Résumé

Education

GPA: 3.58/4 (9.16/10) (via 154 credits).
Rank: 8/600 students of the School of Electronics and Telecommunications (SET).
Thesis: Designing and deploying a vehicle detection and classification system using ultrasonic sensors and microwave motion detectors for the Intelligent Transportation System. (10/10)

Intrusion Detection System: Creating Bro policy scripts based on behavior-based and signature-based malware analysis to raise the alarm about abnormal activities and building the ElasticSearch, Logstash, Kibana (ELK) Stack to monitor windows system calls.
Malware Detection: Applying network-based machine learning models in order to detect malware and host-based Recurrent Neural Networks (RNNs) to identify ransomware as soon as it runs on a computer system with real experiments in our testbed.
Software-Defined Networking (SDN): SDN-based solutions for moving target defense network protection.
Computer Science Courses: CS109 Data Science, 6.006 Introduction to Algorithms, Statistics 110: Probability, Machine Learning by Stanford University on Coursera, Big Data 101, Statistics 101, Deep Learning 101, Deep Learning with Tensor Flow, Spark Fundamentals I&II, BerkeleyX: CS105x, BerkeleyX: CS110x, BerkeleyX: CS120x.

Linux Kernel: Developing Linux device drivers with the aim of optimizing the power consumption of components of a system on a chip (SoC), such as CPU, GPU, and DDR, as well as ensuring the performance of mobile phones and wearable products.
Tizen Framework: Working on RPM, Red Hat Package Manager, packages that belong to the OEM Adaptation Layer (OAL) interms of advanced power management solutions.
RPM applications: Building auxiliary software and automated testing tools in order to support testers, the Quality Assurance (QA) team, and third parties.

Intelligent Transportation System (ITS): Detecting, measuring and classifying different types of cars using various sensors (ultrasonic sensors, microwave motion sensors, infrared sensors, inductive loops, etc.) combined with microcontrollers.
Wireless Sensor Ad-hoc Network (WSAN): Evaluating the energy consumption of Wireless Sensor Ad-hoc Networks with the use of different solutions for the Mobile Object Tracking problem, like the Kalman filter or the Particle filter, using NS2.
Speech-Like Symbol Design for Data Transmission through GSM Voice Channel: Encoding digital data into Speech-Like (SL) symbols using MATLAB to transmit through the Global System for Mobile communications (GSM) voice channel.

2017 Big Data 101, Cognitive Class Certificate of Completion. (BD0101EN)
2017 Statistics 101, Cognitive Class Certificate of Completion. (ST0101EN)
2017 Deep Learning 101, Cognitive Class Certificate of Completion. (ML0115EN)
2017 Deep Learning with Tensor Flow, Cognitive Class Certificate of Completion.(ML0120E)
2017 Machine Learning, Machine Learning by Stanford University on Coursera. (ML)
2017 Spark Fundamentals I, Cognitive Class Certificate of Completion. (BD0211EN)
2017 Spark Fundamentals II, Cognitive Class Certificate of Completion. (BD0212EN)
2017 Spark MLlIB, Cognitive Class Certificate of Completion. (BD0221EN)
2018 Exploring Spark’s GraphX, Cognitive Class Certificate of Completion. (BD0223EN)
2018 SparkR, Cognitive Class Certificate of Completion. (RP0105EN)

2016 The Best Employee, The Best Employee in Quarter II/2016 of SVMC. (Award)
2013 Finalist, The 31st Conference on Student Scientific Research of HUST. (Merit)
09-14 Scholarships, Scholarships of HUST for students having good study results

Programming: Python, R (Certificate), Scala, C/C++, Shell Scripts, Java, mySQL, Matlab.
Technical Tools: Jupyter Notebook, Sublime Text, Eclipse IDE, Source Insight, Visual Studio, Wireshark PCAP Tool.
English: IELTS 6.5 (Listening: 6.5, Reading: 7.0, Writing: 7.0, Speaking: 6.0). (Ielts)

Technology: State-of-the-art Technologies, Mathematics, Algorithms, Probability and Statistics, Programming.
Hobbies: Football, Music, Traveling, Charitable Activities.