Susha Cheriyedath

Feature Writer

B.Sc Chemistry, M.Sc. Biochemistry

Susha is a scientific communication professional holding a Master's degree in Biochemistry, with expertise in Microbiology, Physiology, Biotechnology, and Nutrition. After a two-year tenure as a lecturer from 2000 to 2002, where she mentored undergraduates studying Biochemistry, she transitioned into editorial roles within scientific publishing. She has accumulated nearly two decades of experience in medical communication, assuming diverse roles in research, writing, editing, and editorial management.

Passionate about health and nutrition, Susha is interested in various diet types, such as veganism, and their impact on the body and metabolism. She remains dedicated to staying current with the latest developments in the medical and health science fields. In her leisure time, she engages in gardening, cooking/baking, and sketching/painting. When not immersed in work, she can often be found tending to her garden (weather permitting) or engrossed in her sketching and painting projects.

Articles from Susha

AI-Powered Detection of Partial Discharge in Ceramic Insulators

This research pioneers the use of acoustic emission and artificial neural networks (ANN) to detect partial discharge (PD) in ceramic insulators, crucial for electrical system reliability. With a focus on defects caused by environmental factors, the study achieved a 96.03% recognition rate using ANNs, further validated by support vector machine (SVM) and K-nearest neighbor (KNN) algorithms, showcasing a significant advancement in real-time monitoring for electrical power network safety.

24 Jan 2024

Enhancing Railroad Safety: RailFOD23 Dataset for Foreign Object Detection

Scientists present a pioneering approach to address the scarcity of datasets for foreign object detection on railroad power transmission lines. The article introduces the RailFOD23 dataset, comprising 14,615 images synthesized through a combination of manual and AI-based methods, providing a valuable resource for developing and benchmarking artificial intelligence models in the critical domain of railway safety.

23 Jan 2024

Machine Learning Revolutionizes Division-1 Women's Basketball Performance Analysis

This groundbreaking article presents a comprehensive three-tiered approach, utilizing machine learning to assess Division-1 Women's basketball performance at the player, team, and conference levels. Achieving over 90% accuracy, the predictive models offer nuanced insights, enabling coaches to optimize training strategies and enhance overall sports performance. This multi-level, data-driven methodology signifies a significant leap in the intersection of artificial intelligence and sports analytics, paving the way for dynamic athlete development and strategic team planning.

19 Jan 2024

Polar Sea Ice Detection Using Rotating Fan Beam Scatterometers

Researchers explored the effectiveness of a rotating fan beam scatterometer, specifically the China France Oceanography Satellite scatterometer (CSCAT), for polar sea ice detection. They developed a Bayesian algorithm that leverages CSCAT's multiple incidence angles and dual polarization characteristics to accurately detect sea ice.

25 Oct 2023

FACTCHD: Detecting Fact-Conflicting Hallucinations in Large Language Models

Researchers have introduced FACTCHD, a framework for detecting fact-conflicting hallucinations in large language models (LLMs). They developed a benchmark that provides interpretable data for evaluating the factual accuracy of LLM-generated responses and introduced the TRUTH-TRIANGULATOR framework to enhance hallucination detection.

23 Oct 2023

Predicting 10-Day Maximum Temperatures Using Machine Learning

This article discusses the application of machine learning models to predict anomalies in daily maximum temperatures in India from March to June. The study evaluates various machine learning models and identifies an optimal model, emphasizing its effectiveness in forecasting extreme temperature events, with the potential to complement numerical weather prediction models.

13 Oct 2023

AI in the Mortgage Market: A Framework for Equitable Homeownership Access

Researchers present the "SCALE" framework, which evaluates the impact of AI on the mortgage market, with a focus on promoting homeownership inclusivity for marginalized communities. The framework encompasses societal values, contextual integrity, accuracy, legality, and expanded opportunity, aiming to address concerns about bias and discrimination in AI applications within the mortgage industry while advancing fair lending practices and social equity in homeownership.

12 Oct 2023

Artificial Muses: Comparing Human and Generative AI Chatbots in Creativity

This study delves into the ongoing debate about whether Generative Artificial Intelligence (GAI) chatbots can rival human creativity. The findings indicate that GAI chatbots can generate original ideas comparable to humans, emphasizing the potential for synergy between humans and AI in the creative process, with chatbots serving as valuable creative assistants.

11 Oct 2023

AI Revolutionizes Athlete Selection in Wrestling

In a groundbreaking study, AI-driven data analysis accurately predicts Greco-Roman wrestlers' competitive success, with just an 11% error rate. This research has the potential to revolutionize athlete selection and training in various sports, offering valuable insights for coaches and athletes alike.

10 Oct 2023

LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

This research explores the application of Large Language Models (LLMs) as decision-making components in autonomous driving (AD) systems, addressing challenges in understanding complex driving scenarios. The LLMs, equipped with reasoning skills, enhance the AD system's adaptability and transparency, effectively handling intricate driving situations, and offering a promising direction for future developments in this field.

9 Oct 2023