Nationality: Chinese
Background: My name is Huilin, and I am from China. I finished my bachelor’s degree at Huazhong Agricultural University (Information management and information system) and my master’s degree at Leiden University (Computer science: Data science). After that, I worked as a research assistant at Westlake University (computational protein structure analysis).
My research interests: computational biology, post-translational modification, proteomics analysis, disease.
My PhD goals: Use protein design concepts and deep-learning computational methods to develop novel protein-based affinity-binders for detection and quantification of post-translational modifications in proteins and peptides.
My hobbies: Travel, movies, museum, painting
My project in MIPrecise: Designer-protein binders for pan-specific or sequence specific enrichment of pHis, meHis and meLys PTMs
Master thesis: Standardizing nature-inspired algorithms — a unified framework UNIOA for seven swarm-based algorithms.
Based on the core idea of seven selected swarm-based optimization algorithms (SA), we proposed a unified framework UNIOA to make these seven algorithms more understandable on the level of basic mathematics. UNIOA can also help to prevent SA from meaningless repetitions. The detailed process of conducting the UNIOA is illustrated, including the Unified terminologies, the Unified procedure and the Unified framework UNIOA. Meanwhile, practical experiments are performed to verify the reliability of UNIOA. In addition, a demo for automatically designing SA is developed, which introduces a general application of UNIOA. Subsequently, we leave an open discussion on the possibility of extending UNIOA into the whole nature-inspired optimization algorithms, including SA and evolutionary algorithms (EA).