Presently pursuing my M.Sc. degree in Biomedical Engineering at Bangladesh University of Engineering and Technology, Bangladesh. I am currently working on biomedical signal processing and deep learning-based health informatics projects as an active member of the m-health lab. My other research interests include biomedical simulations, biomedical Instrumentation, and edge device optimization. I am pretty much proficient in python and Matlab programming.

Namaste 🙏! I'm a passionate Data Scientist with an academic foundation from Northwestern University, deeply committed to advancing AI and Machine Learning across healthcare, computational biology, and scientific discovery—with particular strength in mathematically rigorous, FDA-aligned model development. Over the past year, I have successfully designed and implemented AI-driven solutions for ECG classification, denoising, medical imaging, and computational chemistry. My expertise blends deep neural architectures with advanced mathematics—Physics-Informed Neural Networks (PINNs), probability theory, stochastic processes, variational methods, and numerical optimization—to solve complex real-world problems with scientific defensibility. 🏥 FDA-Ready Clinical AI Development I have worked closely with FDA regulatory experts to bring models through clinical validation pipelines, ensuring they meet the rigor expected of medical-grade AI. My team is well-equipped to handle FDA documentation requirements (510(k) submissions, Software as a Medical Device (SaMD) artifacts, predicate analysis, validation reports, and risk management per IEC 62304 / ISO 14971) once a model is ready for launch. This means clients don't just get a working model—they get one built with regulatory submission in mind from day one. 🔬 Recent Work & Expertise in AI for Science & Medicine: ✅ ECG Signal Processing & Classification: Built deep learning models (CNNs, LSTMs, Transformers) for denoising, anomaly detection, and classification of ECG, PCG, PPG, and SCG signals—bringing them to gold-standard PhysioNet quality. ✅ Medical Image Processing (DICOM): Developed AI-driven solutions for lumbar spine classification, CT segmentation (TotalSegmentator models), fat tissue segmentation, bone mineral density estimation, and venous insufficiency detection via thermal imaging. ✅ Physics-Informed Neural Networks (PINNs): Applied PINNs to embed governing differential equations directly into the loss function—producing models that respect physical laws, generalize on sparse data, and are inherently more interpretable for scientific and clinical applications. ✅ Drug Discovery & Computational Biology: Used ML techniques to analyze molecular structures and optimize pharmaceutical compound discovery. ✅ Diffusion Models for Vision: Worked on Stable Diffusion and LoRA fine-tuning for text-to-video and image-to-video pipelines without relying on third-party APIs. ✅ AWS AI/ML Pipeline Deployment: Set up cloud-based pipelines on AWS for training, hosting, and deploying scalable ML models. ✅ Mathematical & Optimization Techniques: Leveraged variational calculus, FFT, wavelet transforms, probability theory, and evolutionary algorithms for feature engineering and model enhancement. 🧠 Core Technical Stack: 🚀 Deep Learning Frameworks: TensorFlow, PyTorch, JAX 📐 Mathematical Foundations: PINNs, probability and stochastic processes, variational calculus, numerical optimization, Bayesian inference 🔬 Generative & Diffusion Models: Stable Diffusion, LoRA, GANs, VAEs 📊 Classical ML: Random Forest, SVM, Gradient Boosting, RAG-based retrieval 👁 Computer Vision: CNNs, Vision Transformers, OpenCV, DICOM processing using SwinUNETR (3D U-Net + Swin), segmentation with nnU-Net 📝 NLP: Transformer-based LLMs, Hugging Face, LangChain, LlamaIndex 💡 Signal Processing: FFT, spectrograms, wavelet transforms, optimization methods ☁ Cloud & MLOps: AWS, Azure, GCP, Kubernetes, FastAPI, DevOps pipelines Why Work With Me? 🔹 Specialized in AI for healthcare, computational biology, and scientific discovery 🔹 Strong mathematical and probabilistic foundation—not just black-box deep learning 🔹 Experience working alongside FDA experts on clinical validation, with a team prepared to handle regulatory documentation 🔹 End-to-end delivery: from research and prototyping to deployment and submission-ready artifacts 🔹 Real-world projects that impact both research and industry Let's connect and build scientifically rigorous, regulation-ready AI together!

