Pawan Kumar Patidar | Machine Learning | Young Scientist Award

Mr. Pawan Kumar Patidar | Machine Learning | Young Scientist Award

Swami Keshvanand Institute of Technology, Management and Gramothan | India

Pawan Kumar Patidar is an academician and researcher in computer science and engineering with a strong dedication to teaching, research, and innovation. Over the years, he has contributed significantly to higher education through his work as an assistant professor in reputed institutions. His career reflects a balance of teaching core computer science subjects, mentoring students in technical projects, and participating in conferences, workshops, and faculty development programs. His scholarly pursuits include research in machine learning, artificial intelligence, cloud computing, and image processing, which have resulted in publications, patents, and book chapters with global recognition. Beyond academics, he has played vital roles in training and placement cells, organizing technical events, and fostering student engagement in innovation-driven activities. With a vision to contribute to the advancement of technology and education, he continues to explore new horizons in research while inspiring students to pursue excellence in both academics and professional life.

Profile

Google Scholar

Education 

Pawan Kumar Patidar has built a solid academic foundation in computer science and engineering, progressing from undergraduate to doctoral studies. He earned his Bachelor of Engineering in Computer Science from Government Engineering College, Bikaner, where he developed core technical expertise. Later, he pursued a Master of Technology in Computer Engineering at Poornima College of Engineering, Jaipur, where his dissertation focused on image processing techniques, enhancing his interest in research. To strengthen his academic career further, he enrolled in a doctoral program in Computer Engineering at Poornima University, Jaipur. His Ph.D. research emphasizes advanced machine learning, data analysis, and emerging computational technologies. Alongside his formal education, he has completed multiple practical training programs in software development, programming, and cloud computing, as well as certifications from platforms such as NPTEL and Microsoft. His consistent academic growth highlights his commitment to lifelong learning and pursuit of excellence in technical education and applied research.

Experience 

Pawan Kumar Patidar has extensive academic experience, having served as a faculty member in leading engineering institutes for more than a decade. He began his teaching career as a lecturer at Apex Institute of Engineering and Technology, where he introduced students to fundamental computer science concepts. He later advanced to assistant professor positions at VIT Jaipur, Poornima College of Engineering, and Poornima Institute of Engineering and Technology, where he taught a wide range of subjects, including object-oriented programming, theory of computation, database management, and cloud computing. At present, he is associated with Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, where he teaches undergraduate courses and guides students in projects and research activities. Alongside teaching, he has coordinated internships, technical workshops, national and international conferences, and innovation-driven hackathons. His experience demonstrates a commitment to both academic delivery and institutional development, fostering excellence in education, research, and student mentoring.

Awards and Honors 

Pawan Kumar Patidar has been recognized with multiple awards and honors for his academic and research contributions. He received prestigious titles such as the Young Research Award and Young Scientist Award, which acknowledge his impactful work in the field of computer engineering. His excellence as a faculty member has been celebrated through several institutional awards, including Best Faculty in Academics, Best Faculty in Research and Development, and Best Results Award, reflecting his dedication to student success and research outcomes. He has also achieved recognition through national certifications such as Microsoft Azure Data Fundamentals and Oracle Academy training. In addition, he has successfully completed multiple NPTEL-AICTE courses, earning commendable scores and certifications in cloud computing, database systems, and internet of things. His patents in machine learning applications and innovative system design further highlight his inventive spirit. Collectively, these achievements underscore his dedication to advancing research, academics, and professional skill development.

Research Focus 

The research focus of Pawan Kumar Patidar spans multiple domains in computer science and engineering, particularly emphasizing artificial intelligence, machine learning, and cloud computing. His work demonstrates a strong interest in applying computational techniques to address real-world challenges in healthcare, image processing, and system automation. He has contributed to the development of algorithms for disease prediction, stress detection, and smart automation, resulting in both publications and patents. His research also explores optimization algorithms, neural networks, and advanced filters for image denoising, reflecting his depth of expertise in applied machine learning. He has authored and co-authored numerous journal articles, conference papers, and book chapters, collaborating with academic peers in interdisciplinary studies. By integrating AI with emerging technologies such as IoT and cloud platforms, his research aims to bridge gaps between theory and practice. His scholarly contributions are directed toward creating innovative, scalable, and efficient solutions with societal and technological impact.

Publications

  • Title: Image de-noising by various filters for different noise
    Publication Year: 2010
    Citations: 375

  • Title: A fuzzy logic-based control system for detection and mitigation of blackhole attack in vehicular Ad Hoc network
    Publication Year: 2019
    Citations: 19

  • Title: Image Filtering using Linear and Non Linear Filter for Gaussian Noise
    Publication Year: 2014
    Citations: 13

  • Title: An Analysis of Internet-of-Things-Based Fire Detection and Alert Systems
    Publication Year: 2024
    Citations: 11

  • Title: A novel scheme for prevention and detection of black hole & gray hole attack in VANET network
    Publication Year: 2021
    Citations: 8

Conclusion

Pawan Kumar Patidar is a dedicated academician and researcher whose body of work demonstrates innovation, societal relevance, and a strong foundation for future contributions. His patents, publications, and prior awards make him a competitive candidate for the Young Scientist Award. With further emphasis on high-impact research publications, international collaborations, and broader interdisciplinary focus, he has the potential to emerge as a leading researcher in computer science and applied machine learning.

Manasvi Aggarwal | Artificial Intelligence | Young Scientist Award

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