Yuan-Yao Lou
yylou [at] purdue [dot] edu yylou Google Scholar yylou Gitbook
About
I'm a fourth-year Ph.D. student in the School of Electrical and Computer Engineering at Purdue University as part of EDGE Lab, co-advised by Prof. Mung Chiang and Prof. Kwang Taik Kim.
My research interests lie in the intersection of (1) the architectural design of distributed systems to jointly optimize network and application performance, and (2) machine learning in the realms of wireless system design in 5G/6G networks. I am deeply passionate about distributed systems (resource allocation for server load-balancing), computer networking (virtualization of 5G/6G networks), and deep reinforcement learning (DRL) for optimization.
Prior to joining Purdue, I was a senior software engineer with 3 years of experience in (1) the development of microservice-based systems in on-premise Linux servers for automating IC/EDA design flow, and (2) the cloud application development on AWS. I received my B.S. and M.S. degrees in Computer Science (CS) from National Chiao Tung University (NCTU) and National Taiwan University (NTU) in 2015 and 2017, respectively.
My research interests lie in the intersection of (1) the architectural design of distributed systems to jointly optimize network and application performance, and (2) machine learning in the realms of wireless system design in 5G/6G networks. I am deeply passionate about distributed systems (resource allocation for server load-balancing), computer networking (virtualization of 5G/6G networks), and deep reinforcement learning (DRL) for optimization.
Prior to joining Purdue, I was a senior software engineer with 3 years of experience in (1) the development of microservice-based systems in on-premise Linux servers for automating IC/EDA design flow, and (2) the cloud application development on AWS. I received my B.S. and M.S. degrees in Computer Science (CS) from National Chiao Tung University (NCTU) and National Taiwan University (NTU) in 2015 and 2017, respectively.
PhD / ECE / @Purdue Software Engineering Computer Network Edge Computing Machine Learning 5G/6G
Skills
Research
Wireless Communication Distributed System Cloud-Edge Computing Cellular Networks (4G/5G/6G) Reinforcement Learning Resource Allocation and Scheduling Deep Reinforcement Learning (DRL) Multi-Agent Reinforcement Learning (MARL) Federated Learning (FL) Large AI Models (LAM) Large Language Models (LLM) Languages
Python C++ Java Javascript Shell Script CUDA SQL Tools
PyTorch TensorFlow Scikit-learn Numpy Seaborn SimPy OpenAI Gym Git Vim Cloud
Grafana Prometheus Docker Telegraf InfluxDB Flask/Eve Django/MongoDB RESTful HTML/CSS Platforms
Linux AWS Google App Engine Android ROS / MuSHR Cisco (Wi-Fi 6E) Amarisoft (4G/5G) Intel/Radisys RAN Publications
[11]
Multi-Agent Reinforcement Learning for Cellular Networking in 5G/6G
(under review) Virtualized RAN Reinforcement Learning Resource Optimization System-level Simulator 5G NR Sub-6 [10]
Real-time Multi-Object Tracking System for Embedded Devices
(under revision) Computer Vision Deep Learning Multi-Object Tracking Real-time Comunication Embedded Device [9]
Y.-Y. Lou,, J. Spencer, K. T. Kim, M. Chiang
arXiv preprint arXiv:2410.00695 [cs.DC]
(under review) Edge Computing Automonous Driving Path Planning Computation Offloading Time-critical Communcation [8]
Y.-Y. Lou,, J. Spencer, K. T. Kim, M. Chiang
arXiv preprint arXiv:2409.19834 [eess.SY]
arXiv Automonous Driving Model Predictive Control Probability Sampling Optimization Data Collection and Analysis [7]
X. Li, M. Abdallah, Y.-Y. Lou, M. Chiang, K. T. Kim, S. Bagchi
arXiv preprint arXiv:2409.10839 [cs.NI]
(under review) Edge Computing Distributed Systems Task Scheduling Real Testbed CBRS 4G / 5G Sub-6 [6]
S. B. Weinstein, Y.-Y. Lou, T. R. Hsing
