Soham Nandi

Computer Science Engineering, specializing in Artificial Intelligence and Machine learning

Soham Nandi is a technical writer based in Memari, India. His academic background is in Computer Science Engineering, specializing in Artificial Intelligence and Machine learning. He has extensive experience in Data Analytics, Machine Learning, and Python. He has worked on group projects that required the implementation of Computer Vision, Image Classification, and App Development.

Soham's passion for AI and Machine Learning propels him toward his goal of becoming a distinguished Machine Learning Engineer and leveraging his knowledge to help the less fortunate. His projects include the Rice grain classifier and Handwriting-based Personality Detector, and he is certified in Data Analytics and Data Science.

Drawing inspiration from writers ranging from Satyajit Ray to Mark Manson, he has his own science fiction stories and blog. He also creates content on personal development and mental health through his Instagram handle. Beyond the screen and code, Soham's world is filled with music. With the ability to play the guitar, ukulele, and drums, he rocks to the tunes of the metal and rock genres, using music as a creative outlet, planning to start a band of his own.

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Articles from Soham

Optimizing Wastewater Treatment with Machine Learning

A study in Desalination and Water Treatment employed machine learning models to predict chemical oxygen demand (COD), biological oxygen demand (BOD), and suspended solids (SS) at the AlHayer wastewater treatment plant in Saudi Arabia.

18 Jun 2024

AI Enhances Power Grid Efficiency and Reliability

Researchers reviewed AI advancements in electric power systems, highlighting its transformative potential due to modern microprocessors and data storage. The study categorizes AI applications into four areas and presents detailed case studies in wind power forecasting, smart grid security, and fault detection.

17 Jun 2024

Reinforcement Learning Boosts Factory Layout Optimization

Researchers developed a novel framework integrating production simulation and reinforcement learning to optimize factory layouts, focusing on equipment placement, logistics paths, and AGV utilization. This multilayered approach significantly increased throughput, reduced logistics distances, and minimized AGV usage, offering a flexible and efficient solution for dynamic manufacturing environments.

14 Jun 2024

Enhancing Smart Grid Resilience Using AI Models

Researchers introduced a graph reinforcement learning model to manage power outages in smart grids, utilizing a capsule-based graph neural network for optimized real-time control policies.

14 Jun 2024

Weed Classification in Precision Farming

Researchers compared traditional feature-based computer vision methods with CNN-based deep learning for weed classification in precision farming, emphasizing the former's effectiveness with smaller datasets

12 Jun 2024

How can AI Assist in Decision Making?

Artificial Intelligence (AI) is revolutionizing decision-making processes across various domains by providing insightful, accurate, and efficient support, enhancing both personal and professional choices.

11 Jun 2024

AI Dataset Revolutionizes Emergency Evacuation

Researchers have introduced the human behavior detection dataset (HBDset) for computer vision applications in emergency evacuations, focusing on vulnerable groups like the elderly and disabled.

11 Jun 2024

Bridging Patterns and Outliers in AI

Researchers explored the integration of pattern recognition with outlier detection using advanced algorithms, suggesting emotions to enhance AI decision-making. They proposed the Integrated Growth (IG) and pull anti algorithms to improve outlier detection by treating outliers as intrinsic parts of patterns, enhancing data analysis accuracy and comprehensiveness.

10 Jun 2024

Advancing Energy Modeling with AI Synergy

A review in Energy Strategy Reviews examines the integration of meta-heuristic (MH) algorithms and deep learning (DL) for energy modeling, showcasing advancements from 2018 to 2023. The proposed framework enhances predictive accuracy and optimization efficiency by leveraging MH's optimization strengths and DL's pattern recognition capabilities.

7 Jun 2024

Accent Classification with Deep Learning Models

A study introduces advanced deep learning models integrating DenseNet with multi-task learning and attention mechanisms for superior English accent classification. MPSA-DenseNet, the standout model, achieved remarkable accuracy, outperforming previous methods.

6 Jun 2024