胡伦老师作为第一作者的论文“Identifying Overlapping Protein Complexes in Yeast Protein Interaction Network via Fuzzy Clustering”（基于：劾嗍侗鹂芍氐蛋白质复合物的算法研究）被FUZZ-IEEE 2017录用并应邀做口头报告。
胡伦老师于2017年7月8日－2017年7月14日出席在意大利那不勒斯市的FUZZ-IEEE 2017会议（：低彻恃趸嵋椋。FUZZ-IEEE是：低沉煊虻闹嵋。会议每年在世界不同地方召开，与会者讨论：低吃诶砺鄯矫婧拖喙赜τ昧煊虻难芯亢头⒄。议题包括：呒刂、：氖Ш屠砺刍、：霾呦低、：萃诰、Type-2：拖低扯喔銮把乜翁。参加会议的具体行程如下：
7月7日由武汉出发，经巴黎转机，于7月8日抵达那不勒斯市，7月9日至10日参加会议分组讨论，并于7月11日在大会做口头报告，7月12日继续参加会议分组讨论，7月13日返回武汉。
论文摘要如下：
The problem of identifying protein complexes is of great significance for studying the protein mechanisms in different cellular systems. It is for this reason that many computational approaches have been proposed to solve the problem. Yet few of them have endeavored to discover overlapping protein complexes, which are crucial to improve the accuracy performance. Hence, in this paper, we explore the feasibility of making use of a fuzzy clustering approach to identify overlapping protein complexes in a natural manner. To do so, we first formulate the identification problem as an optimization problem by following certain intuitions and then develop an algorithm to solve it so that the memberships of each protein to different protein complexes can be optimized to eventually infer the protein complexes of interest. The experimental results on several yeast protein interaction networks show that our algorithm is promising in terms of accuracy.