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							<h1>Ruitao Wu</h1>
							<p>MASTER CANDIDATE</p>
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							<h2>About</h2>
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							<p>My name is <strong>Ruitao Wu</strong>, I am pursuing my Master's degree in Computer Science field at <b> <a href="https://www.sdsu.edu/">San Diego State University</a></b></p>
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							<h2>Education</h2>
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							<p> <strong> M.S.</strong> <i>Computer Science</i><br>Department of Computer Science
								<br>College of Science
								<br>San Diego State University
								<br>San Diego, CA, USA
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							<p> <strong> B.S.</strong> <i>Computer Science</i><br>Department of Computer Science
								<br>College of Engineering & Computer Science
								<br>CSU, Northridge
								<br>Northridge, CA, USA
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							<h2>WORK</h2>
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							<p><strong>Research Assistant</strong>&nbsp;&nbsp;<span>01/2023 -- Now </span></p>
							<p><strong>Research Assistant</strong>&nbsp;&nbsp;<span>05/2021 -- 06/2022 </span></p>
							<p><strong>Instructional Student Assistant</strong>&nbsp;&nbsp;<span>01/2022 -- 05/2022</span></p>
							<p><strong>Tutor -- Computer Science</strong>&nbsp;&nbsp;<span>08/2021 -- 12/2021</span></p>
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							<h2>Research</h2>
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								<i class="fa fa-bookmark" aria-hidden="true" style="text-align:  center;">Networked Airborne Computing System</i>
								
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							<p>Abstraction:The integration of onboard computing capabilities with unmanned aerial vehicles (UAVs) has gained significant attention in recent
								years as part of mobile computing paradigms such as mobile edge computing (MEC), fog computing, and mobile cloud computing.
								To enhance the performance of airborne computing, networked airborne computing (NAC) aims to interconnect UAVs through
								direct flight-to-flight links, with UAVs sharing resources with each other. However, despite the growing interest in NAC and UAV-
								based computing, existing studies rely heavily on numerical simulations for performance evaluation and lack realistic simulators and
								hardware testbeds. To fill this gap, this paper presents the development of two NAC platforms: a realistic simulator based on ROS and
								Gazebo, and a hardware testbed with multiple UAVs communicating and sharing computing resources. Through comprehensive
								simulations and hardware tests, we evaluate the two platforms, examine the impact of key factors on NAC performance, and
								showcase the practical application of NAC. The findings offer valuable insights into the field of NAC and provide guidance for
								future advancements in this area.</p>
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								<li><a href="https://smile.sdsu.edu/">The SysteMs &amp; InteLligEnce Laboratory</a></li>
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								<i class="fa fa-bookmark"> <a href="https://github.com/CalTransProject/CalTransProjLearningModel" style="text-align:  center;">CalTrans Project</a></i>
								
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							<p>Abstraction: Vehicle detection plays an important role in analyzing traffic
								flow data for efficient planning of traffic management projects. Machine Learning
								technology has been increasingly used for vehicle detection. Adverse weather
								conditions prove to be challenging for 2D vehicle detection. There is a lack of
								research on real-time vehicle detection using LiDAR point clouds which are more
								resistant to adverse weather conditions. In this project, we proposed a system that
								collects real-time traffic data, processes it for vehicle detection, and provides a
								web-based user interface with real-time statistical data visualization and 2D realtime detection stream. We processed 2000 images from the 2D videos that were
								collected and trained a model on Darknet using YOLO algorithm. Approximately
								7000 frames LiDAR data was labeled and pro-processed, and a new deep learning
								model was proposed for training and testing. Our system improved vehicle type
								detection compared with the original YOLO pretrained model.</p>
							

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								<li class="fa fa-file-pdf-o"> <a href="assets/curriculumvitae/Ruitao_Wu_CV.pdf">Curriculum Vitae</a> </li>
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								<li class="fa fa-file-pdf-o"> <a href="assets/curriculumvitae/Ruitao_Wu_Resume.pdf">Resume</a> </li>
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							<h2>Publication</h2>
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								<i class="fa fa-book" aria-hidden="true"><FONT COLOR=red>R. Wu</FONT> et al "Real-time Vehicle Detection System for Intelligent Transportation using Machine Learning," 2022 IEEE Green Energy and Smart System Systems (IGESSC), Long Beach, CA, USA, 2022, pp. 1-6, doi: 10.1109/IGESSC55810.2022.9955329. </i>
								<a href="https://ieeexplore.ieee.org/document/9955329"><i class="fa fa-cloud-download" aria-hidden="true"></i></a>
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							<h2>Conference</h2>
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								<i class="fa fa-book" aria-hidden="true">2022 IEEE Green Energy and Smart System Systems (IGESSC), Long Beach, CA, USA</i>
								<a href="https://site.ieee.org/clas-sysc/igessc-2022/"><i class="fa fa-external-link" aria-hidden="true"></i></a>
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							<h2>Academic Service</h2>
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								<i class="fa fa-circle-o" aria-hidden="true">Summer Camp Counselor -- 2023</i>
								<p>Host Information: The SysteMs &amp; InteLligEnce Laboratory (SMILE) and Talent Search SDSU.<br> Summer Camp Supervisor: Junfei Xie, PhD, SMILE Director</p>
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								<i class="fa fa-circle-o" aria-hidden="true">STEM Pathways Mentor -- 2023</i>
								<p>Mentoring understagrand students in STEM field, and support them finish their research project in certain durination and provide all technical consultant.</p>
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							<h2>Award/Honner</h2>
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								<i class="fa fa-flag" aria-hidden="true">Dean’s List Fall 19 | Fall 20 | Spring 20</i>
								<p>College of Engineering and Computer Science <br>California State University, Northridge</p>
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								<i class="fa fa-flag" aria-hidden="true">Senior Design competition FIRST place in Department of Computer Science</i>
								<p>College of Engineering and Computer Science <br>California State University, Northridge</p>
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							<h2>Presentation</h2>
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								<i class="fa fa-users" aria-hidden="true"> IEEE Green Energy and Smart Systems Conference--Student Poster Competition Session</i>
								<p>2022 IEEE Green Energy and Smart System Systems(IGESSC)</p>
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								<i class="fa fa-users" aria-hidden="true">CSU, Northridge’s Autonomy Research Center for STEAHM poster presentation at JPL -- 2022</i>
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							<h2>Membership</h2>
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								<i class="fa fa-user-circle-o" aria-hidden="true">The SysteMs &amp; InteLligEnce (SMILE) Laboratory<a href="https://smile.sdsu.edu/group.html">Current</a></i>
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								<i class="fa fa-user-circle-o" aria-hidden="true"> Laboratory for Sustainable and Additive Manufacturing  <a href="https://www.ecs.csun.edu/~bingbing/people.html">Alumni</a></i>
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								<i class="fa fa-user-circle-o" aria-hidden="true"> NASA -- The Autonomy Research Center for STEAHM <a =href="https://arcs.center/2021-2022-arcs-fellows-associates/">Student Fellow</a></i>
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