🚀 Hey there! its me your go-to expert for all things Machine Learning Python, Deep Learning Python, Computer Vision Python, Data Science, Robotics, Image Processing, C++, Matlab , Ros, and Python. With a fiery passion for innovation and a knack for delivering exceptional results, I'm here to elevate your projects to new heights. 💡 🔬 My forte lies in harnessing the latest techniques and algorithms to craft intelligent, robust solutions. In the realm of Computer Vision, I excel in: - ✅ Object Detection - ✅ Object Tracking - ✅ Semantic Segmentation - ✅ Instance Segmentation - ✅ Object Recognition - ✅ OCR projects In the realm of Machine Learning, I specialize in: - ✅ Support Vector Machines (SVM) - ✅ Random Forest - ✅ Gradient Boosting - ✅ K-Nearest Neighbors (KNN) - ✅ Decision Trees In Deep Learning, I'm proficient in: - ✅ Convolutional Neural Networks (CNN) - ✅ Recurrent Neural Networks (RNN) - ✅ Generative Adversarial Networks (GAN) - ✅ Long Short-Term Memory Networks (LSTM) - ✅ Transformer Networks - ✅ LLM Fine Tuning - ✅ RAG using LLM I have extensive experience in various fields, including: 🏥 Medical Imaging: - ✅ X-ray Disease Detection - ✅ CT Scan Analysis - ✅ MRI Image Analysis - ✅ Disease Classification - ✅ Tumor Detection - ✅ Organ Segmentation - ✅ Analysis of microscopy images 🌾 Agriculture: - ✅ Weed Detection - ✅ Plant Disease Detection - ✅ Palm Trees Detection - ✅ Crop Classification - ✅ Crop Yield Prediction - ✅ Plant Segmentation - ✅ Precision Agriculture 🏙️ Smart Cities: - ✅ Traffic Flow Prediction - ✅ Pedestrian Detection - ✅ Urban Planning Analysis - ✅ Waste Management Optimization - ✅ Environmental Monitoring - ✅ Detecting safety violations from camera footage 📸 Surveillance and Security: - ✅ Anomaly Detection - ✅ Facial Recognition - ✅ Object Tracking in Video - ✅ Intrusion Detection Systems - ✅ Time Series data Analysis 🤖 Robot Projects: ✅ A Pathfinding Algorithm ✅ Dijkstra’s Algorithm for Navigation ✅ SLAM (Simultaneous Localization and Mapping) ✅ 2D/3D Mapping using ROS ✅ LIDAR-based Mapping ✅ Reactive Obstacle Avoidance using IR Sensors ✅ Dynamic Obstacle Avoidance with Sensor Fusion ✅ ROS-based Obstacle Avoidance in Autonomous Vehicles ✅ Gazebo-based Robot Simulation ✅ Autonomous Vehicle Simulation in Gazebo ✅ Gazebo with SLAM Integration ✅ Robot Path Visualization in RViz ✅ Sensor Data Visualization in RViz ✅ RViz for SLAM Visualization 🧠 General Image Labeling Projects ✅ High-Quality Image Annotation for Machine Learning Datasets (Bounding Boxes, Masks, and Keypoints) ✅ Custom Image Labeling for AI Vision Models — Fast & Accurate Dataset Preparation ✅ Manual Image Tagging and Classification for ML Dataset Training ✅ Expert Data Labeling for Image Recognition and Computer Vision Tasks ✅ Dataset Creation and Labeling for Object Detection and Tracking 🎯 Object Detection–Focused Projects ✅ Object Detection Dataset Preparation — Bounding Box & Polygon Annotation ✅ YOLO / COCO / Pascal VOC Dataset Labeling for Object Detection Models ✅ Bounding Box Labeling for Autonomous Driving, Retail, and Drone Vision ✅ Annotation Expert for Object Detection and Instance Segmentation ✅ Prepare and Label Images for Deep Learning Detection Models (YOLO, SSD, Faster R-CNN) 🌈 Semantic & Instance Segmentation Projects ✅ Pixel-Level Semantic Segmentation for Computer Vision Models ✅ Annotation Services for Medical Image Segmentation (CT, MRI, X-Ray) ✅ Semantic Segmentation Dataset Creation From wielding the powers of Keras, TensorFlow, and PyTorch to sculpting intricate neural network architectures for tasks spanning classification, object detection, segmentation, and natural language processing, I thrive on pushing boundaries. 🧠 📊 With a rich tapestry of projects under my belt, I've honed my skills in every aspect, from data preprocessing and feature extraction to model training and evaluation. I'm no stranger to taming colossal datasets and weaving magic with statistical analysis and data visualization. 📈 🖼️ But that's not all! I possess a keen eye for image processing wizardry, from sprucing up images to recognizing objects and slicing through visual data with precision. Whether it's powering autonomous systems or fueling robotics, I've got the expertise to make it happen. 🤖 ✨ My commitment to excellence is unwavering, reflected in my meticulous attention to detail, knack for problem-solving, and knack for effective communication. Your unique needs are my priority, and I'm dedicated to crafting tailored solutions that exceed expectations. 🎯 🌟 So, if you're on the hunt for a reliable, skilled freelancer to tackle your machine learning, deep learning, computer vision, data science, or robotics projects, look no further. Let's join forces and transform your visions into reality with cutting-edge technology. 🌈 💬 Reach out today, and let's start this journey towards success together! 🚀

