- Innovative problem solver: Lead and drive innovation activities within the Data Assurance team, addressing client pain points by applying advanced technologies. This commitment ensures the delivery of high-quality services that effectively solve our clients' challenges.- PwC Pay Lab initiator: Conceptualized and led the development of PwC Pay Lab, a solution that enables efficient and reliable compliance investigations for Australian modern awards and enterprise agreements. It has successfully supported 20+ engagement deliveries.- Financial big data architect: Designed and implemented financial big data processing solutions, leveraging parallel computing and cloud technology (Spark / Databricks / Azure). Successfully reduced data processing time of a time-consuming engagement from several months to days.- Team development leader: Lead internal training and development initiatives and inspire the team to develop and leverage their data science skill set in projects.

Wage Trust- Developed a scalable, Python-based Australia modern award compliance system that can be easily customized to support various awards and business enterprise agreements.- Designed and implemented a wage reconciliation data analysis solution that provides standardized data handling and efficient & reliable data analytics.- Leveraging the award modeling and wage reconciliation solution, the team has successfully served clients by identifying risks in their payroll and roster systems. As a result of our outstanding performance, my team were nominated as one of our clients pay roll partner and secured several engagements worth over one million in value.

Finance advice remediation- System designer and key developer of multiple automatic document processing tools. The OCR and NER based document processing tools could process scanned document images more efficiently and reliably.- Developed remediation backend, dockerized it and deployed on the cloud to provide automatic QA & QC services. Invoice Analyzer- Designed and developed an automatic invoice analyzer tool, which leveraged business rules, NER and google applications to auto-label the fraudulent invoices and significantly speed up the invoice processing.

Noah’s Ark Lab (AI Lab of Huawei Technologies) Machine learning for high-efficiency wireless communications- Worked as a key data scientist of the Noah’s Ark lab, which is the company’s flagship AI lab and focuses on leveraging machine learning technologies in commercial products and services.- Supported product team to clarify technical requirements and identified corresponding machine learning problems.- Compared SVM, Random Forest and Gaussian Process Regression (GPR) on the given datasets through extensive performance evaluation.- Proposed a GPR based algorithm to facilitate system parameter selection. The proposed algorithm outperformed the existing one by over 30% on production data.Reinforcement learning for autonomous parking- Explored the feasibility of reinforcement learning (RL) for autonomous vehicle control under various driving scenarios (parking areas, urban streets, rural road and campus roads).- Trained the neural network based RL model on extensive simulations, where different parking scenarios were considered. Based on the output of the RL model, the testing vehicle realized autonomous parking without human instructions when it was exposed to different parking styles, such as angled vs. perpendicular parking.- Proposed a novel algorithm to reduce exploration states for training the RL model and accelerated the training process significantly. A corresponding patent was filed.

Communication Technology Lab- Regulated internal proposal review procedure and led the team reviewed and analyzed 200+ IEEE 802.11ah proposals and thus fully understood the major tech trends of the standard group. - Focused on the research of low power IoT applications, filed 20+ patents and submitted several proposals to IEEE 802.11ah standard group. - Promoted ideas in the standard group as an IEEE 802.11 delegate. Multiple proposals were accepted and involved in standard document (IEEE 802.11ah).- Explored next generation IoT systems based on cellular networks. Focused on the enhancement of the LTE system for M2M communication.

- 802.11 system modeling, analysis, algorithm evaluation and optimization- Resource management algorithm design for wireless communication systems - Mathematical modeling of 802.11 MAC layer performances under different traffic load conditions. The corresponding papers were presented on international conferences.- Proposed new algorithms for wireless mesh networks. Multiple papers were accepted by top tier international conferences.- Co-supervised PhD students