Shib Shankar Golder is a seasoned technology leader with 19 years of experience in AI/ML, data platforms, ERP systems, Blockchain, Quantum, Edge and cloud computing. He excels in designing and implementing complex algorithms, scalable digital platforms, and data-driven solutions for strategic decision-making. Proficient in SAP, Snowflake, and Power BI, he has led large-scale projects across industries, including manufacturing, healthcare, and automotive. A collaborative leader and mentor, he has successfully managed global teams, delivering innovative solutions in customer experience, eCommerce, and data engineering. Shib combines technical expertise with strategic vision to drive business transformation and technological innovation.
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Scholarly Publications :
Date of Publication | Title of Scholarly Paper | Journal Name & Link |
February, 2025 | IEEE Explore | |
February, 2025 | IEEE Explore | |
February, 2025 | IEEE Explore | |
January, 2025 | Library Progress International | |
December, 2024 | IEEE Explore | |
September, 2024 | Journal of Computational Analysis and Applications | |
August, 2024 | ESP International Journal of Advancements in Computational Technology [ESP-IJACT] | |
July, 2024 | Library Progress International - bpasjournals | |
June, 2024 | International Journal of Intelligent Systems and Applications in Engineering (IJISAE) |
Top Project Contributions :
Year of Project | Project Name | Skills & Tools Covered | Project Details |
November, 2024 | Stock Market News Sentiment Analysis and Summarization - Generative AI | Large Language Models , Transformers , Prompt Engineering, Exploratory Data Analysis , Data Manipulation, Word Embeddings, Text Preprocessing | The prices of the stocks of companies listed under a global exchange are influenced by a variety of factors, with the company's financial performance, innovations and collaborations, and market sentiment being factors that play a significant role. News and media reports can rapidly affect investor perceptions and, consequently, stock prices in the highly competitive financial industry. With the sheer volume of news and opinions from a wide variety of sources, investors and financial analysts often struggle to stay updated and accurately interpret its impact on the market. As a result, investment firms need sophisticated tools to analyze market sentiment and integrate this information into their investment strategies.
Develop an an AI-driven sentiment analysis system that will automatically process and analyze news articles to gauge market sentiment, and summarizing the news at a weekly level to enhance the accuracy of their stock price predictions and optimize investment strategies. |
October, 2024 | Image classification using CNNs - Plant Seedlings Classification | Keras , CNN , Working With Images, Computer Vision | In recent times, the field of agriculture has been in urgent need of modernizing, since the amount of manual work people need to put in to check if plants are growing correctly is still highly extensive. Despite several advances in agricultural technology, people working in the agricultural industry still need to have the ability to sort and recognize different plants and weeds, which takes a lot of time and effort in the long term. The potential is ripe for this trillion-dollar industry to be greatly impacted by technological innovations that cut down on the requirement for manual labor, and this is where Artificial Intelligence can actually benefit the workers in this field, as the time and energy required to identify plant seedlings will be greatly shortened by the use of AI and Deep Learning. The ability to do so far more efficiently and even more effectively than experienced manual labor, could lead to better crop yields, the freeing up of human inolvement for higher-order agricultural decision making, and in the long term will result in more sustainable environmental practices in agriculture as well. |
August, 2024 | EDA, Data Preprocessing, Tensorflow, Keras, Artificial Neural Networks, Regularization | Analyze the customer data, build a neural network to help the operations team identify the customers that are more likely to churn, and provide recommendations on how to retain such customers. | |
July, 2024 |
Credit Card Users Churn Prediction - Advanced Machine Learning | EDA,RANDOM FOREST, Bagging, Boosting, SMOTE, Cross Validation, Data Preprocessing, Hyperparameter Tuning | Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it. |
June, 2024 | EDA, Data pre-processing, Model building - Decision Tree, Model Performance, Evaluation and Improvement, Business Recommendations | To identify bank customers with a high likelihood of purchasing a loan, you need to analyze the provided data to understand key customer attributes influencing loan acquisition. With this analysis, build a predictive model that captures patterns and customer characteristics, which will help the bank effectively target potential loan buyers, improving marketing efforts and increasing conversion rates. | |
May, 2024 | Python, Numpy, Pandas, Seaborn, Univariate analysis, Bivariate analysis, Exploratory Data Analysis, Business Recommendations | Perform an exploratory data analysis and provide actionable insights for a food aggregator company to get a fair idea about the demand of different restaurants and cuisines, which will help them enhance their customer experience and improve the business. |
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