Muhammad Usama
NUST
· 2019
Email
mmusama99@gmail.com
Phone
923338803388
LinkedIn
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GitHub
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Academic
Program
BE Electrical Engineering
CGPA
3.43
Year
2019
Education
SEECS
Address
Multan
DOB
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Career
Current role
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Target role
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Skills
Convolutional neural networks, Recurrent neural networks, Computer vision, Tensorflow, keras, pytorch, Open cv, C++, python, linux
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Muhammad Usama Details Technical Skills Soft Skills Reference Cell: 923338803388 Email: mmusama99@gmail.com Address: HOUSE NO.981 BLOCK:Q PHASE 2 WAPDA TOWN MULTAN Multan , Pakistan Convolutional neural networks Recurrent neural networks Computer vision Tensorflow, keras, pytorch Open cv C++,python, linux(basic) To be furnished upon request. Professional Profile Please update objective section. Education BE Electrical Engineering School of Electrical Engineering and Computer Science (SEECS) , 3.41 Bachelor of Electrical Engineering School of Electrical Engineering and Computer Science (SEECS) , 3.43 (2019) Internship Experience DAAD Research Fellowship ( 13-Jul-2022 - 11-Sep-2022 ) • Fully funded DAAD research Fellowship at Robotics Research lab, Technical University, Kaiserslautern, Germany via German-Pakistan Research collaboration. • Working on Computer Vision application in Precision Agriculture using multi-spectral imagery captured through UAV. • Developed Autonomous pest stress MachVIS, Islamabad. ( 01-May-2022 - 01-Dec-2022 ) • Collected novel dataset of different crops of Pakistan using DJI Inspire and Sequoia+ sensor along with SenseCAP IoT sensors. • Data preprocessing and analysis based on multispectral imagery and time series IoT sensors through computation of Vegetation Indices. • Multi-modality through fusion of Imagery Signal Processing and Machine Learning (SIGMA) Lab, NUST ( 01-Jul-2021 - 01-Jun- 2022 ) • Completed Deep Learning and Computer Vision Literature with a research focus on Self Driving Cars. • Working on Autonomous Mine Detection Drone using NVIDIA Jetson Nano and SDR for onboard computing of live feedback camera to have Autonomous maneuverability and mine detection using RF transmission and rece Projects Detection of pest infestation in crops using drone imagery and A-IoT • Dataset is being collected using DJI Inspire and Sequoia+ sensor from different crops along with sequential IoT sensors data like temperature, humidity, soil moisture sensors etc. • Data preprocessing and orthomosaic compilation is done using softwares like Pix4d mapper, Pix4d fields, Webodm etc. NDVI, RV Sensor fused autonomous driving • Dataset is being collected from Carla simulator and data stream pipeline will be through ROS- bridge. • Camera, Lidar and other sensors data will be communicated through ROS topics and fused for decision making. • Keras, ROS and Carla will be utilized in project. Behavioral cloning of Self Driving Car • Using Udacity’s self-driving car simulator, collected real time pictures of left, right and center cameras along with steering angel and velocity. Preprocessed data using Pandas. • Created network using NVIDIA model having Convolutional, Dense and Dropout layers along with Relu activation function reducing
AI enrichment
Muhammad Usama holds a BE in Electrical Engineering with a focus on computer vision and deep learning, supported by a DAAD research fellowship in Germany. His experience includes developing autonomous systems for precision agriculture and mine detection using drones and IoT sensors.
Skills (AI)
["Computer Vision", "Deep Learning", "TensorFlow", "Keras", "PyTorch", "OpenCV", "Python", "C++", "ROS", "UAV/Drones", "Multispectral Imagery", "IoT Sensors", "Linux"]
Status: ai_done