Research Assistant @ Aalto University School of Science and Technology
Summer Trainee @ SAMSUNG Electronics R&D Center
Bachelor’s Degree, Faculty of Computer Science @
Nanjing University of Posts and Telecommunications
I am a researcher in the Computational Systems Biology Laboratory, Genome-Scale Biology Research Program, and a Phd student in University of Helsinki. My research is along the direction of machine learning, and data and graph mining for genome-scale data which are high-throughput big data. My focus is to develop and/or apply machine learning and data/graph mining methods
I am a researcher in the Computational Systems Biology Laboratory, Genome-Scale Biology Research Program, and a Phd student in University of Helsinki. My research is along the direction of machine learning, and data and graph mining for genome-scale data which are high-throughput big data. My focus is to develop and/or apply machine learning and data/graph mining methods to identify patterns or clusters behind the cancer patients.
★ 5+ years project research and manage experience on analyzing cancer patients and identifying prognostic markers and subtypes using high throughput data.
★ Special skill of analyzing different types of data and discovering patterns and new insights.
★ Strong skills of developing new methods and integrating different types of data (e.g., transcriptome, genome, epigenome and interactome) to discover new insights and identify therapeutic markers.
★ Familiar with many analytical algorithms/tools related to high throughput data analysis.
★ Learning capacity, creativity, and passion for data analysis and discovering patterns.
★ Excellent programming skills using R, C, SQL, Matlab in Linux.
I like sports, especially competitive and thrilling sports such as football and downhill. I also enjoy fishing, hiking and camping. I am a super fan of science fiction movies where new technologies and future world are imagined. I like catching up new techs and crazy ideas and exploring unknown world.
University Researcher @ ★Develop and apply methods (e.g., machine learning, data/graph mining, clustering methods) to predict cancer patients with low and high survival risks, and to identify features/predictors associated with patient survival risks. The challenges are high dimensionality of data features which are problematic for traditional machine learning methods, and multi-level data sources which should be integrated properly to perfect the patient profiles.
★Identify subgroups of cancer patients associated with clinical features using machine learning scheme which includes model selection, optimization of the number of subgroups, feature selection and independent validation.
★Predict graph structure using Gaussian probabilistic model to discover the relevance between features in cancer patients. From April 2010 to Present (5 years 9 months) FinlandResearch Assistant @ We predicted network signal environment to reduce energy consumption of smart phone using Auto Regressive Integrated Moving Average (arima), Newton Forward Interpolation (NFI) and Markov chain (MC) methods. We proposed and evaluated a prediction-based power adaptation. I implemented all the algorithms and adaptation codes independently. I participated in data analysis as well. From December 2009 to March 2010 (4 months) FinlandSummer Trainee @ Participated to test and documentation of mobile phone operating system.
Participated to set up text corpus and development of core decoder in Machine Translation Project. From July 2006 to September 2006 (3 months) China
Master’s Degree, Computer Science @ Helsingin yliopisto / University of Helsinki From 2008 to 2011 Bachelor’s Degree, Faculty of Computer Science @ Nanjing University of Posts and Telecommunications From 2004 to 2008 Chengyu Liu is skilled in: Machine Learning, Algorithms, R, Bioinformatics, Computational Biology, Genetics, LaTeX, Python, Matlab, Pattern Recognition, Computer Science, Mathematical Modeling, Data Mining, Science, Information Retrieval
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