Greetings! I am a PhD candidate in Statistical Machine Learning (ML), and a certified Machine Learning Scientist and Data scientist (Upwork & IBM) with both Master’s and Bachelor’s degrees in Statistics. My strong academic foundation equips me advanced data science and ML workflows. I specialize in developing predictive models for financial markets—particularly in crypto and stock price forecasting—using time series analysis, deep learning, and ensemble methods. My work also involves designing and backtesting algorithmic trading strategies, optimizing model performance under live market conditions, and building interactive dashboards for real-time data visualization and decision support. 🌟 Top Rated on Upwork – Consistent record of client satisfaction and delivery excellence. 🔍 Why Hire Me? ✅ Advanced ML Expertise I leverage cutting-edge techniques to deliver highly accurate and innovative predictive solutions. ✅ Comprehensive Tool Proficiency Programming: Python, R Dashboards & Visualization: Tableau, Power BI, Streamlit Statistical Software: SPSS, STATA, E-Views, Minitab Database & Cloud: SQL, Google Cloud (for scalable, production-ready ML deployments) ✅ Quantitative Research Strength Deep experience in algorithm design and time series forecasting enables trend prediction with exceptional precision. ✅ End-to-End Execution From data ingestion to predictive modeling and visualization, I manage the full pipeline with performance and clarity in mind. ✅ Clear Communication I break down complex ML models and insights into intuitive, actionable formats for stakeholders and non-technical audiences. 💼 What I Deliver: Predictive Modeling Time Series Forecasting & Analysis Interactive Dashboards in Tableau, Power BI, and Streamlit Risk Assessment & Optimization Models Feature Engineering & Model Tuning Visual Analytics & Business Intelligence

I'm Vishwajeet Panda, a highly motivated and results-oriented tech professional with a passion for innovation and a proven track record of success. As a winner of the Smart India Hackathon in both 2022 and 2023, I possess strong technical expertise in Machine Learning (ML), Deep Learning (DL), and web development. My diverse skillset encompasses Python, TensorFlow, Keras, Scikit-learn, and more. I also have experience with MLOps, Flask, OpenCV,and web development frameworks. Here's what sets me apart: * My victories in Hackathons showcase my ability to tackle complex challenges and deliver innovative solutions, in tight deadlines. * My top priority is high quality work and I thrive on building successful partnerships and exceeding expectations. Ready to discuss your project? Leveraging my skills and experience to bring your vision to life. Contact me today to discuss how I can contribute to your success. Email: panda18vishu@gmail.com

I'm a developer with over 15 years development experience in many fields, including computer vision and deep learning solution, full-stack development, Python data process, web service application, LLM application and so on. With rich software architect experience, I could also help you on software architecture, building tech stack at project start phase. With rich software solution experience, I could analyze requirement document and provide necessary project plan, feature design and so on. • skill set include: Python, C/C++/C#, java script, vue.js, PHP, java, web service • experienced in computer vision, deep learning training & deployment solution • experienced in building big data solution in cloud computing environment • experienced in building LLM related project, like ChatGPT integration, finetune and API development • good at software performance optimization

Machine Learning Engineer specializing in medical image analysis, deep learning, RAG pipelines, LLM development, generative AI and time series forecasting delivering production-ready AI systems built on real-world data. I help researchers, startups and enterprises turn complex data — medical images, documents, sensor signals and time series into reliable machine learning systems for detection, classification, prediction and intelligent automation. Every project I deliver is a working, documented system not a research prototype. Medical Image Analysis & Computer Vision I develop deep learning models for medical imaging and computer vision applications including image classification, object detection and semantic segmentation. Work covers MRI, CT, X-ray, whole slide image analysis, histopathology and EEG/ECG biosignal processing. Models: YOLOv8, UNet, ViT, EfficientNet, ResNet, Mask RCNN, SAM Frameworks: PyTorch, TensorFlow, OpenCV RAG Pipelines, LLM & Generative AI I build retrieval-augmented generation systems, AI agents and custom LLM chatbots for enterprise and research use. Work covers document Q&A, knowledge base search, LLM fine-tuning and AI workflow automation. Tools: LangChain, LlamaIndex, OpenAI GPT, LLaMA, Mistral, HuggingFace Vector DBs: ChromaDB, Pinecone, FAISS Time Series Forecasting & Anomaly Detection I build forecasting and anomaly detection models for finance, retail, IoT, energy and industrial domains. Work covers demand forecasting, predictive maintenance, multivariate time series and real-time anomaly detection. Models: LSTM, Transformer, Prophet, XGBoost, LightGBM Message me with your project — I will tell you exactly what is achievable and the best approach for your data.

