Silpaja Chandrasekar

Ph.D. in Computer Science

Computer Science, Medical Image Analysis, Cancer Cell Detection

Dr. Silpaja Chandrasekar has a Ph.D. in Computer Science from Anna University, Chennai. Her research expertise lies in analyzing traffic parameters under challenging environmental conditions. Additionally, she has gained valuable exposure to diverse research areas, such as detection, tracking, classification, medical image analysis, cancer cell detection, chemistry, and Hamiltonian walks.

Dr. Silpaja commenced her career as a Programmer Analyst Trainee at CTS (Cognizant Technology Solutions). Later, she ventured into research and served as a Research Associate in the Department of Chemistry at IIT (Indian Institute of Technology) Madras. Her passion for research led her to become a full-time research scholar in the field. Additionally, Silpaja embraced the joy of teaching as an Assistant Professor at Sri Venkateswara College of Engineering, Chennai.

Silpaja’s research experience has honed her skills in writing manuscripts, news articles, and reviews. Moreover, she has actively participated as a peer reviewer for many journals. After taking a break to raise her two daughters, Silpaja is now eager to re-immerse herself in the realms of learning, research, and writing. She finds joy in cooking and spending quality time with her daughters. At present, she is a Tech writer in the field of Artificial Intelligence.

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Articles from Silpaja

Analyzing AI Educational Curricula and Textbooks: A Text Mining Approach

This research paper explores the intersection of artificial intelligence (AI) and education by analyzing AI educational curricula and textbooks using text mining techniques. The study assesses the presence of key AI concepts, topic structures, and practical tools, offering valuable insights for structuring effective AI curricula and improving alignment with educational resources.

7 Sep 2023

Revolutionizing Early Parkinson's Disease Detection: A Hybrid CNN-LSTM Model

This study presents a groundbreaking hybrid model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for the early detection of Parkinson's Disease (PD) through speech analysis. The model achieved a remarkable accuracy of 93.51%, surpassing traditional machine learning approaches and offering promising advancements in medical diagnostics and patient care.

7 Sep 2023

AI Adoption in Academic Libraries: A Comparative Study of UK and Chinese Universities

This research delves into the adoption of Artificial Intelligence (AI) in academic libraries, comparing the approaches of top universities in the United Kingdom (UK) and China. The study highlights that while Chinese universities emphasize AI in their strategies, British universities exhibit caution, with a limited focus on AI applications in libraries, and underscores the need for careful consideration of AI's role in higher education libraries, taking into account factors such as funding, value, and ethics.

7 Sep 2023

AI-Powered Monkeypox Diagnosis: Optimizing Accuracy and Speed

This paper presents a Convolutional Neural Network (CNN) approach for classifying monkeypox skin lesions, enhanced by the Grey Wolf Optimizer (GWO). By improving accuracy and efficiency, this method aids in early disease detection, benefiting patient outcomes and public health by controlling outbreaks.

6 Sep 2023

Revolutionizing Animation Creation: AI-Powered Digital Characters

Researchers explore the fusion of artificial intelligence, natural language processing, and motion capture to streamline 3D animation creation. By integrating Chat Generative Pre-trained Transformer (ChatGPT) into the process, it enables real-time language interactions with digital characters, offering a promising solution for animation creators.

6 Sep 2023

BARD, ChatGPT, and Watson in Jeopardy!: A Question-Answering Showdown

A deep dive into the performance of BARD, ChatGPT, and Watson on Jeopardy! questions reveal their expertise but also their struggle with disambiguating complex queries. This study underscores the importance of innovative testing methods and considerations for answer reproducibility in evaluating AI language models.

5 Sep 2023

Securing Food Supply Chains with AI and Federated Learning

Researchers demonstrate the potential of Artificial Intelligence (AI) and Federated Learning (FL) to predict and prevent food fraud while preserving data privacy in complex supply chains. Their framework, utilizing a data-driven Bayesian Network model, effectively integrated data from various sources and improved decision-making regarding food fraud control while upholding data confidentiality.

5 Sep 2023

How is AI Used in Healthcare Diagnosis?

This comprehensive article explores the significant role of artificial intelligence (AI) in healthcare diagnosis, highlighting its applications, benefits, and the various AI methods employed in the medical field. It also discusses the challenges faced in implementing AI, including data quality, regulatory compliance, and ethical concerns, and emphasizes the importance of transparency and ethical frameworks for the responsible use of AI in healthcare.

4 Sep 2023

What is AI’s Role in Gaming?

This article delves into the profound impact of artificial intelligence (AI) on the gaming industry, from enhancing gameplay and character behavior to generating diverse game content. It explores various applications of AI in gaming, the methods used, and the challenges developers face. The article concludes with a glimpse into the future of AI-driven gaming and the potential for continued innovation and growth in this dynamic field.

4 Sep 2023

Enhancing Flight Trajectory Prediction with Wavelet Transform and Neural Architecture

Researchers present the Wavelet Transform-based Flight Trajectory Prediction (WTFTP) framework, which employs time-frequency analysis and an innovative encoder-decoder neural architecture to improve the accuracy of aircraft trajectory prediction. The results demonstrate superior performance, particularly in maneuver control scenarios, and highlight the potential of time-frequency analysis in enhancing flight trajectory forecasting.

1 Sep 2023