOPUS

Education:

Shams Al Ajrawi holds a Ph.D. in Electrical and Computer Engineering from a joint program between the University of California, San Diego, and San Diego State University, where his research focused on Brain-Computer Interface (BCI) applications. Prior to his Ph.D., he earned a Master’s degree in Electrical and Computer Engineering from the New York Institute of Technology and a Bachelor of Science in Computer Engineering from the Technological University. His academic journey is marked by a strong foundation in electrical engineering, computer science, and AI, with a specific focus on innovative applications in neuroscience and data processing.

Experience:

Shams has held prominent roles in both industry and academia. As a Lead Software Engineer at John Wiley & Sons, he led initiatives to enhance technology efficiency and reduce costs, including the integration of AI-based solutions like ChatGPT. His role also involved collaborating with corporate clients and managing cross-functional teams using Agile methodologies. In academia, he has served as an Associate Professor and Graduate Program Manager at Alliant International University, where he developed curricula, conducted research, and managed grants. Additionally, Shams is a Researcher Affiliate at UC San Diego’s Qualcomm Institute, focusing on BCI signal interpretation, and he has taught at several institutions, including San Diego State University and National University.

Research Interest:

Shams Al Ajrawi’s primary research interests lie in Brain-Computer Interface (BCI) technology, artificial intelligence, and signal processing. His work in the BCI domain has focused on improving signal extraction and classification, using techniques such as hierarchical recursive feature elimination and flexible wavelet transformation. His research aims to enhance the efficiency and accuracy of interpreting brain signals, particularly for applications related to assisting individuals with spinal cord injuries. Additionally, he explores the integration of AI and machine learning techniques in software development, cybersecurity, and data analytics, striving to develop innovative solutions that merge computational efficiency with real-world applications.

Awards:

Shams has been recognized for his contributions in both industry and academia. He received promotions and excellence awards for two consecutive years at John Wiley & Sons for his leadership and innovative approach in software engineering. In 2023, he was appointed as an Associate Professor at Alliant International University in recognition of his contributions to academia. He has also earned several professional certifications, including the ISACA certification (2023–2028) and Cisco’s CCNA certification, further solidifying his expertise in software engineering and networking.

Publications:

Shams Al Ajrawi has authored numerous papers in prestigious journals, focusing on BCI applications, RFID, and AI. Some of his notable publications include:

“Investigating Feasibility of Multiple UHF Passive RFID Transmitters Using Backscatter Modulation Scheme in BCI Applications” (2017) – Published in IEEE International Symposium on Performance Evaluation of Computer and Telecommunication Systems Cited by 35 articles.

“Bi-Directional Channel Modeling for Implantable UHF-RFID Transceivers in BCI Application” (2018) – Published in Journal of Future Generation Computer Systems, Elsevier Cited by 42 articles.

“Efficient Balance Technique for Brain-Computer Interface Applications Based on I/Q Down Converter and Time Interleaved ADCs” (2019) – Published in Informatics in Medicine Unlocked, Elsevier Cited by 30 articles.

“Hybrid MAC Protocol for Brain-Computer Interface Applications” (2020) – Published in IEEE Systems Journal Cited by 27 articles.

“Cybersecurity in Brain-Computer Interfaces: RFID-Based Design-Theoretical Framework” (2020) – Published in Informatics in Medicine Unlocked, Elsevier Cited by 22 articles.

Conclusion:

Shams Al Ajrawi stands out as a highly accomplished candidate for a “Best Researcher Award.” His rich experience, cutting-edge research, and impactful contributions across both industry and academia position him as a leading figure in his field. However, by narrowing his research focus and expanding interdisciplinary and mentorship efforts, he could enhance his candidacy even further. Overall, he appears highly suitable for the award.

Javed Rashid | Computer Science | Best Researcher Award

Posted on by Academic achievements

Dr. Javed Rashid | Computer Science | Best Researcher Award 

Network Administrator | University of Okara | Pakistan

Research for Best Researcher Award

Strengths for the Award

Dr. Javed Rashid has demonstrated exceptional capabilities in both research and practical application, making him a strong candidate for the Best Researcher Award. His extensive experience as a Network Administrator and educator at reputable institutions like the University of Okara and University of Education showcases his ability to manage and innovate in complex technical environments. Dr. Rashid’s academic achievements, including a Ph.D. in Computer Science with a GPA of 3.58/4 from Islamic International University, underscore his deep knowledge and dedication to the field.

