Glen Christy Fernandes
Email: firstname.lastname@example.org LinkedIn: https://www.linkedin.com/in/glencfernandes Mobile: +1-480-***-**** Education
• Master of Science – Arizona State University Tempe, AZ Computer Engineering – Computer Systems; GPA: 4.0 Jan 2020 – Dec 2021
• Bachelor of Engineering – R V College of Engineering Bangalore, India Electrical and Electronics Engineering; GPA:3.8 Aug 2013 – May2017 Technical Skills
• Programming Languages: Python, SQL
• Frameworks and libraries: TensorFlow, Keras, SciKit-Learn, OpenCV, Git, Tableau, Linux, Wireshark, SOAP UI, Postman, Selenium, Robot Framework.
• Technologies: Machine learning, Deep Learning, Computer vision, Natural Language Processing. Relevant Coursework
Foundations of Algorithms, Natural Language Processing, Statistical Machine Learning, Data Mining, Random Signal Theory, Python for Rapid Engineering Solutions, Programming in C, Digital Logic Design, Signals and Systems, Digital Signal Processing. Experience
• Wipro Limited Bangalore, India
Software Engineer Aug 2017 – Dec 2019
Developed and implemented testcases to automate mobile network testing using python, Selenium and Robot automation framework for the T-Mobile DIGITS application.
Automated various features like NSIM, M-store and SMSC.
Performed execution of regression suites and analysis for the failure of test cases. o NetApp:
Storage Quality Analyst
Developed test suite for testing resiliency of SMB protocol, by configuring the NetApp filer using REST APIs. Implemented I/O load testing to perform systemic testing of NetApp data management software ONTAP.
• ABB India Limited Bangalore, India
Intern May 2015 – Jun 2015
Researched on SCADA automation and substation communications and learnt how to implement relay and PLC controls under the substation automation protection and control division. Academic Projects
Title: Solving Math Word Problems using Pre-Trained Language Models Objective: To solve simple Math Word Problems described in natural language using Large pre trained Language Models such as BERT and GenBERT and fine tuning the models to solve math word problems. Title: Time Series Analysis of CGM data for predicting meal and no meal information of diabetic patients. Objective: Performed feature engineering on time series data of CGM sensors to extract the best features for prediction. Applied classifiers on the extracted features to predict meal or no-meal info for diabetic patients achieving an accuracy of 65%. Title: Classifying COVID-19 From Chest X-rays Utilizing Pre-Trained Convolutional Neural Networks. Objective: Developed a model using pre-trained models built from Deep Convolutional Neural Networks (DCNNs) with transfer learning to extract embeddings from the images and which in turn are used as feature vector for classification using a machine learning classifier.
Title: IoT based automation of greenhouse irrigation Objective: To monitor the moisture of greenhouse plants, water them and obtain the value via cloud. This was achieved by using ESP8266 as the Wi-Fi module and TCP-IP as the communication protocol. Title: Human Machine Interface based automation for disabled people. Objective: To effectively control the motion of the wheelchair by processing the images of hand gestures from a live video using MATLAB and interfacing the output from MATLAB to a PIC microcontroller.