Wajih hassan Raza
NUST
· 2024
Email
wraza.bee20seecs@seecs.edu.pk
Phone
923303922221
LinkedIn
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GitHub
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Academic
Program
BE Electrical Engineering
CGPA
3.67
Year
2024
Education
School of Electrical Engineering and Computer Science
Address
Karachi , Pakistan
DOB
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Career
Current role
undergraduate research assistant
Target role
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Skills
Embedded c, Python, keras, Tensorflow, scikit-learn, Proteus, ads, pspice, octave, Open cv, Matlab, Modelsim altera, Lab view, Microsoft word, excel, project, C++
Interests / quote
I am an undergraduate student pursuing a bachelor’s in electrical engineering at the National University of Sciences and Technology (NUST). Currently, I am working as a research assistant at the Information Processing and Transmission Lab (IPT), where I work on the performance analysis and optimization of Intelligent Reflected Surfaces (IRS)-enabled wireless networks, a key technology for 6G. Previously, I was a research intern at the Machine Vision and Intelligent Systems Lab, where I worked on a deep active learning framework for large-scale semi-automated phenotype extraction using BERT NER. We successfully published our work in the prestigious Expert Systems with Applications journal. I have also earned multiple certifications in Python, Reinforcement Learning, and Deep Learning. I am passionate about applying my skills and knowledge to solve real-world problems in the 6G and machine learning domains. I aspire to become a leading researcher and innovator in these domains.
Verbatim text
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Wajih hassan Raza Details Technical Skills Soft Skills Reference Cell: 923303922221 Email: wraza.bee20seecs@seecs.edu.pk Address: D-168, Rufi Fountain Bungalows, Block-19,Gulistan-e- Jauhar. Karachi , Pakistan Embedded c Python, keras Research and technical writing Tensorflow, scikit-learn Proficient in python, c & c++ Proteus, ads, pspice, octave Open cv Matlab Modelsim altera Analytical thinking Strong work ethics Microsoft word, excel, project Lab view Communication and presentation Team management skills Problem solving skills To be furnished upon request. Professional Profile I am an undergraduate student pursuing a bachelor’s in electrical engineering at the National University of Sciences and Technology (NUST). Currently, I am working as a research assistant at the Information Processing and Transmission Lab (IPT), where I work on the performance analysis and optimization of Intelligent Reflected Surfaces (IRS)-enabled wireless networks, a key technology for 6G. Previously, I was a research intern at the Machine Vision and Intelligent Systems Lab, where I worked on a deep active learning framework for large-scale semi-automated phenotype extraction using BERT NER. We successfully published our work in the prestigious Expert Systems with Applications journal. I have also earned multiple certifications in Python, Reinforcement Learning, and Deep Learning. I am passionate about applying my skills and knowledge to solve real-world problems in the 6G and machine learning domains. I aspire to become a leading researcher and innovator in these domains. Education BE Electrical Engineering School of Electrical Engineering and Computer Science , 3.67 Bachelor in Electrical Engineering National University of Sciences and Technology , 3.67 (2024) GCE Advanced Level The City School, PAF Chapter , 4 A*s (2020) GCE Ordinary Level Shahwilayat Public School , 1 A*, 7 As, 1 B (2018) Internship Experience Information Processing and Transmission Lab, NUST ( 01-Mar-2023 - 31-May-2024 ) I work as an undergraduate research assistant on the performance analysis of intelligent-reflected-surfaces (IRS) assisted wireless networks in real-world environments. As a second part of the project, we will apply reinforcement learning to optimize the deployment and distribution of IRS in multiple real-w Machine Vision and Intelligent Systems Lab, NUST ( 03-Apr-2023 - 01- Feb-2023 ) I worked as an undergraduate research intern on a deep active learning framework for large-scale semi automated phenotype extraction using BERT NER. We used the ClinicalBERT embedding and fine-tuned them for multi-token sequence classification using a Pytorch environment. We utilized 52,000 notes, achieving p
AI enrichment
Wajih Hassan Raza is an undergraduate Electrical Engineering student at NUST with a 3.67 CGPA, specializing in 6G wireless networks and machine learning. He has research experience as a research assistant and intern, contributing to publications in IRS optimization and deep active learning frameworks.
Skills (AI)
["Embedded C", "Python", "Tensorflow", "Keras", "Scikit-learn", "OpenCV", "Matlab", "Proteus", "ADS", "PSPICE", "Octave", "ModelSim Altera", "LabVIEW", "Reinforcement Learning", "Deep Learning", "BERT NER", "PyTorch"]
Status: ai_done