I am an AI Researcher with numerous publications including IEEE TNNLS, MICCAI, CBMS, etc. I also have a YouTube channel named "Idiot Developer", where I upload videos related to deep learning. I also write blog posts on my website idiotdeveloper.com. ✅ Projects: 1. Human Face Landmark Detection - using pre-trained MobileNetv2 2. Multiclass Face Segmentation - using UNET. 3. Dog Breed Classification - using pre-trained ResNet50 4. Human Parsing using Crowd Instance-level Human Parsing (CHIP) dataset 5. Brain Tumor Segmentation 6. GAN to generate Anime 7. Retina Blood Vessels 8. Background Removal from Human Images and Videos 9. Implemented various segmentation architectures: U-Net, ResU-Net, DeepLabV3+, DoubleUNet, U2-Net and more. 10. Lung Segmentation 11 Autoencoders

Hi, Thank you for visiting my profile! I am an experienced Data Scientist, AI Specialist, and Research Consultant with over 10 years of industry experience, 15+ research publications, and 200+ satisfied industrial clients. My expertise lies in academic research, consultancy, and building cutting-edge AI/ML solutions. Whether you need in-depth research support, advanced AI integration, or technical guidance, I deliver results tailored to your needs. 📘 Research Writing and Consultancy 🌟 Highlights: 🔹 Crafting high-quality academic research papers, theses, and dissertations for SCI/SSCI-indexed journals. 🔹 Ghostwriting for academic manuscripts, ensuring originality and impactful content. 🔹 Comprehensive literature reviews with the latest studies (2020–present) from reliable, peer-reviewed sources. 🔹 Structuring compelling research proposals with strong problem statements, methodologies, and objectives. 🔹 Formatting and editing aligned with academic styles like APA, MLA, Chicago, Vancouver, IEEE, and others. 🔹 Plagiarism detection and removal with detailed PDF reports and recommendations for improvement. 🔹 Addressing reviewer comments meticulously to enhance the chances of publication. 💡 AI and Machine Learning Development 🔧 Expertise in Technologies 🟢 Advanced proficiency with LLMs (e.g., ChatGPT, LLaMA 2), Transformers (BERT, RoBERTa, GPT), and RAG (Retrieval-Augmented Generation) pipelines. 🟢 Developing custom AI solutions such as NLP systems, intelligent analytics pipelines, and retrieval systems. 🟢 Implementation of advanced ML algorithms, including Random Forest, XGBoost, SVM, and KNN. 🟢 Expertise in deep learning frameworks like PyTorch, TensorFlow, and Keras for computer vision, image recognition, object detection, and classification tasks. 🟢 Integration of modern data lakes and scalable architectures for processing large datasets. 🟢 Deployment of AI/ML models on cloud platforms (AWS, GCP) with Docker and Kubernetes for seamless scalability and performance optimization. 🟢 Performance tuning with techniques such as self-supervised learning, transfer learning, and advanced model fine-tuning. 📑 Editing, Proofreading, and Formatting ✨ Comprehensive Services 🟡 Thorough editing for grammar, sentence structure, and flow to enhance document quality. 🟡 Precision formatting of research papers, theses, and dissertations as per journal/institutional requirements (e.g., IEEE, APA, Chicago, etc.). 🟡 Cross-checking citations and references using tools like EndNote, Zotero, and Mendeley to ensure accuracy and consistency. 🟡 Meticulous formatting of tables, figures, headings, subheadings, TOC, and appendices to meet professional standards. 🟡 Detailed proofreading for grammatical and typographical errors, ensuring a polished and professional document. 🟡 Expert review and constructive feedback on existing drafts to improve structure, clarity, and impact. 🌟 Why Work With Me? I combine extensive research expertise, cutting-edge technical skills, and a dedication to delivering high-quality results that exceed expectations. With 20+ research publications and over 200 satisfied clients, I am confident I can meet your needs and help you achieve your goals. Let’s connect and discuss how I can contribute to your success! Best regards, Junaid Hussain Muzamal

Hello, I'm Tam 👋 - 7+ years of experience in Deep Learning, Computer Vision, LLM, and Generative AI. - 3+ years of experience in AI Automation, RAG, AI Agents. - Tech stack: Python, PyTorch, TensorFlow, OpenCV, FastAPI, Docker, CUDA, AWS, Modal, DeepStream, Javascript/TypeScript, NodeJS, NextJS, ReactJS, Electron, Tauri, PyQt - Built high-performance real-time object detection systems with NVIDIA DeepStream for edge and GPU deployment. - Developed OCR & document understanding pipelines for scanned documents, engineering drawings, and forms. - Built LLM/VLM-powered AI applications, including multimodal assistants, RAG systems, image analysis, and AI inference APIs. Let's turn your AI idea into a production-ready product.