Satish Kabade | Computer Science and Artificial Intelligence | Best Industrial Research Award

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Mr Satish Kabade | Computer Science and Artificial Intelligence | Best Industrial Research Award

Product Technical Expert, Communication Experts, United States

Satish Kabade is a seasoned IT Consultant and Solutions Architect with over 17 years of experience in software development, enterprise architecture, and cloud computing. He is renowned for his expertise in Microsoft .NET and Azure technologies, leading cross-functional teams to deliver scalable, high-performing solutions. Satish has been instrumental in integrating AI and Machine Learning into pension management systems, enhancing automation, risk analysis, and predictive analytics. His work includes developing AI-driven fraud detection algorithms, personalized retirement benefit recommendations, and AI-based chatbots for member inquiries. He holds certifications as an Azure Solution Architect, TOGAF 9 Certified Architect, and Certified Scrum Master. Satish is also a mentor, conducting workshops on design patterns, best coding practices, cloud migration strategies, and AI/ML implementation.

Profile

Google Scholar

Education 

Satish Kabade’s educational background reflects a strong foundation in technology and cloud computing. He completed a Post Graduate Program in Cloud Computing from Great Learning in 2021, equipping him with advanced knowledge in cloud technologies. Prior to this, he earned a Post Graduate Diploma in Computer Applications from CDAC, Pune, in 2006, which provided him with a comprehensive understanding of software development and computer science principles. His academic journey began with a Bachelor of Engineering in Mechanical Engineering from Shivaji University, Solapur, in 2004, showcasing his analytical and problem-solving skills. This diverse educational background has enabled Satish to bridge the gap between traditional engineering and modern IT solutions, making significant contributions to the integration of AI and cloud technologies in various domains, particularly in pension management systems.

Experience 

With over 17 years in the IT industry, Satish Kabade has amassed extensive experience in software development, enterprise architecture, and cloud computing. He has designed and developed full-stack solutions using .NET Core, C#, ASP.NET, and AWS cloud technologies, ensuring seamless integration between front-end and back-end components. Satish has leveraged AWS Cloud services such as EC2, S3, Lambda, and RDS to deploy, scale, and manage cloud-based applications, ensuring high availability and fault tolerance. His expertise extends to integrating AI and Machine Learning solutions into pension management systems, enhancing automation, risk analysis, and predictive analytics. Notably, he has developed AI/ML-based predictive analytics for retirement planning and investment forecasting, improving decision-making for pension fund administrators and members. Additionally, Satish has implemented AI-driven fraud detection algorithms for pension disbursements and payroll processing, minimizing risks and ensuring regulatory compliance.

Research Focus

Satish Kabade’s research focus centers on the integration of Artificial Intelligence (AI) and Machine Learning (ML) into pension management systems to enhance automation, risk analysis, and predictive analytics. He has developed AI/ML-based predictive analytics for retirement planning and investment forecasting, enabling improved decision-making for pension fund administrators and members. His work includes implementing AI-driven fraud detection algorithms for pension disbursements and payroll processing, minimizing risks and ensuring regulatory compliance. Satish has also designed and implemented Machine Learning models for personalized retirement benefit recommendations, leveraging historical contribution data and economic trends. Additionally, he has developed AI-based chatbots and virtual assistants for member inquiries, streamlining benefits administration and customer support. His research aims to improve the efficiency, security, and personalization of pension systems, contributing to the broader field of AI applications in financial services.

Publication Top Notes

  1. “AI-Driven Financial Management: Optimizing Investment Portfolios through Machine Learning”

    • Authors: T.V. Ambuli, S. Venkatesan, K. Sampath, Kabirdoss Devi, S. Kumaran

    • Published: August 2024

    • Conference: 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT)

    • Summary: This paper explores the application of AI and ML in optimizing investment portfolios, focusing on enhancing financial management strategies through advanced computational techniques.

