Machine Learning Deep

Naga Sai Surya Guttikonda

716-***-**** ********@*******.*** https://www.linkedin.com/in/surya-guttikonda EDUCATION

Master of Science: Expected: December 2023

Robotics, University at Buffalo, The State University of New York. Bachelor of Technology:

Automotive Engineering, Vellore Institute of Technology, India, August 2021. SKILLS & TOOLS

Languages: Proficient in Python, SQL, R

Tools: Experienced in Pytorch, Hadoop, Jupyter, TensorFlow, MATLAB Certifications: AWS- Cloud practitioner

Coursework: Studied Deep learning, Intro to Machine Learning, Computer Vision and Image Processing, Robotic Algorithms, Analysis of Algorithms.

PROJECTS

Object detection using Machine Learning and Deep Learning: Python, Pytorch, TensorFlow, Jupyter.

• Executed and compared YOLO and SSD object detection algorithms on custom image datasets, achieving accuracy rates of 92% (YOLO) and 88% (SSD).

• Optimized processing speeds to 30 FPS (YOLO) and 25 FPS (SSD), and analyzed precision, recall, and mAP scores for data-driven algorithm selection. Facial recognition, Computer Vision: Python, Jupyter, OpenCV

• Applied K-means clustering algorithm for facial recognition, utilizing diverse custom images to enhance accuracy significantly.

• Achieved precision and recall rates of 92% and 89% respectively, resulting in an overall accuracy score of 88%.

• Elevated facial recognition accuracy by 15% through strategic integration of varied lighting conditions and facial expressions in custom images.

Path planning using RRT algorithm: Python, OpenCV

• Implemented RRT algorithm to autonomously navigate intricate indoor environments, enabling a small robot to avoid obstacles, optimize paths, and effectively accomplish tasks with a 45% reduction in completion time.

• Achieved an 85% success rate, enhancing robot's autonomous navigation capabilities in real-world robotics scenarios.

Design of Automotive Suspension using Machine Learning: Altair hyperworks, Jupyter, Matlab

• Leveraged sensor data capturing 40,000 suspension force values per compression to train a robust Random forest machine learning model, enabling accurate prediction of vehicle off-road performance.

• Leading a team of 7, enhanced vehicle's off-road performance prediction accuracy while re-engineering suspension parameters, increasing shock travel by 14mm without compromising chassis rigidity. WORK EXPERIENCE

Robotics Intern, Decibels Lab, Bangalore, India: April 2020 – May 2021

• Spearheaded Robotic path planning intern, focusing on planning of warehouse robot deployment and obstacle avoidance using the data collected from sensors.

• Performed data mining and engineered a 3D printed prototype which would act as a hub for robot charging station, while navigating through warehouse. Head of Design and Engineering Department, Team Kshatriya, BAJA SAE INDIA: June 2019 – August 2021

• Directed a high performing team for the execution of design components and conducted comprehensive end-to-end testing by analyzing real-time recordings.

• Conducted comprehensive fatigue and structural analysis on entire vehicle utilizing Altair HyperWorks, identifying crucial areas for enhancement, ensuring safety standards. Increased vehicle durability by 20% through targeted structural modifications.

AWARDS & INVOLVEMENT

Design Engineer and Race driver: Secured 7th position out of 456 participants in BAJA SAE INDIA 2020, hosted by Mahindra India.

Outstanding Outgoing Student: Acknowledged for excellence in Automotive Engineering at VIT Vellore.

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