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

Advancing Land Resource Management: A Comprehensive Evaluation Model

The article introduces a groundbreaking evaluation model for LRCC, combining entropy weight and cloud similarity, validated through empirical analysis and a Chongqing case study, offering insights for sustainable land planning and development practices.

1 May 2024

Using ML to Predict Anemia Among Young Girls in Ethiopia

Researchers utilized machine learning algorithms to predict anemia prevalence among young girls in Ethiopia, analyzing data from the 2016 Ethiopian Demographic and Health Survey. The study identified socioeconomic and demographic predictors of anemia and highlighted the efficacy of advanced ML techniques, such as random forest and support vector machine, in forecasting anemia status.

30 Apr 2024

Security Challenges in IoT: Safeguarding Connected Devices

As IoT technology proliferates, safeguarding connected devices is crucial to prevent cyber threats and ensure data privacy and operational integrity. Addressing security challenges like device diversity and interconnectivity vulnerabilities requires robust measures such as authentication, encryption, and network segmentation.

29 Apr 2024

Advanced ML Approach for Extracting Pairing Glue Functions from Optical Spectra

Researchers introduce the regularized recurrent inference machine (rRIM), a novel ML method integrating physical principles for extracting pairing glue functions from optical spectra in superconductivity research. The rRIM offers robustness to noise, flexibility with out-of-distribution data, and reduced data requirements, bridging gaps in understanding complex physical phenomena.

29 Apr 2024

Autonomous Molecular Crawlers for Spatial Analysis via DNA Nanotechnology

Researchers introduced molecular robotic crawlers utilizing DNA-based artificial motors to autonomously survey molecular environments and report spatial information. These crawlers, operating at the nanoscale, demonstrated the ability to count subunits in molecular complexes and detect multivalent proximities, facilitating the creation of detailed molecular interaction maps inside cells.

26 Apr 2024

Real-Time Safety Helmet Detection with Improved YOLOv5 Algorithm

Researchers introduced enhancements to the YOLOv5 algorithm for real-time safety helmet detection in industrial settings. Leveraging FasterNet, Wise-IoU loss function, and CBAM attention mechanism, the algorithm achieved higher precision and reduced computational complexity. Experimental results demonstrated superior performance compared to existing models, addressing critical safety concerns and paving the way for efficient safety management systems in construction environments.

25 Apr 2024

Exploring Noise in Machine Commonsense Reasoning Benchmarks

Researchers conducted a noise audit on human-labeled benchmarks for machine commonsense reasoning (CSR), revealing significant levels of noise across different experimental conditions and datasets. The study emphasized the impact of noise on performance estimates of CSR systems, challenging the reliance on single ground truths in AI benchmarking practices and advocating for more nuanced evaluation methodologies.

24 Apr 2024

Enhancing Security Scanning with Infrared Thermography and CNNs

This study in Nature explores the application of convolutional neural networks (CNNs) in classifying infrared (IR) images for concealed object detection in security scanning. Leveraging a ResNet-50 model and transfer learning, the researchers refined pre-processing techniques such as k-means and fuzzy-c clustering to improve classification accuracy.

23 Apr 2024

IoT and Smart Homes: Enhancing Comfort and Security

The fusion of Internet of Things (IoT) technology with smart homes has ushered in a new era of comfort and security. From automated systems to AI integration, smart homes have evolved into intelligent living spaces, enhancing convenience and safety for occupants.

23 Apr 2024

The MPDB Dataset: Exploring Driving Behavior with Multimodal Physiological Data

Researchers present the MPDB dataset, capturing physiological responses of 35 participants during a driving simulator experiment. Combining EEG, ECG, EMG, GSR, and eye-tracking data with driving behaviors, the dataset offers insights into human cognitive functions while driving. Detailed collection methods, storage structures, and validation procedures ensure the dataset's reliability and effectiveness in studying driver behavior, paving the way for advancements in traffic psychology and behavior modeling.

22 Apr 2024