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

Predicting Gait Quality Progression Using Neural Networks

This study introduces an AI-based system predicting gait quality progression. Leveraging kinematic data from 734 patients with gait disorders, the researchers explore signal and image-based approaches, achieving promising results with neural networks. The study marks a pioneering application of AI in predicting gait variations, offering insights into future advancements in this critical domain of healthcare.

3 Jan 2024

The Impact of AI in the Service Robot Sector

The integration of Artificial Intelligence (AI) into service robots has sparked a revolutionary transformation across diverse industries, reshaping task completion and service delivery. From healthcare to agriculture, these robots, equipped with AI algorithms, enhance efficiency, accuracy, and overall productivity. The convergence of AI and robotics has ushered in a new era of automation, propelling machines to emulate human-like capabilities, offering a glimpse into a future where machines actively collaborate to enhance human experiences.

2 Jan 2024

AI-based Grading and Assessment

This exploration delves into the rapid transformation of grading and assessment systems through the integration of Artificial Intelligence (AI). It traces the evolution of assessment methodologies, highlighting the advantages and challenges of AI-driven grading. The article emphasizes the efficiency, objectivity, and personalized learning experiences enabled by AI, while addressing ethical considerations such as privacy, algorithm bias, and the need for contextual understanding.

2 Jan 2024

The Impact of AI in Connected Cars

This exploration delves into the transformative integration of artificial intelligence (AI) in connected cars, revolutionizing the automotive industry. The essay traces the evolution of connected cars, highlighting AI applications that enhance safety, enable predictive maintenance, personalize driving experiences, optimize traffic management, and analyze driver behavior. It addresses challenges such as data privacy and ethical dilemmas, emphasizing the need for robust regulatory frameworks.

30 Dec 2023

Unveiling Insights into Behavioral Analytics Using AI

This essay explores the profound impact of artificial intelligence (AI) on human behavior through the lens of behavioral analytics. It delves into the core components of behavioral analytics, highlighting its applications in marketing, healthcare, cybersecurity, and more. The essay addresses the challenges and ethical considerations associated with AI-powered behavioral analytics, emphasizing the need for transparency, fairness, and responsible deployment.

30 Dec 2023

The Power of AI in Virtual Classrooms

The integration of Artificial Intelligence (AI) in virtual classrooms has revolutionized education, offering personalized learning paths, intelligent tutoring systems, and enhanced engagement. This article explores the evolution of virtual classrooms, applications of AI, and the benefits it brings, emphasizing the importance of a balanced approach that combines technological advancements with the human touch. As AI continues to shape the future of education, it holds the potential to bridge gaps, enhance accessibility, and create a more inclusive learning ecosystem.

30 Dec 2023

What are Long Short-Term Memory Networks?

This article delves into the significance of Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks, in comprehending sequences of information. It discusses their expertise in recognizing patterns, connections, and complexities within vast datasets, highlighting their pivotal role in natural language processing, time series analysis, and speech recognition.

30 Dec 2023

AI's Evolution in Language Translation

Artificial Intelligence (AI) has reshaped language translation, progressing from traditional methods reliant on human expertise to AI-driven systems harnessing neural networks and deep learning. AI's influence revolutionizes communication, offering nuanced, contextually sensitive translations, bridging global divides. However, challenges like cultural nuances and ethical considerations persist. Despite this, ongoing research aims to enhance AI's capabilities, fostering inclusive, accurate, and real-time translations, promising a more connected global community.

27 Dec 2023

AI's Impact on Medical Robots

The integration of Artificial Intelligence (AI) into medical robots has revolutionized healthcare, enhancing diagnostics, treatment methodologies, surgical procedures, and patient care. These intelligent machines, equipped with advanced algorithms, offer precision and efficiency, ushering in a new era of healthcare. However, ethical considerations, including patient data protection, safety guidelines compliance, and accountability, present challenges that require careful resolution as these technologies advance.

27 Dec 2023

Naive Bayes: An Effective Classifier in Machine Learning

Naive Bayes, a foundational probabilistic classifier in machine learning, derives its effectiveness from assuming feature independence. Despite its "naive" label, it remains remarkably efficient, particularly in scenarios with large datasets and real-time applications. The algorithm's adaptability is evident in various types, such as Multinomial, Gaussian, Bernoulli, and Complementary Naive Bayes, each suited to different data types and classification challenges.

27 Dec 2023