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

Using AI to Advance Air Traffic Control Communication Transcription

Researchers discuss the ATCO2 project, which aims to improve air traffic control (ATC) communications through artificial intelligence (AI). The project provides open-sourced data, including over 5,000 hours of transcribed communications, and achieves a 17.9% Word Error Rate on public ATC datasets. The paper highlights the challenges of data scarcity in ATC, the data collection platform, ASR technology, and the potential for Natural Language Understanding (NLU) in air traffic management.

25 Oct 2023

Influence of Visual Information and Voice Assistants on Sustainable Clothing Shopping

Researchers examined the impact of visual information and the perceived intelligence of voice assistants on consumers' purchasing behavior in online sustainable clothing shopping. Their findings highlight the importance of positive attitudes toward sustainable fashion and the role of AI-driven voice assistants.

25 Oct 2023

Efficient Radar-Based Human Activity Recognition with Lightweight Hybrid Vision Transformer

Researchers introduced the Lightweight Hybrid Vision Transformer (LH-ViT) network for radar-based Human Activity Recognition (HAR). LH-ViT combines convolution operations with self-attention, utilizing a Residual Squeeze-and-Excitation (RES-SE) block to reduce computational load. Experimental results on two human activity datasets demonstrated LH-ViT's advantages in expressiveness and computing efficiency over traditional approaches.

25 Oct 2023

Role of AI in Health Monitoring Wearables

This article explores the pivotal role of Artificial Intelligence (AI) in health monitoring wearables, emphasizing its potential to revolutionize healthcare. AI-powered wearables enable real-time health tracking, early disease detection, and personalized health insights, promoting proactive health management and remote patient care.

24 Oct 2023

Innovative Robot Arm Motion Control: An Inner Rehearsal-Based Approach

Researchers have introduced a novel robot arm motion control approach inspired by human cognitive mechanisms. This inner rehearsal-based method enhances robot arm-reaching precision by employing a two-stage learning process for internal models and integrating visual feedback, resulting in smoother and more efficient motion trajectories.

23 Oct 2023

IoT-Based System for Recognizing Negative Emotions Using Multimodal Biosignal Data

Researchers have introduced an innovative IoT-based system for recognizing negative emotions, such as disgust, fear, and sadness, using multimodal biosignal data from wearable devices. This system combines EEG signals and physiological data from a smart band, processed through machine learning, to achieve high accuracy in emotion recognition.

23 Oct 2023

Synchronized Talking Face Video Generation Using GANs and Time-Frequency Features

This research presents an innovative method called TF2 for generating synchronized talking face videos driven by speech audio. The system utilizes generative adversarial networks (GANs) and a Multi-level Wavelet Transform (MWT) to transform speech audio into different frequency domains, improving the realism of the generated video frames.

20 Oct 2023

Enhancing Glycemic Control in Type I Diabetes with Offline Reinforcement Learning

This research focuses on improving closed-loop systems for type I diabetes glycemic control using offline Reinforcement Learning (RL) agents trained on actual patient data. The study shows that these RL agents outperform existing behavior policies, enhancing glycemic control in challenging cases, with the potential to adapt to real-world patient scenarios.

20 Oct 2023

Interactive Task Planning with Language Models

Researchers introduced an interactive robot framework that leverages Large Language Models (LLMs) to excel in long-term task planning, adapting to new goals and tasks during execution. The system seamlessly integrates high-level planning and low-level execution using language, demonstrating robustness and adaptability across tasks.

19 Oct 2023

Predicting Future AI Research Directions with AI and Network Features

Researchers introduced the Science4Cast benchmark to forecast future AI research, emphasizing the importance of network features for precise predictions. This approach offers a promising tool to accelerate scientific progress in artificial intelligence.

19 Oct 2023

Silpaja Chandrasekar

Articles from Silpaja

Using AI to Advance Air Traffic Control Communication Transcription

Influence of Visual Information and Voice Assistants on Sustainable Clothing Shopping

Efficient Radar-Based Human Activity Recognition with Lightweight Hybrid Vision Transformer

Role of AI in Health Monitoring Wearables

Innovative Robot Arm Motion Control: An Inner Rehearsal-Based Approach

IoT-Based System for Recognizing Negative Emotions Using Multimodal Biosignal Data

Synchronized Talking Face Video Generation Using GANs and Time-Frequency Features

Enhancing Glycemic Control in Type I Diabetes with Offline Reinforcement Learning

Interactive Task Planning with Language Models

Predicting Future AI Research Directions with AI and Network Features

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