DURLA LAKSHMIVENKATA NAGA VISWANADHA REDDY
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Computer Vision & Deep Learning.
DUR LA LAKSHMIVENKATA NAGA VISWANADHA REDDY is an aspiring AI Engineer with 5 months of experience as a Research Intern at the National Institute of Ocean Technology. Possessing a strong foundation in Python, MATLAB, and SQL, and hands-on experience with frameworks like TensorFlow, Keras, and OpenCV. Key projects include developing UAV image stitching pipelines for coastal mapping, designing a CNN + Bi-GRU model for underwater polymetal detection, and building a lightweight DNN for sleep apnea detection, showcasing expertise in AI/ML, Deep Learning, and Computer Vision.
Vel Tech Rangarajan Dr. Sagunthala R and D Institute Of Science and Technology
B.Tech · ECE (Specialization in AIML)
August 1, 2021 – June 30, 2025
Narayana Junior College
Intermediate · MPC
June 1, 2019 – May 31, 2021
Narayana E.M. High School
Matriculation
June 1, 2019 – May 31, 2019
National Institute of Ocean Technology (NIOT) - Govt.of India
Research Intern
January 1, 2025 – May 1, 2025
Chennai, Tamil Nadu, India
Drone-Based Image Processing and Classification
January 1, 2025 – May 1, 2025
* Deployed YOLOv5 for real-time object detection on orthomosaic imagery to classify terrain into trees, buildings, and sand directly integrated with the NIOT stitching pipeline. * Converted 2D mosaic images into 3D spatial representations, enabling volumetric terrain analysis for environmental monitoring reports.
Underwater Polymetal Detection
July 1, 2024 – December 1, 2024
* Designed a custom CNN + Bi-GRU hybrid model with an attention mechanism for audio-based classification of underwater polymetallic nodules. * Achieved 87.4% accuracy using Ranger optimiser and Cosine Decay LR scheduling and outperforming a baseline CNN by 12 percentage points.
Sleep Apnea Detection Using Deep Learning
January 1, 2024 – June 1, 2024
* Designed a lightweight DNN for real-time monitoring of blood oxygen saturation and airflow signals, achieving ¿92% detection accuracy. * Optimised model size and inference latency for deployment on IoT-enabled wearable devices.
AI/ML Internship Completion Certificate
LABMENTIX
June 1, 2026 – Present
Python Programming Crash Course
Coursera
June 1, 2026 – Present
MATLAB Programming
MATLAB Online
June 1, 2026 – Present
In-plant training certificate
VOLTME MOTORS PVT LIMITED
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internship show a strong focus on AI/ML applications, aligning well with an AI Engineer role. The diversity of projects (image processing, audio classification, sensor data for IoT) indicates a broad interest and adaptability within the AI domain. The academic nature of most projects and the current student status suggest a learning-oriented mindset, which can be a good cultural fit for innovative teams. However, the lack of professional experience beyond a single internship means less exposure to corporate culture and team dynamics.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical problems and optimize solutions for specific constraints (e.g., model size, inference latency). The internship at NIOT suggests an ability to contribute to active research and development workflows. However, without direct interview data, it's difficult to assess collaboration, problem-solving under pressure, or communication in a team setting.