  2. “A Machine Learning Model for Algorithmic Optimization of Superannuation Schemes”

    • Authors: Winfred Katile Mukunzi, Brian Wesley Muganda, Bernard Shibwabo

    • Published: October 2024

    • Summary: The study develops a machine learning-based recommendation model for optimal asset portfolio selection and allocation in superannuation schemes, addressing challenges in financial market uncertainties.

  3. AI-Driven Fraud Detection in Investment and Retirement Accounts
    Author: Ajay Benadict Antony Raju
    Published in: ESP International Journal of Advancements in Computational Technology, Volume 2, Issue 1, 2024

    Summary:
    This paper discusses the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in detecting fraudulent activities within investment and retirement accounts. It highlights the limitations of traditional fraud detection methods and emphasizes the advantages of AI and ML in analyzing large datasets to identify patterns indicative of fraudulent behavior. The study underscores the importance of integrating AI-driven approaches to enhance the security and integrity of financial systems.ESP Journals

  4.  Enhancing AI-Based Financial Fraud Detection with Blockchain
    Authors: Prof. Kumar Lui, Prof. Kusal Fisher, Prof. Shyam Raj
    Published in: International Journal of Holistic Management Perspectives, Volume 4, Issue 4, 2023

    Summary:
    This article explores the integration of Blockchain technology with AI-based financial fraud detection systems. It examines how blockchain’s decentralized and immutable nature can complement AI models to provide more robust and transparent fraud detection mechanisms. The paper discusses various use cases and the potential benefits of combining these technologies to combat financial fraud effectively.

Conclusion

Satish Kabade is a highly capable technologist and applied researcher, especially in AI/ML integration within legacy government and pension systems. His work shows clear innovation, enterprise-scale application, and practical relevance, which are key strengths for industrial research recognition. However, for a Best Industrial Research Award, the lack of formal research dissemination (papers, presentations, patents) may be a limiting factor unless the award heavily favors applied over academic research.

Tuhin Subhra De | Artificial Intelligence Awards | Young Scientist Award

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Mr Tuhin Subhra De | Artificial Intelligence Awards | Young Scientist Award

Mr Tuhin Subhra De, Indian Institute of Technology Kharagpur, India

Tuhin Subhra De is a dual-degree student at the Indian Institute of Technology Kharagpur, specializing in Civil and Environmental Engineering with minors in Mathematics and Computing, and Artificial Intelligence Applications. With a CGPA of 8.7/10.0, Tuhin has demonstrated his prowess in both academics and research. He has gained significant experience as a Deep Learning Research Intern at IIT KGP’s Center for Excellence in AI, where he worked on improving text generation quality using advanced models. Tuhin has also completed internships in Data Science and Machine Learning at prominent organizations like Udaan.com and Deakin University, focusing on predictive modeling and knowledge distillation. His research work has led to multiple publications in esteemed journals and conferences. Outside academics, Tuhin is active in mentoring and social work, contributing to the welfare of underprivileged communities and participating in various sports events.

Publication Profile

Google scholar

Strengths for the Award

  • Academic Excellence: Tuhin Subhra De has demonstrated strong academic performance with a CGPA of 8.7/10.0 from a prestigious institution like IIT Kharagpur, where he completed a dual degree in Civil and Environmental Engineering with minors in Mathematics, Computing, and AI.
  • Research Experience: He has extensive research experience, notably working as a Deep Learning Research Intern at the Center for Excellence in AI, IIT KGP. His work includes complex topics like Hierarchical Variational Autoencoders and diffusion-based models, showcasing his deep understanding and innovation in AI and machine learning.
  • Publications: Tuhin has multiple publications, including articles in respected journals and conferences. These publications reflect his ability to contribute valuable research to the field of AI and machine learning, which aligns well with the award’s focus on young researchers.
  • Technical Skills: His proficiency in various programming languages, tools, and libraries, combined with his experience in implementing complex models, indicates his strong technical foundation, crucial for cutting-edge research.

