Dr. Sampath Lonka

Ph.D, Mathematics

Large Language Models (LLM), Natural Language Processing (NLP), Deep Learning, Data Science, Calculus

Dr. Sampath Lonka is a scientific writer based in Bangalore, India, with a strong academic background in Mathematics and extensive experience in content writing. He has a Ph.D. in Mathematics from the University of Hyderabad and is deeply passionate about teaching, writing, and research.

Sampath enjoys teaching Mathematics, Statistics, and AI to both undergraduate and postgraduate students. What sets him apart is his unique approach to teaching Mathematics through programming, making the subject more engaging and practical for students.

Sampath works in various fascinating research areas, including Natural Language Processing, Deep Learning, Topological Data Analysis, and AI for Mathematics. He has developed several impactful Computer Vision and Language Models that effectively tackle real-world problems. These research interests and work reflect Sampath's commitment to exploring the intersections of mathematics and cutting-edge technologies.

Beyond the professional realm, Sampath has diverse interests and enjoys reading captivating literature, embarking on adventurous travels, and experimenting with culinary delights in the kitchen.

Sampath's unwavering passion for mathematics, expertise in AI, and dedication to nurturing young minds comes from his unique blend of academic knowledge, research accomplishments, and teaching experience.

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Articles from Sampath

Optimizing Radiomics: Unveiling Algorithm Combinations for Stable Performance

This study delves into the world of radiomics, evaluating the impact of different methods and algorithms on model performance across ten diverse datasets. The research highlights the key factors influencing radiomic performance and provides insights into optimal combinations of algorithms for stable results, emphasizing the importance of careful modeling decisions in this field.

1 Sep 2023

Vehiclectron: Monovision Sensor-Based 3D Vehicle Dimension Estimation

Researchers introduce Vehiclectron, a novel approach for precise 3D vehicle dimension estimation using monovision sensors and road geometry. This cost-effective solution utilizes object detection and core vectors to accurately estimate vehicle dimensions, offering potential applications in intelligent transportation systems and traffic flow management.

1 Sep 2023

VideoCutLER: Advancing Unsupervised Video Instance Segmentation

Researchers introduce VideoCutLER, an innovative unsupervised technique for multi-instance segmentation and tracking in videos. By leveraging synthetic video generation and a novel three-step process, VideoCutLER outperforms optical flow-based methods and achieves remarkable performance in video instance segmentation benchmarks.

31 Aug 2023

From Classrooms to Smart Universities: AI’s role in Transforming Higher Education

Researchers discuss how artificial intelligence (AI) is reshaping higher education. The integration of AI in universities, known as smart universities, enhances efficiency, personalization, and student experiences. However, challenges such as job displacement and ethical considerations require careful consideration as AI's transformative potential in education unfolds.

31 Aug 2023

Enhancing Recommender Systems with Fuzzy Logic and Label Vectors

A recent paper in PLOS ONE introduces an innovative method to improve the ranking and predictive accuracy of recommender systems. By incorporating fuzzy logic and user attribute-based label vectors, the proposed algorithms outperform classical methods in terms of rating prediction accuracy and recommendation list quality.

30 Aug 2023

Neural Networks Drive Robotic Cars to Victory in Autonomous Racing

Researchers present an AI-driven solution for autonomous cars, leveraging neural networks and computer vision algorithms to achieve successful autonomous driving in a simulated environment and real-world competition, marking a significant step toward safer and efficient self-driving technology.

30 Aug 2023

Unlocking Multimodal Understanding: Qwen-VL Models for Vision-Language Interaction

New research dives into the cutting-edge realm of Qwen vision-language (Qwen-VL) models, a groundbreaking fusion of large language models (LLMs) and vision encoders designed to bridge the gap between text and images. These models transcend traditional language boundaries by collectively comprehending and perceiving both text and visual cues, promising revolutionary advances in fields ranging from image captioning to real-world behavior analysis.

29 Aug 2023

Unlocking Clear Communication: D2StarGAN for Speech Intelligibility Enhancement

Researchers explore the innovative D2StarGAN model, a cutting-edge deep learning solution designed to enhance speech intelligibility in noisy environments. They also discuss how this framework leverages dual non-parallel speech style conversion techniques to create natural and clear speech, revolutionizing communication in challenging auditory conditions.

29 Aug 2023

Artificial Intelligence in Text Generation

Discover the intricate world of text generation and its transformative impact on natural language processing. From historical approaches to cutting-edge techniques like deep generative models and pre-trained language models, delve into applications such as machine translation, text summarization, and dialogue systems.

28 Aug 2023

What is Fairness and Bias in AI?

This article explores the intricate landscape of AI fairness, from biased predictions to its societal impact. Discover strategies for addressing bias, the challenges in avoiding AI automation, and the vital role of fairness in the future of AI. Learn how collaboration, policy guidelines, and comprehensive solutions can pave the way to dependable, equitable machine learning systems.

28 Aug 2023