Gopalakrishna Adusumilli

M.Tech in Digital electronics

July 2018 - July 2020

Relevant Coursework

• Automotive electronics
• Machine learning
• Image processing

B.Tech. in electronics & Communication

May 2018

Relevant Coursework

• Image processing
• Algorithms & Optimization for Big Data
• Digital signal processing

IELEKTRON TECHNOLOGIES PVT. LTD

January 2023 - Present

Product management

• As the Product Development Lead at IELEKTRON, I conceived, designed, and delivered an advanced end-to-end cloud management tool tailored to address intricate data lifecycle challenges.
• Led a cross-functional team of 10 engineers, designers, and data scientists to conceptualize, design, and execute an end-to-end cloud management tool.
• Oversaw the entire product lifecycle, from ideation to deployment, ensuring alignment with business objectives and technical feasibility.
• Orchestrated data ingestion strategies, establishing seamless pipelines for efficient data capture, transformation, and storage, resulting in a 75% increase in data accuracy and 40% reduction in processing time.
• Designed the development of an intuitive sensor data visualization module, empowering users to gain actionable insights from complex data sets effortlessly.
• Fostered strong client relationships by gathering feedback, incorporating feature requests, and iterating on the product, resulting in 40% growth in client satisfaction.

March 2021 - January 2023

Algorithm developer - ADAS

• Working with ADAS KPI Development team, Europe
• Developed algorithm for real-time 3D object detection & localization of vehicles using LiDAR point cloud data & Ground truth data with detection accuracy of 80% PPV per detection
• Optimized the efficiency of the object tracking algorithm to maintain stability during lane change by the vehicles
• Developed a robust SLAM based vehicle trajectory & road curvature estimation algorithm with vehicle odometry data
• Automated event-based pre-analysis with the development of ML model for pattern recognition on categorical data with prediction accuracy of 96.8%
• Developed an End-to-end 3D visualization toolchain for an enhanced view of LiDAR point cloud data, 3D meshes, and bounding boxes for the KPI validation test team
• Experience working with sensor data from GPS, Point cloud, GT meshes, and vehicle odometry

Continental Automotive TCI

November 2029 - July 2020

Software Engineer

• Involvement in development of in-house commercial LiDAR (HFL110) algorithm development
• Developed an End-to-end learning algorithm for 3D object detection using LiDAR point cloud data
• Developed a PoC for vehicle parking location using RADAR data
• Skills: Python, Pyspark, Deep learning, LiDAR data pre-processing

Languages and Databases

Frameworks

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