His research contributions are particularly noteworthy. Dr. Rashid’s publications cover a broad spectrum of computer science topics, from deep learning and computer vision to medical disease diagnosis. His work on deep learning models for potato leaf disease recognition and skin cancer detection highlights his expertise in leveraging cutting-edge technologies to address real-world problems. The diversity and impact of his research make him a standout in the field.

Areas for Improvement

While Dr. Rashid’s research portfolio is robust, there are areas where he could enhance his profile further. Interdisciplinary collaboration could be one avenue for growth, as integrating insights from other fields could lead to novel approaches and innovations. Expanding his international collaborations and partnerships might also help in gaining broader recognition and influence in global research circles.

Additionally, Dr. Rashid might consider engaging more actively in public science communication and outreach. By presenting his work at international conferences and participating in public forums, he could increase the visibility of his research and its applications. Fostering a stronger online presence through platforms like academic social networks or personal research blogs could also help in showcasing his contributions and engaging with a wider audience.

Short Bio

Dr. Javed Rashid is an accomplished scholar and professional with a diverse background in computer science and IT management. Currently serving as a Network Administrator at the University of Okara, he has extensive experience in both administrative and academic roles. Dr. Rashid is recognized for his significant contributions to research in computer vision, deep learning, and disease detection, demonstrating his commitment to advancing technology and its practical applications.

Profile

ORCID

Education

Dr. Rashid holds a Ph.D. in Computer Science from Islamic International University, Islamabad, where he achieved a commendable GPA of 3.58/4. He is also a gold medalist in both his MSCS/MPhil and MCS degrees from Superior University Lahore and Hajvery University, respectively. His academic journey includes a Bachelor of Laws from Punjab University and a Bachelor of Computer Sciences from Allama Iqbal Open University, reflecting his well-rounded educational background.

Experience

Dr. Rashid has a robust professional history, including roles as a Network Administrator, Deputy Registrar-IT, and Assistant Network Administrator at the University of Okara. His prior experience includes positions at the University of Education, Okara Campus, and Government Degree College Chichawatni. He has also contributed as a visiting lecturer and has extensive experience in both practical IT management and academic instruction.

Research Interest

Dr. Rashid’s research interests are centered on advanced topics in computer science, including computer vision, deep learning, and pattern recognition. His work explores applications in areas such as smart cities, medical disease diagnosing, and plant leaf diseases. He is particularly focused on leveraging deep learning techniques to enhance disease detection and classification systems.

Awards

Dr. Rashid has been recognized for his academic excellence and research contributions. Notable awards include gold medals for his MCS and MSCS degrees, acknowledging his outstanding academic performance. His research achievements continue to gain attention and impact in the field of computer science.

Publications

Rashid, J., Khan, I., Ali, G., Almotiri, S.H., AlGhamdi, M.A., Masood, K. “Multi-Level Deep Learning Model for Potato Leaf Disease Recognition,” Electronics, 2021, 10(17), 2064. Link
Cited by: 20

Rashid, J.; Ishfaq, M.; Ali, G.; Saeed, M.R.; Hussain, M; Alkhalifah, T.; Alturise, F.; Samnd N. “Skin Cancer Disease Detection Using Transfer Learning Technique,” Appl. Sci., 2022, 12, 5714. Link
Cited by: 35

Rashid, J., Khan, I., Ali, G., Rehman, S.U., Alkhalifah, T., Alturise, F. “Real-Time Multiple Guava Leaf Disease Detection from a Single Leaf Using Hybrid Deep Learning Technique,” Computers, Materials & Continua, 2023, 74(1), 1235-1257. Link
Cited by: 18

Sohail, M.; Ali, G.; Rashid, J.; Ahmad, I.; Almotiri, S.H.; AlGhamdi, M.A.; Nagra, A.A.; Masood, K. “Racial Identity-Aware Facial Expression Recognition Using Deep Convolutional Neural Networks,” Appl. Sci., 2022, 12, 88. Link
Cited by: 27