Areas for Improvement

  • Broader Impact: While Tuhin’s research is technically strong, he could focus on expanding the practical applications and societal impact of his work. Demonstrating how his research can solve real-world problems or benefit specific industries could strengthen his candidacy.
  • Leadership and Collaboration: Although Tuhin has mentored students and participated in team projects, further leadership roles or collaborative research endeavors could enhance his profile. Engaging in interdisciplinary projects or leading a research team could be beneficial.
  • Diversity of Experience: Tuhin’s experience is heavily concentrated in AI and machine learning. Diversifying his research portfolio by exploring related fields or integrating his AI expertise into other disciplines might provide a more well-rounded profile.

Education 

Tuhin Subhra De is currently pursuing a dual degree (B.Tech. and M.Tech.) in Civil and Environmental Engineering from the prestigious Indian Institute of Technology Kharagpur (IIT KGP), where he has maintained an impressive CGPA of 8.7/10.0. His academic journey at IIT KGP includes minors in Mathematics and Computing, and Artificial Intelligence Applications, reflecting his diverse interests and technical proficiency. Tuhin’s coursework encompasses a wide array of subjects, including Artificial Intelligence, Machine Learning, Deep Learning, Big Data Processing, and Secure AI/ML, providing him with a solid foundation in cutting-edge technologies. His strong background in Statistics, Probability, Linear Algebra, and Time Series Modeling further complements his technical expertise. Tuhin’s educational achievements are underscored by his active participation in prestigious competitive exams and Olympiads, where he ranked among the top percentile. His education at IIT KGP has equipped him with the skills and knowledge to excel in both academic and professional pursuits.

Experience  

Tuhin Subhra De has accumulated a wealth of experience through various internships and research roles. At the Center for Excellence in AI at IIT KGP, he is currently a Deep Learning Research Intern, focusing on improving text generation quality using diffusion and energy-based models. During his internship at Udaan.com, Tuhin successfully increased the customer order conversion rate by implementing predictive buying methods and advanced machine learning techniques, which led to a significant improvement in business outcomes. His role as a Machine Learning Research Intern at Deakin University involved applying knowledge distillation to enhance the performance of heterogeneous ML models, demonstrating his ability to innovate in complex environments. Tuhin’s early experiences also include an internship at the Indian Institute of Management Mumbai, where he developed methods to optimize profit in cargo acceptance, combining operations research with machine learning. His hands-on experience across various domains underscores his versatility and technical acumen.

Research Focus  

Tuhin Subhra De’s research focus lies at the intersection of artificial intelligence, machine learning, and data science, with a particular emphasis on deep learning models and their applications. His current research at the Center for Excellence in AI, IIT KGP, involves enhancing the quality of text generation using advanced models like Hierarchical Variational Autoencoders, diffusion models, and energy-based frameworks. Tuhin is also exploring the contrast in learning processes between different AI models, aiming to address challenges such as decoder collapse in generative tasks. His past research at Deakin University centered on knowledge distillation, where he worked on improving the accuracy of machine learning models by transferring knowledge between heterogeneous networks. Additionally, Tuhin’s work at Udaan.com involved developing predictive models that significantly boosted customer order conversion rates. His research is driven by a passion for solving real-world problems through innovative AI and ML techniques, making significant contributions to the field.

Publication Top Notes

A non-linear Lasso and explainable LSTM approach for estimating tail risk interconnectedness

A Machine learning and Empirical Bayesian Approach for Predictive Buying in B2B E-commerce

Prediction of Turn Around Time using Neural Networks – A Case Study of Shipping Port 

Conclusion

Tuhin Subhra De is a strong candidate for the Research for Young Scientist Award, given his academic excellence, significant research contributions, and technical expertise. To further enhance his application, he could focus on demonstrating the broader impact of his research, seeking leadership opportunities, and diversifying his experience. Overall, his profile is highly competitive for the award, reflecting his potential as a promising young scientist in the field of AI and machine learning.