IEEE International Conference on Microwaves, Communications, Antennas, Biomedical Engineering and Electronic Systems, 2021
IEEE COMCAS 21' Edge Computing Distributed SDN [5]
Y.-Y. Shih, A.-C. Pang, Y.-Y. Lou
Fog and Fogonomics: Challenges and Practices of Fog Computing, Communication, Networking, Strategy, and Economics, 2020
Book Chapter Edge Computing Computation Offloading Wearable Device System Design Android [4]
Modularized Service Provisioning at Fog Networks
Y.-Y. Shih, A.-C. Pang, Y.-Y. Lou, C.-C. Chuang, L. Zhao, Z. Ren
IEEE Vehicular Technology Society Asia Pacific Wireless Communications Symposium, 2018
IEEE VTS APWCS 18' Edge Computing Computation Offloading Microservice System Design [3]
Y.-Y. Lou
National Taiwan University Master's Thesis, 2017
NTU Fog-Edge Computing Microservice Offloading Android Wear Testbed Deployment [2]
H.-P. Lin, Y.-Y. Shih, A.-C. Pang, Y.-Y. Lou
ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2016
ACM MSWiM 16' Edge Computing Function Module Sharing Resource Allocation Greedy / Heuristic Education
Aug. 2021 - May. 2026
Purdue University
West Lafayette, IN, USA
Ph.D. student in Electrical and Computer Engineering
GPA: 3.7 / 4.0
Sep. 2015 - Jun. 2017
National Taiwan University
Taipei, Taiwan
M.S. in Computer Science
GPA: 3.8 / 4.0
Jun. 2013 - Aug. 2013
Rice University
Houston, TX, USA
English as a Second Language (ESL) Program - Level 5
Sep. 2011 - Jun. 2015
National Chiao Tung University
Hsinchu, Taiwan
B.S. in Computer Science
GPA: 3.8 / 4.0
Honors . Awards
Jun. 2021
IEEE 7th World Forum on Internet of Thing (WF-IoT)
Dec. 2020
IEEE Winter School on Fog/Edge Computing
IEEE SA & ComSoc
Jun. 2017
Valedictorian of Graduation Ceremony
Dept. of CS, National Taiwan University
Feb. 2017 / May. 2017
Outstanding Teaching Assistant Awards
x2
National Taiwan University
Jun. 2014 / Jun. 2015
Presidential Awards
x2
National Chiao Tung University
Jul. 2014
Research Project Funding (103-2815-C-009-043-E)
National Science and Technology Council (Taiwan)
Experience
Mode: All Research Industry Aug. 2021 - Present
Purdue University - EDGE Lab
West Lafayette, IN, USA
Graduate Research Assistant
Edge Computing RAN Autonomous Driving Computation Offloading AI-ML / DRL for Joint Optimization of Network and Application in 5G/6G[11] Trained multi-agent reinforcement learning (MARL) model for network deployment policy by considering multi-dimensional trade-offs in joint optimization Edge Computing for Path Planning in Autonomous Driving[8, 9] Optimized local path planning by collaborative and sampling-based model predictive control (MPC) method with driving data analysis in edge networks Network Testbed Deployment for Smart Factory Applications (Digital Twin) Deployed 5G and Wi-Fi 6E testbeds and trained DL model for defect detection using Amazon dataset (ARMBench) for performance comparison and analysis Multi-object Tracking (MOT) and Detection System for Embedded Devices[10] Designed MOT system by using static and dynamic matching approaches along with content-aware dynamic sampling technique, achieving 63.12% MOT accuracy Multi-tier Computation Offloading Framework in 6G Edge Cloud[7] Proposed multi-tier edge computing system including device cloud concept to schedule offloading tasks in 4G testbed, optimizing latency and reducing cost Leadership and Collaboration Mentor undergraduate students to study Robot Operating System (ROS) and explore computer networking projects in 5G area Work with industry partners with 10+ engineers to bridge the gap between theory and practice of deploying and orchestrating software-defined cellular systems Collaborate with Purdue research teams on AI IoT and Industry 4.0 projects including collaborative video analysis for multi-object tracking (MOT) [7, 10]
Apr. 2021 - Aug. 2021
IoT Eye Inc.
