Abhishek Kanakagiri
Solana Offline Transaction Webapp
Experience
Solana Offline Transaction Webapp
- Built a decentralized app using Next.js and Convex DB for secure offline Solana transaction signing.
Senior Engineer - Lead Developer Data Analytics
Magna Electronics
- Built and maintained large-scale data pipelines using Python, PySpark, and AWS services (S3, Athena, EC2, SQS) for sensor data analysis from Camera, LiDAR, and GPS modules.
- Maintained and extended the backend of KPI tooling systems using Node.js and MongoDB to support validation workflows and visualization.
- Designed relational SQL schemas for structured storage of perception test data and KPI results.
- Automated test execution, report generation, and feature validation, reducing manual overhead by 50%.
- Created interactive dashboards using AWS Quicksight and Plotly to support data-driven decisions for ADAS validation teams.
- Implemented and retrained the YOLOv7 deep learning model to detect custom object types for test automation and KPI generation in vision-based ADAS functions.
- Led a team of 4–5 developers, reviewed code, and coordinated task planning with OEM partners and internal teams.
- KPI Tooling: Designed modular backend APIs in Node.js and MongoDB; enabled dashboard visualizations and AWS-based data processing.
- Audi – Multi-Functional Front Camera: KPI design for object detection, pedestrian/lane/traffic sign recognition; root cause analysis; outlier identification.
- VW – Trained Park Assist: KPI generation and ground truth derivation using DGPS/IPS data in complex parking scenarios.
- BMW – LiDAR Validation: Point cloud analysis for false-positive/negative detection; safety-related scenario analysis.
Consulting Core Test Developer
Ferchau GmbH
- Developed test infrastructure and automated validation workflows using Python and AWS for ADAS features.
- Integrated cloud-based tools for performance testing and reporting.
- Coordinated with various function owners for KPI-related activities.
- Worked closely with customer teams to design and implement data processing pipelines across multiple projects.
- Automated system test activities and report generation using transcoded Ethernet data.
Student Research Assistant & Master Thesis
Carissma Forschungszentrum
- Built and configured a prototype autonomous vehicle platform for ADAS testing using Camera and LiDAR sensors.
- Created a virtual testbed by building 3D digital twins and HD maps of Ingolstadt using MATLAB Roadrunner.
- Integrated with ROS and simulated traffic scenarios for perception validation.
Comparison of Machine Learning Algorithms for Cyclist Detection
- Determined the feasibility of use of computer vision algorithms in an autonomous vehicle for increasing passenger safety at level 5 of autonomous driving.
- Used deep neural networks such as CNN to detect cyclists.
- Used HOG technique to extract image features and SVM classification algorithm to detect cyclists.
Manufacturing Engineer II
Lam Research India Pvt. Ltd
- Designed and analyzed structural fixtures and collaborated with cross-functional global teams.
- Implemented process improvements to meet manufacturing and structural integrity requirements.
Industries Experience
See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.
Experienced in Automotive (5.5 years), Manufacturing (2.5 years), and Information Technology (0.5 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Product Development (7.5 years), Information Technology (4.5 years), Business Intelligence (3.5 years), Quality Assurance (3.5 years), Production (2.5 years), and Research and Development (1 year).
Summary
Data Analytics Engineer with 5+ years of experience in developing scalable data pipelines, automating test workflows, and analyzing multi-sensor datasets in the automotive sector. Strong expertise in Python, PySpark, and AWS-based validation environments. Proven track record of driving performance improvements through KPI analytics, sensor validation, and cloud automation. Effective team leader with hands-on experience in ADAS feature validation and test infrastructure.
Skills
- Cloud Platforms & Big Data: Extensive Daily Use Of Aws For Test Execution, Automation, And Cloud Computing (Ec2, S3, Athena, Sqs, Emr, Lambda, Boto3)
- Programming & Backend: Python (Pandas, Numpy, Plotly), Selenium, Node.js, Next.js, React.js, Typescript, Git, Docker, Rest Apis, Json-based Integrations, Webhooks
- Validation & Etl: Kpi Development, Etl Pipelines, Camera/lidar/gps Data Analysis
- Software & Project Tools: Jira, Confluence, Codebeamer, Microsoft Office
- Ml And Ai Agents: Yolov7 Model Retraining For Object Detection, Opencv, Hugging Face, Llm Tools Like Chatgpt, Cursor, Copilot
- Databases: Sql (Schema Design), Mongodb, Convex Database
- Sensor Systems: Camera, Lidar, Gps, Dgps, Indoor Positioning
Languages
Education
Technische Hochschule Ingolstadt
International Automotive Engineering · International Automotive Engineering · Ingolstadt, Germany · 1.7
M S Ramaiah Instiute of Technology
Mechanical Engineering · Mechanical Engineering · Bengaluru, India · 1.5
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