Muhammad Osama

BTech(MechEng)

Mechanical Engineering with specialization in AI & Robotics

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence. Muhammad has worked on various research projects related to data analytics, machine learning, and deep learning for industries such as retail, medical, finance, agriculture, and Ed-Tech. He is enthusiastic and passionate about Artificial Intelligence-related research. Outside of work, he enjoys learning about new developments across all the fields related to science, technology, engineering, mathematics, and statistics.

Articles from Muhammad

AudioSeal: Detecting AI-Generated Speech with Precision

AudioSeal introduces a novel watermarking method tailored for pinpointing AI-generated speech in audio files, ensuring robust detection and localization capabilities down to the sample level, thus bolstering audio authenticity and security.

25 Jun 2024

NLP Approach for Improving Green Building Certification

Researchers analyzed multiple green building certification systems worldwide, evaluating their operational, embodied, and whole life cycle assessment (OEW) credits. Findings highlighted inconsistencies in credit prioritization and methodologies, proposing a framework for enhancing system effectiveness through standardized approaches and increased focus on circular economy principles and waste reduction.

24 Jun 2024

AI Models Enhance Energy Efficiency in Desert Climates

Researchers developed and compared three AI models to estimate energy consumption in residential buildings in desert climates, identifying key factors influencing energy use. The study highlights AI's potential to improve energy efficiency and sustainability in the built environment.

21 Jun 2024

Computer Vision for Aircraft Attitude Estimation

Researchers have developed a markerless computer vision method to measure aircraft model attitudes during dynamic wind tunnel testing, providing accurate estimations without altering aerodynamic properties. This novel technique, validated through simulations and real-world data, significantly improves accuracy over traditional methods and offers versatility for various aircraft designs and applications.

20 Jun 2024

Hybrid AI Model Boosts Particle Identification in Physics

Researchers introduced "DeepRFreg," a hybrid model combining deep neural networks and random forests, significantly enhancing particle identification (PID) in high-energy physics experiments. This innovation improves precision and reduces misidentification in particle detection.

19 Jun 2024

Evaluating GUI Assistants with Video-Based Benchmarks

Researchers introduced VideoGUI, a novel benchmark evaluating GUI assistants on complex, visual-centric tasks derived from high-quality web instructional videos. Their study highlights the limitations of current state-of-the-art models and offers detailed evaluation metrics for advancing GUI automation.

18 Jun 2024

Machine Learning Boosts Rainfall Prediction Accuracy

Researchers have developed an advanced machine learning model utilizing long short-term memory (LSTM) to improve the accuracy of predicting extreme rainfall events in Rwanda. This model offers significant insights for climate adaptation and disaster management, especially amid escalating severe weather conditions.

17 Jun 2024

Predicting Upper Secondary Education Dropout Using Machine Learning

In a study published in Scientific Reports, researchers used machine learning to predict upper secondary education dropout with high accuracy. By analyzing comprehensive data from kindergarten to Grade 9, the study identified key factors influencing dropout, enabling early intervention strategies to support at-risk students.

14 Jun 2024

AI Enhances Thin Section Image Annotation

Researchers developed the SACA-StyleGAN method to generate and semi-automatically annotate cast thin section images of tight oil reservoirs. This approach significantly improves data diversity, image quality, and annotation efficiency, offering a promising solution for geological analysis and exploration.

13 Jun 2024

GPT-4 Enhances Japanese Essay Scoring

A recent study found GPT-4 superior in assessing non-native Japanese writing, outperforming conventional AES tools and other LLMs. This advancement promises more accurate, unbiased evaluations, benefiting language learners and educators alike.

12 Jun 2024