Ms. Manasvi Aggarwal | Artificial Intelligence | Young Scientist Award

Senior Data Scientist, Mastercard

Name: Manasvi Aggarwal Gender: Female Designation: Senior Data Scientist Department: AI Garage Organization: Mastercard Specialization: Artificial IntelligenceExpertise: Graph Neural Networks (GNNs), Spatio-Temporal Forecasting, Neural Algorithmic Reasoning Industry Experience: Microsoft, Myntra, Mastercard Notable Work: Developed MRP-GNN, identifying $17M in fraud and increasing fraud detection rates by 20% Research Collaborations: Oxford, Cambridge (INAR project) Publications: ICPR, IEEE BigData, ICML workshops, RecSys, Springer book Awards: Business Excellence Award (Mastercard), Google-sponsored EEML travel grant Professional Contributions: ICLR, IEEE BigData, and NeurIPS program committee member Vision: Advancing scalable AI solutions for real-world impact

profile:

Scholar

🎓 Education

B.Tech: Computer Science, University of Delhi (Ranked 4th in cohort) Competitive Exams: GATE (99.47 percentile), JEST (All India Rank 35) M.Tech (Research): Computer Science, IISc Bengaluru Thesis: “Embedding Networks: Node and Edge Representations” (Graph-based learning, NLP, Computer Vision) PhD Offers: Fully funded PhD admissions from Canada and the USA (deferred due to financial reasons) Key Research Areas: Graph Neural Networks, Spatio-Temporal Forecasting, Neural Algorithmic Reasoning Notable Academic Achievements: IISc Research Contributions in GNNs and self-supervised learning

💼 Experience

Microsoft: Developed multi-label categorization for Azure offers using BERT embeddings and web scraping Myntra: Worked on pricing automation, demand forecasting, and user cohort modeling with graph-based approaches Mastercard: Leading AI-driven fraud detection initiatives, including MRP-GNN (detected $17M fraud, 20% improved detection rates) Industry Collaborations: Worked with teams in Israel, USA, and India on AI-driven solutions Mentorship: Guides junior AI researchers, participates in hiring interviews

🏆 Awards & Honors

Business Excellence Award – Mastercard Priceless Mentoring and Guidance Award – Mastercard Google-sponsored travel grant – EEML 2024 1st Runner-up – Myntra HackerRamp Hackathon Invited Program Committee Member – ICLR, IEEE BigData, NeurIPS

🔬 Research Focus

Key Areas: Graph Neural Networks (GNNs), Spatio-Temporal Forecasting, Neural Algorithmic Reasoning Mastercard Research: Developed MRP-GNN, detecting high-risk merchants and preventing financial fraud AI for Security: Fraud detection, risk prediction, secure transactions Spatio-Temporal AI: Developed GNN for terror activity forecasting in Jammu & Kashmir Academic Collaborations: Works with Oxford & Cambridge on INAR, optimizing CLRS-30 benchmarks Publications: Published in ICPR, IEEE BigData, ICML workshops, RecSys Community Contributions: Co-organized Southeast Asian Learning on Graphs (LoG) 2024 Meetup

✅ Conclusion

Manasvi Aggarwal is a highly competitive candidate for the Best Researcher Award, with a strong blend of academic excellence, industry impact, publications, and global collaborations. If she strengthens her patent portfolio, citation metrics, and leadership in independent research projects, she would be an even stronger contender for distinguished research awards.

publication

Deep Learning – M. Aggarwal, M.N. Murty (2021) – 21 citations

Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs – M. Aggarwal, M.N. Murty (2021) – 18 citations

Self-supervised Hierarchical Graph Neural Network for Graph Representation – S. Bandyopadhyay, M. Aggarwal, M.N. Murty (2020) – 4 citations

Robust Hierarchical Graph Classification with Subgraph Attention – S. Bandyopadhyay, M. Aggarwal, M.N. Murty (2020) – 4 citations

Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization – S. Bandyopadhyay, M. Aggarwal, M.N. Murty (2020) – 3 citations

A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention – S. Bandyopadhyay, M. Aggarwal, M.N. Murty (2021) – 2 citations

Region and Relations Based Multi Attention Network for Graph Classification – M. Aggarwal, M.N. Murty (2021) – 2 citations

Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users – A. Budhiraja, M. Sukhwani, M. Aggarwal, S. Shevade, G. Sathyanarayana (2022) – 1 citation

Node Representations – M. Aggarwal, M.N. Murty (2021) – 1 citation

Hierarchically Attentive Graph Pooling with Subgraph Attention – S. Bandyopadhyay, M. Aggarwal, M.N. Murty (2020) – 1 citation

Embedding Graphs – M. Aggarwal, M.N. Murty (2021)

Representations of Networks – M. Aggarwal, M.N. Murty (2021)

Embedding Networks: Node and Graph Level Representations – M. Aggarwal

Mr Narayan Vyas | Artificial Intelligence | Young Scientist Award

Mr Narayan Vyas , Vivekananda Global University, India

Dr. Narayan Vyas is an Assistant Professor at Vivekananda Global University, Jaipur, specializing in Internet of Things (IoT) and application development. With a Ph.D. in Computer Science and multiple publications in peer-reviewed journals, he is recognized for his significant contributions to IoT, machine learning, and remote sensing. Dr. Vyas has a proven track record in academia and industry, including roles as a Technical Trainer and Research Consultant. His research includes developing frameworks for agricultural changes and innovations in mobile app development. He is also an active keynote speaker and workshop organizer, dedicated to advancing technological education.