NJ, USA / Taiwan
Remote
Full-stack Cloud Developer, Internship
DevOps AWS EC2 Web Frappe Flask Open-source DevOps and Cloud Application Development Deployed multi-agency management platform on AWS using Frappe framework to support five industry partners Developed DevOps toolkit in Python automating product deployment and management to improve scalability Automated Flask Eve API testing using Postman and Python to boost product robustness Enhanced free-trial feature of Bootstrap-based official website to speed up product delivery Released internal documents of developed products and tools and publish tutorial of Frappe pp development on GitHub
GitHub Repo Dec. 2020 - Aug. 2021
Independent Researcher
IEEE
NY, USA / Taiwan
Remote
Collaborator: Prof. Stephen B. Weinstein and Prof. T. Russell Hsing
Edge Computing Distributed SDN Presentation Distributed SDN and Edge Computing for 6G Networks Proposed distributed SDN system coupled with localized edge platforms and storage to support emerging applications such as autonomous driving Served as speaker in Edge and Fog Computing track on IEEE 7th World Forum on Internet of Things (WF-IoT) in 2021 Published an introductory paper on IEEE COMCAS 2021 [6]
IEEE WF-IoT Dec. 2017 - Apr. 2021
Silicon Motion - Algorithm and Technology R&D Center
NASDAQ: SIMO
Milpitas, CA, USA / Taipei, Taiwan
Supervisor / Senior Software Engineer
System Design Microservice Automation Tool Dev Leadership Design Flow Automation and In-house EDA Tool Development Deployed microservice system in on-premise servers to automate 7/16 nm IC design flows, boosting development efficiency and improving verification robustness Developed in-house design verification tools reviewing timing and power requirements to improve reliability Automated library maintenance flow using Python and shell script to save manual effort by up to 80%
Leadership and CommunicationActed as project leader to cooperate with industry partners (TSMC, Synopsys) for establishing design flows in new IC technology nodes Cooperated with Human Resources as technical campus recruiter to promote on-campus brand awareness Established programming disciplines (Python) and organized training sessions for new employees
Promoted twice within 24 months for outstanding performance on software development and solution finding
Leadership and Communication
Sep. 2015 - Sep. 2017
National Science and Technology Council (Taiwan)
Taipei, Taiwan
Graduate Researcher
Microservice Wearable Computing Android Web Django Microservice-based Computation Offloading for Wearable Devices Proposed microservice-based function module sharing framework (Virtual Local-Hub) for Android wearable devices by edge computing and WiFi P2P concept Modified Android Wear OS to intercept system calls and redirect application API calls to wireless base stations for offloading orchestration Reduced execution time of wearable microservices by up to 60% and CPU usage by up to 70% Published conference paper on ACM MSWiM 2016 and book chapter in 2020[2, 3, 4, 5]
Networked System DevelopmentBuilt WLAN testbed from scratch including DHCP and NAT to evaluate E2E latency and power consumption of wearable edge computing framework Designed telemetry platform using Django to monitor system performance and manage service provisioning Developed latency-sensitive applications on Android devices such as speech recognition in natural language processing by CMUSphinx
Networked System Development
Portfolio
Jul. 2014 - Mar. 2015
Princeton University - EDGE Lab
Princeton, NJ, USA
Research Intern / Mentor: Prof. Mung Chiang and Dr. Ming-Jye Sheng
Markov Chain 4G LTE RAN RRC/DRX IoT 4G LTE IoT Session Management for Balancing Latency, Power, and Signaling Built Markov chain model based on RRC inference algorithms in AT&T tools to analyze DRX impact on 4G LTE IoT session factors (signal load, power, delay) Conduct probabilistic model simulations to reveal the efficacy of algorithms in power saving and signal reduction for IoT Developed toolkits based on AT&T Lab tools to analyze packets and profile Android apps performance Improved power saving by up to 50% and signal saving by up to 60% for packets within 0.1s delay Published a journal paper in IEEE Internet of Things Journal (IoT-J) in 2016 [1]
Teach
Feb. 2016 - Jan. 2017
Teaching Assistant
Taipei, Taiwan
National Taiwan University - CSIE 3510 Computer Network / CSIE 5057 Advanced Computer Network
TCP/IP Chatbot Socket Programming TCP/IP & Socket Programming in C++/Python Lectured TCP/IP protocol (802.11, 802.3) and demonstrated network packet monitoring and analysis using WireShark Designed IRC chatbot application as project assignment to teach students socket programming Enhanced program robustness by peer-testing system and promoted creativity by flexible score criterion Assigned paper readings and hold course seminar for final evaluation Received two times of Outstanding Teaching Assistant awards