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

NOIR: A Brain-Robot Interface for Versatile Human-Robot Collaboration

Researchers have introduced the Neural Signal Operated Intelligent Robots (NOIR) system, a groundbreaking brain-robot interface that allows individuals to control robots using their brain signals. The NOIR system combines modular brain decoding with parameterized robot skills and learning to empower users to perform complex everyday tasks efficiently.

7 Nov 2023

Deep Learning for Sheep Loin CT Image Segmentation

This study explores the application of deep learning models to segment sheep Loin Computed Tomography (CT) images, a challenging task due to the lack of clear boundaries between internal tissues. The research evaluates six deep learning models and identifies Attention-UNet as the top performer, offering exceptional accuracy and potential for improving livestock breeding and phenotypic trait measurement in living sheep.

5 Nov 2023

LLaVA-Interactive: A Versatile Multimodal Human and AI Interaction Prototype

Researchers introduce LLaVA-Interactive, an innovative multimodal human and artificial intelligence (AI) interaction prototype. This system enables users to engage in multi-turn dialogues and interact through visual and language prompts, offering diverse applications, from content creation to culinary guidance, and inspiring future research in multimodal interactive systems.

5 Nov 2023

Hierarchical Generative Modeling for Autonomous Robot Control Inspired by Human Motor Control

Researchers have explored the use of hierarchical generative modeling to mimic human motor control, enabling autonomous task completion in a humanoid robot. Through extensive physics simulations, they demonstrated the feasibility and effectiveness of this approach, showcasing its potential for complex tasks involving locomotion, manipulation, and grasping, even under challenging conditions.

5 Nov 2023

Enhancing Human-AI Interactions in Decision Support: A Systematic Review

This research article underscores the importance of aligning AI outputs with human expectations in decision support systems and introduces the concept of Explainable AI (XAI). A systematic review results in a taxonomy of interaction patterns, emphasizing the need for more interactive functionality in AI systems.

3 Nov 2023

Impact of Audio Quality, Familiarity, and Response Bias in Voice Recognition on Zoom

Researchers investigate the impact of audio quality, especially in video conferencing (Zoom), on human voice recognition. Findings suggest that Zoom and studio-quality audio outperform telephone audio, and listeners familiarized with Zoom audio trend towards improved recognition, highlighting the potential advantages of Zoom's speech coding mechanisms.

3 Nov 2023

Integrating IoT Technology for Efficient Load Management in Residential Distribution Systems

Researchers introduce an innovative framework that integrates Internet of Things (IoT) technology, particularly IoT windows and occupant behavior, into residential distribution systems to enhance load management and conserve energy. The study highlights the potential of IoT-based load optimization, discusses its impact on distribution operations and underscores the importance of coordination for aligning IoT-enabled household energy consumption with rooftop photovoltaic generation in intelligent grid systems for improved sustainability.

2 Nov 2023

IoT-Integrated Drone Cybersecurity: Using DL and ML for Intrusion Detection

This paper explores the integration of IoT with drone technology to enhance data communication and security across various industries, including agriculture and smart cities. The study focuses on the use of machine learning and deep learning techniques to detect cyberattacks within drone networks and presents a comprehensive framework for intrusion detection.

2 Nov 2023

Evaluating Language Models with SKILL-MIX: A Novel Approach

This article discusses a novel evaluation method called "SKILL-MIX" for assessing the capabilities of Large Language Models (LLMs). SKILL-MIX challenges LLMs by generating text that combines random subsets of skills and topics, providing a more comprehensive assessment of their abilities, and addresses the limitations of traditional evaluation methods in the evolving landscape of language models.

1 Nov 2023

AI Revolutionizes Biodiversity Conservation and Monitoring

Researchers highlight the increasing role of artificial intelligence (AI) in biodiversity preservation and monitoring. AI is shown to be a powerful tool for efficiently processing vast datasets, identifying species through audio recordings, and enhancing conservation efforts, though concerns about its environmental impact must be addressed.

1 Nov 2023