Aditya Kumar Srivastav

AI Researcher

Dadri, Uttar Pradesh, India3 mos experience

Key Highlights

Winner of AgroTech Hackathon at Microsoft Office
Developed AI-powered Crowd Surveillance System
Internship focused on Computer Vision in agriculture

Stackforce AI infers this person is a Data Scientist with expertise in Computer Vision and Machine Learning in Agritech and Public Safety.

Contact

Skills

Core Skills

Computer VisionDeep LearningMachine LearningVulnerability Assessment And Penetration Testing (vapt)

Other Skills

Anomaly DetectionArtificial Neural NetworksCore JavaDeepSORTExploratory Data AnalysisFastAPIIDM MANAGER(RHEL 8.4)JavaJava SwingMicrosoft ExcelNatural Language Processing (NLP)Neural NetworksNumPyPandasPython (Programming Language)

Experience

Agro farm ventures private limited

Computer Vision Engineer

Apr 2025 – May 2025 · 1 mo · Shimla, Himachal Pradesh, India · Hybrid

I secured this internship opportunity after participating in the AgroTech Hackathon, held at the Microsoft Office, where our team Aerotoxs emerged as the winner. As a reward, we were offered the chance to intern at Kisan Manch, an organization focused on leveraging technology for agricultural innovation.
Currently, I am working on a Computer Vision-based project, where I am developing and implementing a model capable of:
Detecting the number of apple boxes using CCTV footage.
Identifying SKU labels on each box.
Detecting defects in the boxes, such as whether a box is broken, opened, or tampered.
This project involves real-time image processing and object detection techniques, contributing to automation and quality control in the supply chain.

Computer VisionArtificial Neural NetworksNeural NetworksDeep LearningYolo

Uptoskills

Data Scientist

Jan 2025 – Apr 2025 · 3 mos · India · Remote

At UptoSkills, I led the development and deployment of an AI-powered Crowd Surveillance System. My core responsibilities included:
Designing and implementing real-time object detection using YOLO and DeepSORT for individual tracking.
Developing an anomaly detection module capable of identifying critical threats like stampedes or weapons using an autoencoder model.
Integrating and deploying various modules into a live FastAPI-based web system with video streaming capabilities.
Leading a sub-team, where I managed intern tasks, tracked progress, and contributed to project planning and growth strategies.
This project emphasized scalable deployment, real-time analytics, and ensuring public safety using intelligent computer vision techniques.

Computer VisionMachine Learning