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Trishna Devi

@trishnadevi

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AI & ML Engineer and Data Scientist focused on deep learning, computer vision, and explainable real-world solutions.

India

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What I'm looking for

I’m looking for an entry-level role where I can build deep learning and computer vision solutions with explainable AI, and contribute to scalable real-world deployments across mobility, remote sensing, and edge IoT systems.

I’m an AI and Data Science graduate with practical experience in Deep Learning, Computer Vision, Remote Sensing, and IoT systems. I focus on transforming complex data into scalable, real-world solutions for disaster management, intelligent mobility, and decision support systems, with a strong emphasis on interpretability.

In my work, I built an automated Brahmaputra Basin flood mapping framework using Sentinel-1 and Landsat-8, using semantic segmentation with explainable AI; DeepLabV3+ achieved 94.56% Accuracy and meaningful Dice/IoU performance. I also developed PiViTel, an IoT-Based Edge Intelligence Device using Raspberry Pi with GPS and IMU sensors, and created explainable vehicle trajectory anomaly detection using Isolation Forest and SHAP. For computer vision, I implemented an intra-campus vehicle tracking system using YOLOv5 and PP-OCR (published in SILCON 2025), and built a crop yield prediction Streamlit app using a Random Forest model across 55 crops and 30 states.

Experience

Work history, roles, and key accomplishments

Summer Internship

K-Means Technologies Pvt. Ltd.

Jun 2025 - Jul 2025 (1 month)

Developed piViTel, an IoT-based edge intelligence platform using Raspberry Pi, Pi Camera, GPS, and IMU sensors. Designed telemetry pipelines to collect, process, and transmit sensor data from edge devices to cloud services for mobility applications.

IoT Edge Computing Raspberry Pi Pi Camera GPS IMU Telemetry Sensor Processing Cloud Transmission

Summer Internship

AEDC Ltd. (AMTRON)

Jun 2023 - Jul 2023 (1 month)

Built an IoT-based fire and gas detection system using NodeMCU ESP8266, fire sensors, and MQ-5 gas sensors. Implemented a web interface to monitor sensor readings and generate automated safety alerts.

IoT NodeMCU ESP8266 MQ 5 Gas Sensors Web Interface Safety Alerts Environmental Monitoring

Cloud Solution Architect Bridge Course

NIELIT

Jun 2022 - Aug 2022 (2 months)

Completed training in cloud computing fundamentals and AWS services. Deployed a WordPress website on AWS and configured EC2 instances, storage, and security settings.

AWS EC2 Cloud Computing Cloud Infrastructure Management

Field Training

Northeast Frontier Railway

Jun 2023 - Present (3 years 1 month)

Completed field training in the Signal & Telecommunication Department, learning railway signaling systems and communication infrastructure. Gained practical exposure to operational procedures and safety systems.

Railway Signaling Telecommunications Infrastructure