Publication Profile

Orcid

Strengths for the Award

Extensive Research Contributions: Narayan has a robust research profile with numerous publications in peer-reviewed international journals and conferences. His work spans diverse and cutting-edge fields, including IoT, remote sensing, machine learning, and computer vision. This breadth and depth of research indicate a high level of expertise and a significant contribution to the field.
Active Engagement in Academia: As an Assistant Professor and Research Coordinator, Narayan plays a key role in shaping academic programs and mentoring students. His leadership in developing syllabi and organizing workshops demonstrates a commitment to advancing both education and research.
Industry Experience and Practical Impact: His practical experience in mobile application development and work with clients worldwide show his ability to bridge the gap between academic research and real-world applications. This experience is valuable for translating theoretical research into practical solutions.
Editorial and Consultancy Roles: Editing several books and working as a research consultant highlight his expertise and recognition in the field. These roles suggest a high level of respect and credibility among peers.
National Recognition: Passing the NTA UGC NET & JRF on his first attempt underscores his strong foundational knowledge and commitment to research excellence.

Areas for Improvement

Research Continuity and Focus: While Narayan’s work is extensive, he could benefit from focusing more deeply on a narrower set of research areas. This could lead to more impactful and cohesive contributions in specific domains.
Increased Research Collaboration: Although Narayan has collaborated with others, increasing his participation in interdisciplinary research projects could further enhance his impact and visibility in diverse fields.
Awards and Grants: While Narayan has significant achievements, actively seeking and obtaining prestigious awards and grants could bolster his profile and provide additional validation of his research impact.
Public Engagement: Enhancing efforts to communicate research findings to a broader audience, including the general public, could improve the societal impact of his work.

Education

Dr. Narayan Vyas is pursuing a Ph.D. in Computer Science at Punjabi University, Patiala, focusing on developing an image fusion framework for agricultural detection using remote sensing data. He cleared the NTA UGC NET & JRF in Computer Science on his first attempt. Dr. Vyas holds a Master’s in Computer Application from Maharshi Dayanand Saraswati University, where he achieved the first rank. He completed his Bachelor’s in Computer Applications with a specialization in IoT, where he developed a self-balancing robot as his major project.

Experience

Dr. Narayan Vyas currently serves as an Assistant Professor and Research Coordinator at Vivekananda Global University, Jaipur. Previously, he was a Technical Trainer at Chandigarh University, where he founded the Student Research Cell. His role as Principal Research Consultant at AVN Innovations Pvt. Ltd. involved leading research projects and mentoring junior researchers. As a Senior Mobile App Developer at Flexxited, he developed applications for clients globally. His experience spans from academic roles to hands-on technical work, including freelance and training positions.

Awards and Honors

Dr. Narayan Vyas has been recognized for his contributions to technology and research. He served as a Session Chair at the 1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI-2023). He has reviewed papers for prestigious conferences such as IEEE NMITCON-2023 and ICDSNS-2023. He was a proctor for the IEEEXtreme 17.0 programming competition and conducted notable workshops on mobile app development and IoT at leading universities.

Research Focus

Dr. Narayan Vyas’s research focuses on integrating advanced technologies like IoT, machine learning, and remote sensing to solve complex problems in agriculture, healthcare, and environmental monitoring. His work includes developing frameworks for detecting agricultural changes, improving mobile app development methodologies, and enhancing remote sensing data analysis. He is passionate about applying these technologies to real-world problems and advancing the academic understanding of their applications.

Publication Top Notes

“Applying Machine Learning Techniques to Bioinformatics” 📚

“Innovations in Machine Learning and IoT for Water Management” 💧

“Quantum Innovations at the Nexus of Biomedical Intelligence” 🧬

“AI-Driven Alzheimer’s Disease Detection and Prediction” 🧠

“Secure Energy Optimization: Leveraging IoT and AI for Enhanced Efficiency” ⚡

“Internet of Medicine for Smart Healthcare” 🏥

“Multimodal Data Fusion for Bioinformatics” 🌐

“Elevating IoT Sensor Data Management and Security Through Blockchain Solutions” 🔒

“A Machine Learning Framework for Accurate Prediction of Parkinson’s Disease from Speech Data” 🗣️

“Advancing Precision Agriculture: Leveraging YOLOv8 for Robust Deep Learning Enabled Crop Diseases Detection” 🌾

Conclusion

Narayan Vyas is a compelling candidate for the Research for Young Scientist Award due to his significant contributions to research, his active role in academia, and his practical experience. His extensive publication record and leadership in academia reflect a high level of expertise and dedication. Addressing the areas for improvement, such as focusing research efforts and seeking additional recognition, could further strengthen his candidacy. Overall, his achievements and ongoing contributions make him a strong contender for this award.

Manasvi Aggarwal | Artificial Intelligence | Young Scientist Award