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

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.

Weijia Jia | AI on Edge Computing | Best Researcher Award

Prof. Weijia Jia | AI on Edge Computing | Best Researcher Award

Director | Beijing Normal University (Zhuhai), China | China

Evaluation of Weijia Jia for the Best Researcher Award

Strengths for the Award:

Weijia Jia exemplifies excellence in research, making a compelling case for the “Best Researcher Award” with his significant achievements and contributions. His extensive educational background, including degrees from prestigious institutions and significant research experience across various international platforms, underscores his deep expertise. Jia’s role as Dean of the Institute of Artificial Intelligence and Future Networks at Beijing Normal University, coupled with his leadership at the Interdisciplinary Intelligent Supercomputing Center, highlights his influential position in advancing AI and supercomputing.

His impressive list of honors, such as the IEEE Fellow title, numerous awards including the IEEE Outstanding Paper Award and the Best Student Paper Award, and recognition as a top scientist by Stanford University, reflect his impactful contributions to the field. His research in edge computing, multi-server allocation, and AI-driven solutions has resulted in high-impact publications in leading journals like IEEE Transactions and ACM Transactions. The substantial citation count and h-index reinforce his scholarly influence and the relevance of his work in the academic community.

Areas for Improvement:

While Jia’s research portfolio is robust, there are areas where improvements could further bolster his candidacy. Expanding his research focus to include emerging areas such as quantum computing or interdisciplinary applications could enhance his influence. Additionally, increasing collaboration with industry partners could accelerate the practical implementation of his research findings and bridge the gap between theoretical advancements and real-world applications.

Moreover, fostering greater visibility in diverse academic conferences and engaging in collaborative research projects with international institutions could broaden his impact and contribute to a more globalized perspective in his work. Strengthening outreach and communication efforts to highlight the societal benefits and practical applications of his research could further enhance his reputation and influence.

Short Bio:

Weijia Jia is a distinguished academic and researcher specializing in artificial intelligence and future networks. Currently serving as the Dean of the Institute of Artificial Intelligence and Future Networks and the Director of the Interdisciplinary Intelligent Supercomputing Center at Beijing Normal University (BNU-Zhuhai), Jia has made significant contributions to edge computing and intelligent systems. His extensive career includes roles as a Chair Professor and Vice President for Research & Development, reflecting his leadership and expertise in advancing technological research and innovation.

Profile:

Google Scholar

Education:

Weijia Jia’s educational background is extensive and international. He completed his BSc and MSc in Computer Science at Central-South University, Changsha, China. He furthered his studies with a MSc in Applied Science from the Faculty Polytechnic of Mons, Belgium, and earned his PhD from the same institution. This robust educational foundation has provided Jia with a deep and broad understanding of computer science and its applications.

Experience:

Jia’s career spans several prestigious academic and research institutions. Starting as an Assistant Lecturer at Central-South University, he has held significant positions including Visiting Professor at the University of Ottawa, Research Fellow at GMD, and Professor roles at City University of Hong Kong and Shanghai Jiao-tong University. His current role at Beijing Normal University (BNU-Zhuhai) includes serving as the Dean and Director, highlighting his leadership in AI and supercomputing research.

Research Interests:

Weijia Jia’s research interests are centered on artificial intelligence, edge computing, and intelligent supercomputing. His work explores dynamic resource allocation, container scheduling, and innovative AI models for efficient computing. Jia’s research aims to address challenges in distributed systems and networked environments, contributing to advancements in both theoretical and practical aspects of AI and computing technologies.

Awards:

Jia’s research excellence has been recognized through numerous awards. He is a 2020 IEEE Fellow and has received accolades such as the IEEE Outstanding Paper Award and Best Student Paper Award in 2023. His contributions have earned him a place among the top 2% of lifetime scientists by Stanford University, and he has received various national and international awards, including the 1st Prize of Scientific Research Awards from China’s Ministry of Education in 2017.

Publications:

Joint Resource Overbooking and Container Scheduling in Edge Computing, IEEE Transactions on Mobile Computing, 2024 (Early Access). Cited by: Tang et al., 2024.

Dynamic Parallel Multi-Server Selection and Allocation in Collaborative Edge Computing, IEEE Transactions on Mobile Computing, 2024 (Early Access). Cited by: Xu et al., 2024.

Adversarial Bandits With Multi-User Delayed Feedback: Theory and Application, IEEE Transactions on Mobile Computing, 2024 (Early Access). Cited by: Li et al., 2024.

MEL: Efficient Multi-Task Evolutionary Learning for High-Dimensional Feature Selection, IEEE Transactions on Knowledge and Data Engineering, 36(8), 2024. Cited by: Wang et al., 2024.

EF-DETR: A Lightweight Transformer-Based Object Detector With an Encoder-Free Neck, IEEE Transactions on Industrial Informatics, 2024 (Early Access). Cited by: Cheng et al., 2024.

Latency-Aware Container Scheduling in Edge Cluster Upgrades: A Deep Reinforcement Learning Approach, IEEE Transactions on Services Computing, 2024 (Early Access). Cited by: Cui et al., 2024.

OffsetINT: Achieving High Accuracy and Low Bandwidth for In-Band Network Telemetry, IEEE Transactions on Services Computing, 17(3), 2024. Cited by: Qian et al., 2024.

SecEG: A Secure and Efficient Strategy against DDoS Attacks in Mobile Edge Computing, ACM Transactions on Sensor Networks, 20(3), 2024. Cited by: Huang et al., 2024.

Startup-aware Dependent Task Scheduling with Bandwidth Constraints in Edge Computing, IEEE Transactions on Mobile Computing, 23(2), 1586-1600, 2024. Cited by: Lou et al., 2024.

Perceptual Quality Analysis in Deep Domains Using Structure Separation and High-Order Moments, IEEE Transactions on Multimedia, 26, 2219-2234, 2024. Cited by: Xian et al., 2024.

Conclusion:

Weijia Jia’s distinguished career, marked by significant achievements in AI and supercomputing, exceptional research output, and notable awards, positions him as a strong candidate for the “Best Researcher Award.” His deep expertise, innovative contributions, and leadership in advancing cutting-edge technologies are commendable. Addressing the areas for improvement, particularly in expanding research focus and enhancing industry collaboration, could further solidify his standing as a leading researcher in his field. Overall, Jia’s credentials and accomplishments align well with the criteria for the award, making him a deserving nominee for this prestigious recognition.