Abdolvakil Fazli

 EDUCATION Sadjad University of Technology, Mashhad, IranOctober 2017 BSc in Electrical Engineering “Concentration: Electronics”, GPA 18.06/20 Thesis title: cooperative spectrum sensing for secondary users (19.25 out of 20) Politecnico di Milano university, Milan, Italy March 2019 Master’s in Signals and Data Analysis, average (27.53/30) INTERESTS Statistical Signal processing Machine learning Data analysis Deep Learning COMPUTER SKILL Cognitive Radio Networks Reinforcement Learning Wireless Communications Programming: proficient in generating and compiling various MATLAB, C++ and Python-based scripts and implementing algorithms. Software: Microsoft Excel Project, Latex, Radio mobile. EXPERIENCES Teaching assistant at Electrical Engineering Department. Sadjad University of Technology, Mashhad, Iran Responsible for teaching related duties to aid professor with and obtain and produce material needed for class such as visual aids, answer keys, supplementary note, and blackboard materials as well as Setting up simulation and laboratory activities Holding office hours to clarify course materials and help students with their problems and individual projects Review and evaluation of student’s performance TA Courses: Mathematics I, Differential Equations, Engineering Mathematics, Analogue and Digital Electronics, Fundamentals of telecommunication Systems I & II (Analogue and Digital). Master’s student in Politecnico di Milano2018(ongoing) Important Courses: Advanced Digital Signal Processing, Wireless Communications, Machine learning, Information theory, Model identification and data analysis, Digital Communications, Data intelligence applications. projects in master’s degree: Adaptive pre-distortion in digital communication systems: Using both Simulink and MATLAB script Rate adaptation in an optical communications system using probabilistic shaping method, an information theoretical approach: a collaboration with Nokia. Channel estimation and system Identification and deconvolution problem in MIMO systems: for both with memory and memory-less channels. Adaptive beamforming in 3GPP scenario with various moving UEs: Using LMS algorithm and MUSIC estimator, comparing the performance of the system in terms of BER in different snapshots of moving UEs. Adaptive filtering and interference mitigation: for Stereo signals in various scenarios; Adaptive noise cancellation, frequency sinusoid cancellation, etc. Combinatorial multi-arm bandit in different applications: Social influence, Matching, Advertising, and Pricing scenario to maximize the influence of different messages given a daily budget and number of users as constraints.