Abhishek Kumar Pathak

Lead ML Engineer

Hyderabad, Telangana, India2 yrs 5 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Achieved 99.81% accuracy in CNN-based model for agriculture.
Developed AI solutions for real-time applications.
Strong foundation in Python and machine learning frameworks.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on Computer Vision and AI applications.

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Skills

Core Skills

Computer VisionMachine LearningDeep Learning

Other Skills

.NET FrameworkAI AlgorithmsAutomationAutonomous Road InspectionC (Programming Language)C#C++Cascading Style Sheets (CSS)CommunicationComputation OptimizationConvolutional Neural Networks (CNN)DSADlibEngineeringEnglish

About

I am a dedicated professional with practical experience in machine learning, AI, and deep learning, aiming to create meaningful solutions through data-driven innovation. With a B.Tech in Computer Science and Engineering, I have been fortunate to work on projects that optimize AI algorithms for real-world applications. As a Junior Research Fellow at IIT Indore, I developed a CNN-based classification model that achieved 99.81% accuracy, designed for edge deployment in agriculture. My journey also includes working on projects like pothole detection using CNNs, as well as scalable AI solutions. During my internship at iHUB DivyaSampark, IIT Roorkee, I worked on a drowsiness detection system using models like InceptionV3 and MobileNetV2, achieving remarkable accuracy. I have a strong foundation in Python, machine learning frameworks such as TensorFlow and PyTorch, data analysis, and visualization. I am deeply passionate about applying these skills to solve challenging problems in areas like computer vision and real-time AI applications. I am always eager to learn, grow, and contribute to impactful projects that drive innovation. I look forward to connecting and exploring how I can bring value to exciting opportunities in AI and data science.

Experience

Amd

AI/ML Software Engineer (CIEL)

Jun 2025 – Present · 9 mos · Hyderabad, Telangana, India · On-site

Indian institute of technology, indore

Junior Research Fellow

Sep 2023 – May 2025 · 1 yr 8 mos · Indore, Madhya Pradesh, India · On-site

As a Junior Research Fellow at IIT Indore, I conducted cutting-edge research in Artificial Intelligence and Computer Vision based project. I developed an optimized Convolutional Neural Network (CNN) model that achieved 99.81% accuracy for rice grain classification, making it suitable for edge deployment in real-time agricultural applications. Additionally, I designed and deployed a YOLO-based deep learning system for pothole detection, integrated with a Streamlit Cloud interface to provide real-time alerts. My role involved close collaboration with interdisciplinary teams to fine-tune model performance and ensure reliability in field deployment. I regularly conducted literature reviews and contributed to technical documentation to support our research outputs and publications. Overall, I played a key role in developing and deploying scalable, production-ready AI models for impactful real-world applications.

Convolutional Neural Networks (CNN)YOLOStreamlit CloudComputer VisionAI AlgorithmsMachine Learning

Ihub divyasampark @ iit roorkee

CHANAKYA UG FELLOWSHIP

Nov 2022 – Aug 2023 · 9 mos · IIT Roorkee · Remote

During my Chanakya UG Fellowship at iHUB DivyaSampark, IIT Roorkee (Nov 2022 – Aug 2023), I worked on developing an AI-powered drowsiness detection system to enhance road safety. I implemented and fine-tuned deep learning models such as InceptionV3, VGG16, and MobileNetV2, achieving high accuracies of 99.18%, 98.80%, and 99.01% respectively. The models were trained to classify eye states and detect fatigue in real-time, using image classification techniques. I evaluated the models using key performance metrics including accuracy, precision, recall, F1-score, and confusion matrix. This project helped me strengthen my skills in computer vision, deep learning, and model evaluation while contributing to a meaningful, real-world application.

InceptionV3MobileNetV2VGG16Deep LearningComputer Vision