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

Revolutionizing Litchi Harvesting: A Smart Robotic System with Active Obstruction Removal

Researchers present an advanced robotic prototype for litchi harvesting equipped with a cutting-edge visual system. The system integrates the YOLOv8-Seg model for litchi segmentation, binocular stereo-vision for picking point localization, and an intelligent algorithm for obstruction removal, showcasing promising capabilities for autonomous litchi picking.

14 Nov 2023

Using Deep Learning for Time Series Forecasting

This article explores the intricacies of time series data, its components, and the challenges it presents, including irregularities and non-stationarity. The evolution of time series forecasting is traced from traditional statistical methods to contemporary deep learning techniques, such as Deep Feed Forward Neural Networks, Recurrent Neural Networks, Bidirectional RNNs, Convolutional Neural Networks, Generative Models, and Transformers.

13 Nov 2023

Three-Tier Deep Learning Model for Early Plant Disease Detection

This study introduces an innovative framework for early plant disease diagnosis, leveraging fog computing, IoT sensor technology, and a novel GWO algorithm. The hybrid approach, incorporating deep learning models like AlexNet and GoogleNet, coupled with modified GWO for feature selection, demonstrates superior performance in plant disease identification.

12 Nov 2023

AI Tools in Education: Adoption and Implications of ChatGPT and GPT-4 Among German Students

This study investigates the widespread usage of AI tools, particularly ChatGPT and GPT-4, among German students across disciplines. With nearly two-thirds of students utilizing these tools, the research emphasizes the need for further exploration into usage patterns, perceptions, and potential implications for teaching and learning.

12 Nov 2023

Enhancing Sugarcane Yield Prediction in China: A WCA-LSSVM Approach

This study introduces a novel approach for forecasting sugarcane yield in major Chinese production regions. Utilizing the Water Cycle Algorithm (WCA) to fine-tune the Least Squares Support Vector Machine (LSSVM) model, the proposed method demonstrates superior accuracy and generalization capabilities, offering valuable insights for optimizing sugarcane production practices.

10 Nov 2023

DEEPPATENT2: A Comprehensive Dataset for Advancing Technical Drawing Understanding

Researchers present DEEPPATENT2, an extensive dataset containing over two million technical drawings derived from design patents. Addressing the limitations of previous datasets, DEEPPATENT2 provides rich semantic information, including object names and viewpoints, offering a valuable resource for advancing research in diverse areas such as 3D image reconstruction, image retrieval for technical drawings, and multimodal generative models for innovation.

10 Nov 2023

LDM3D-VR: Advancing Virtual Reality with Latent Diffusion Models

Researchers introduce LDM3D-VR, a novel framework comprising LDM3D-pano and LDM3D-SR, revolutionizing 3D virtual reality (VR) content creation. LDM3D-pano excels in generating diverse and high-quality panoramic RGBD images from textual prompts, while LDM3D-SR focuses on super-resolution, upscaling low-resolution RGBD images and providing high-resolution depth maps.

9 Nov 2023

Revolutionizing Neuroscience: Machine Learning's Role in Simulating the Human Brain

A recent publication delves into the evolving landscape of utilizing machine learning to simulate the complexities of the human brain. Tracing the historical journey from simplified neural network models to contemporary connectome-driven approaches, the article emphasizes the potential of machine learning in replicating neural activities.

9 Nov 2023

Multichannel Deep Learning Model for Enhanced Underwater Image Quality

Researchers introduced the MDCNN-VGG, a novel deep learning model designed for the rapid enhancement of multi-domain underwater images. This model combines multiple deep convolutional neural networks (DCNNs) with a Visual Geometry Group (VGG) model, utilizing various channels to extract local information from different underwater image domains.

8 Nov 2023

Relay Learning: A Secure Deep-Learning Framework for Cross-Site Clinical Data

Researchers introduced Relay Learning, a novel deep-learning framework designed to ensure the physical isolation of clinical data from external intruders. This secure multi-site deep learning approach, Relay Learning, significantly enhances data privacy and security while demonstrating superior performance in various multi-site clinical settings, setting a new standard for AI-aided medical solutions and cross-site data sharing in the healthcare domain.

8 Nov 2023