Software, Data, People & Society
Sigurdsgade 41, 2200 København N.
Fields of interest
· Data Management systems
· Spatial Data
· Social Computing
· Machine Learning
My scientific focus areas are on building scalable and efficient data management systems. My current research work explores a new actor-based programming abstraction and corresponding cloud-based system design, implementation and optimization to manage data and facilitate online coordination for intelligent moving object applications. The latter applications include autonomous systems scenarios, such as fully automated taxi services and agricultural harvesting operations. This research project promises to deliver results at a highly ranked conference in data management.
I have explored the question of how to model and build IoTs applications with actor-oriented databases. This work is of high relevance, as it presents analysis grounded on real-world needs and provides guidelines to practitioners on how to realize the potential of this exciting class of applications by leveraging new actor-oriented database technology. I have articulated the open challenges in building new systems to serve spatial data scalability in a multi-core and multi-node setting at the beginning of PhD study.
Primary fields of research
· 2020/12-Present An Evaluation of Spatial Partitioning Techniques to Handle Skew in Moving Actor-Oriented Databases
Our work is to achieve scalability through parallelism and distribution in M-AODBs. We utilize spatial partitioning, which directly affects load balance in the split of movement processing as well as tail latencies in the communication induced by reactions, solving the challenge of tolerating spatial skew in the distribution of reactive moving objects.
· 2019/03-Present Moving Actor-Oriented Databases: A Data Management Framework for Reactive Moving Object Applications
our work is to combine a new actor-based programming abstraction and corresponding cloud-based system design and implementation to manage data and facilitate online coordination for the Internet of Moving Things.
· 2019/05-2019/10 Dolphin Demo: A Scalable Actor-Oriented Spatial Database for Smart Farms
Build a scalable actor-oriented spatial databases demo for increasing heterogeneous dynamic farming data. This database can handle frequent data updates, necessitate real-time analysis and provide notification based on continuously changing smart farm data.
· 2018/09-2019/04 Modeling and Building IoT Data Platforms with Actor-Oriented Databases
Due to the challenges presented by IoT applications, good scalability of data-intensive IoT data management and processing platforms is now required. Our work offers a novel approach and guidances to model and builds IoT data platforms based on the characteristics of an Actor-Oriented Database.
· 2017/06–2018/09 Vecstra: An Efficient and Scalable In-Memory Database for Vector and Raster Geospatial Data
In response to the increasing demand for access to a wealth of geospatial data originating from new sensing technologies, we build a world-wide geospatial standards-compliant in-memory data management system. The design goals of this geospatial database system are to provide for high throughput, low latency and efficient resource usage in geospatial data management and online analysis.
· 2016/03–2017/03 Personalized Travel Route Planning based on POI in Spatial Network
We implemented a system combining social hotspot data and spatial data in the city of Nanjing to make personalized travel trip recommendations.
· 2015/09–2015/12 Personalized Travel Itinerary Planning based on Multi-objective Optimization Algorithm under Multi-Constraints
We proposed a a multi-objective optimization problem under multi-constraints. An evolution strategy of non-dominated sorting ranking and Tabu search was employed to handle the optimization of this problem.
· 2015/03–2015/09 Prosodic Head Motion Generation From Text for a Chinese Talking Avatar
We designed a prediction model on a talking avatar based on the relationship between text-based prosodic features and nodding of head movements.
· 2015/03–2015/06 Research of Neural Network Problem: Weather Forecast Classification
We finished a weather forecast application based on MFNN neural networks by using the historical data of different cities.
· 2013/12–2014/06 Research and Implementation of CCSDS Image Compression Algorithm
We implemented the CCSDS standard algorithm that conducts image compression on discrete wavelet transform and bit-plane coding.