H. Chu, M. R. Saeed, J. Rashid, M. T. Mehmood, I. Ahmad et al. “Deep learning method to detect the road cracks and potholes for smart cities,” Computers, Materials & Continua, 75(1), 1863–1881, 2023. Link
Cited by: 22

Rehan Ahmad, Javaid Rashid, Suhail Iqbal, Khurshid Asghar “Evaluation of Multi-Channel Wireless Network Using Performance Metrics,” Journal of Basic and Applied Scientific Research., 4(8), 36-44, 2014. Link
Cited by: 10

Rashid, J., Khan, I., Abbasi, I., A.; Saeed M.R., Saddique, M., Abbas, M., A. “A Hybrid Deep Learning Approach to Classify the Plant Species,” Computers, Materials & Continua, 76 (3), 3897–3920, 2023. Link
Cited by: 19

Afzal, M., F.; Khan, I., Rashid, J.; Saddique, M., Gaber, H. “Binary Oriented Feature Selection with Crosstree Constraints for Valid Product Derivation in Software Product Line,” Computers, Materials & Continua, 76 (3), 3653–3670, 2023. Link
Cited by: 16

Conclusion

Dr. Javed Rashid is a distinguished researcher whose work has made significant contributions to the field of computer science, particularly in the areas of deep learning, computer vision, and disease diagnosis. His strengths lie in his extensive experience, impactful research, and academic achievements. By focusing on interdisciplinary collaborations, expanding international networks, and enhancing public engagement, Dr. Rashid could further elevate his profile and influence in the research community. For these reasons, he is a highly deserving candidate for the Best Researcher Award.

Guda Vanitha | Computer Science | Best Researcher Award

Posted on by Academic achievements

Dr. Guda Vanitha | Computer Science | Best Researcher Award

Associate Professor, Chaitanya Bharathi Institute of Technology,(A), India

Dr. G. Vanitha is an accomplished educator and Assistant Professor in the Department of Computer Science Engineering at Chaitanya Bharathi Institute of Technology. With 17 years of teaching experience, she holds a Ph.D. in Computer Science Engineering from Jawaharlal Nehru Technological University, Hyderabad. Her research focuses on Natural Language Processing, particularly in event time relation extraction. Dr. Vanitha has authored a textbook, holds multiple patents, and has received numerous awards for her contributions to academia.

Profile

Google Scholar

 

🎓 Education:

Dr. Vanitha completed her Ph.D. in Computer Science Engineering from Jawaharlal Nehru Technological University, Hyderabad in 2021. She also holds an M.Tech in Computer Science Engineering (2012) and a B.Tech in Computer Science Engineering (2006) from Bharat Institute of Engineering Technology, JNTUH, Hyderabad. Additionally, she pursued a Diploma in Computer Science Engineering and completed her SSC from the Board of Secondary School of Education.

💼 Experience:

She has been serving as an Assistant Professor in Computer Science and Engineering at Chaitanya Bharathi Institute of Technology since April 2007. Prior to this, she held an ad-hoc position in the same department from August 2006 to April 2007.

🔬 Research Interests:

Dr. Vanitha’s research interests include Language Theory, Data Engineering, Machine Learning, and Artificial Intelligence. Her work focuses on developing frameworks for event extraction and representation in natural language texts.

🏆 Awards:

Dr. Vanitha received the “Pre-eminent Researcher National Award 2022” from Chennai Teacher’s Council (CTC) in recognition of her outstanding contributions to research.

📚 Publications:

Covid19 Patterns Analyzation Using Machine Learning, International Journal of Interdisciplinary Cycle Research (JICR), 2021.

Building Graph for Events and Time in Natural Language Text, International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2020.

Heart Disease Prediction Using Hybrid Technique, Journal of Interdisciplinary Cycle Research (JICR), 2020.

Event Extraction And Classification From English Articles, International Journal of Recent Technology and Engineering (IJRTE), 2019.

Event-Time Relation in Natural Language Text, International Journal of Engineering and Advanced Technology (IJEAT), 2019.

Performance Analysis of Learning Models on Medical Documents, International Journal of Innovative Research in Technology (IJIRT), 2018.