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[1]大西洋中部黄鳍金枪鱼的垂直分布与有关环境因子关系.海洋与湖沼，2004，35(1)：64-68. (第1作者)；
[2]大西洋中部金枪鱼延绳钓渔场大眼金枪鱼生物学特性.水产学报，2004，28(2)：216-220.(第1作者)；
[3]大西洋中部金枪鱼延绳钓渔场黄鳍金枪鱼生物学特性.海洋与湖沼，2004，35（4）：538—542.(第1作者)；
[4]大西洋中部大眼金枪鱼的垂直分布与温度和盐度的关系.中国水产科学，2004，11（6）：561—566.(第1作者)；
[5]大西洋中部金枪鱼延绳钓渔场大眼金枪鱼（Thunnus obesus）叉长与原条鱼重、净重的关系及原条鱼重与净重的关系. 海洋与湖沼，2006，37（3）：193-197.(第1作者)；
[6]马尔代夫海域延绳钓渔场大眼金枪鱼的钓获水层、水温和盐度.水产学报，2006，30(3): 335-340.(第1作者)；
[7]马尔代夫海域金枪鱼延绳钓渔场大眼金枪鱼（Thunnus obesus）生物学特性.中国水产科学，2006，13(4)：674-678. (第1作者)；
[8]网箱养殖大黄鱼两种间距分级栅分级效果的比较. 水产学报，2006，30 (6)：765-770.(第1作者)；
[9]基于分位数回归的大西洋中部公海大眼金枪鱼栖息环境综合指数. 水产学报，2007，31(6):798-804.(第1作者)；
[10]印度洋公海温跃层与黄鳍金枪鱼和大眼金枪鱼渔获率的关系. 水产学报，2008，32(3)：369-378.(第1作者)；
[11]Environmental preferences of longlining for yellowfin tuna (Thunnus albacares) in the tropical high seas of the Indian Ocean. Fisheries Oceanography，2008，17（4）：239–253.(第1作者)（SCI）；
[12]Environmental preferences of bigeye tuna (Thunnus obesus) in the Indian Ocean: an application to a longline fishery. Environmental Biology of Fishes, 2009，85（2）:153-171.(第1作者) （SCI）；
[13]帕劳群岛附近海域延绳钓渔场大眼金枪鱼栖息环境.海洋与湖沼, 2009, 40（6）：768-776.(第1作者)；
[14]Developing an integrated habitat index for bigeye tuna (Thunnus obesus) in the Indian Ocean based on longline fisheries data. Fisheries Research, 2010, 105(2):63-74.(第1作者) （SCI）；
[15]Environmental preferences of Alopias superciliosus, and Alopias vulpinus in waters near Marshall Islands. New Zealand Journal of Marine and Freshwater Research, 2011, 45(1):119-135.(通讯作者) （SCI）；
[16]基于有限元分析的漂流延绳钓渔具作业状态数值模拟.海洋与湖沼, 2011,42(2):256-261.(第1作者)；
[17]基于最小势能原理的延绳钓渔具作业状态数值模拟.中国水产科学, 2011,18(5):1170-1178.(第1作者)；
[18]马绍尔群岛海域大青鲨栖息地综合指数.水产学报,2011,35(8):1208-1216.(第1作者)；
[19]Standardizing CPUE of yellowfin tuna (Thunnus albacares) longline fishery in the Indian Ocean using deterministic habitat based model. Journal of Oceanography, 2011,67：541-550.(第1作者) （SCI）；
[20]Develop habitat environment integration indices of bigeye tuna (Thunnus obesus ) near Palau Waters. Marine and Freshwater Research, 2012, 63:1244–1254.(通讯作者) （SCI）；
[21]吉尔伯特群岛海域大眼金枪鱼栖息环境综合指数.海洋与湖沼，2012, 43(5):954-962. (第1作者)；
[22]Modeling the hook depth of tuna longline in the Indian Ocean. Journal of Ocean University of China, 2012,11(4): 547-556.(第1作者) （SCI）；
[23]金枪鱼延绳钓钓具的最适浸泡时间. 中国水产科学,2013, 20(2):346-350.(第1作者)；
[24]基于GAM的吉尔伯特群岛海域黄鳍金枪鱼栖息地综合指数.水产学报，2013,37（8）：142-153.(第1作者)；
[25]Determining the drag coefficient of a cylinder perpendicular to water flow by numerical simulation and field measurement. Ocean Engineering, 2014,85(11):93–99.(通讯作者) （SCI）；
[26]海洋环境因子和渔具对吉尔伯特群岛海域镰状真鲨误捕率的影响.水产学报，2015,39（1）：147～159.(第1作者)；
[27]印度洋中西部大眼金枪鱼年龄与脂肪含量的关系. 海洋与湖沼, 2015,46（4）:741-747. (第1作者)；
[28]The dynamic simulation of the pelagic longline deployment. Fisheries Research, 2015, 167：280-292. (第1作者) （SCI）;
[29]库克群岛海域海洋环境因子对大眼金枪鱼渔获率的影响.水产学报, 2015,39（8）:1230-1241.(第1作者)；
[30]基于有限元分析的金枪鱼延绳钓钓钩力学性能研究.水产学报, 2015,39（11）:1742-1751.(通讯作者）；
[31]The relationship between fat content and biological parameters of bigeye tuna in the Western Central Indian Ocean. Journal of Ocean University of China, 2016, 15 (5): 853-860.(第1作者)(SCI)；
[32]环型和圆型钓钩的力学性能.水产学报, 2016,40(6）:965-975.(第1作者)；
[33]印度洋公海海域黄鳍金枪鱼鱼体脂肪含量 与生物学参数的关系.水产学报, 2017,41(9）:1407-1414.(第1作者)；
[34]Dynamic simulation of pelagic longline retrieval. Journal of Ocean University of China,2019, 18 (2): 455-466.(第1作者)(SCI)；
[35]Relationship between the spatiotemporal distribution of dominant small pelagic fishes and environmental factors in Mauritanian waters. Journal of Ocean University of China,2020, 19 (2): 393-408.(通讯作者)(SCI)；
[36]The potential vertical distribution of bigeye tuna (Thunnus obesus) and its influence on the spatial distribution of CPUEs in the tropical Atlantic Ocean. Journal of Ocean University of China, 2020, 19 (3):669-680. (通讯作者)(SCI)；
[37]金枪鱼延绳钓力学性能研究进展. 南方水产科学，2020，16(2):121-127. (第1作者)；
[38] “丢弃渔具(ALDFG)”研究进展. 水产学报, 2020,44(10）:1762-1772.(第1作者)；
[39]毛里塔尼亚海域日本鲭时空分布与海洋环境的关系.上海海洋大学学报，2020,29（6）：868-877. (第1作者)；
[40]毛里塔尼亚海域短线竹筴鱼时空分布与海洋环境的关系. 海洋渔业，2020,42（5）：533-541. (第1作者)；
[41]A comparative study on habitat models for adult bigeye tuna in the Indian Ocean based on gridded tuna longline fishery data. Fisheries Oceanography, 2021,30:584–607. (通讯作者)(SCI)；
[42]基于 ANSYS Workbench 力学仿真的金枪鱼延绳钓钓钩深度. 渔业现代化, 2021,48(4):85-94. (第1作者)；
[43]基于集成学习的大西洋热带海域黄鳍金枪鱼渔情预报. 中国水产科学, 2021 , 28(8): 1069–1078. (第1作者)；
[44]基于深度卷积嵌入式聚类（ DCEC） 的海洋环境特征提取对渔情预报模型的改进研究. 海洋学报, 2021,43(8):105-117.
[45]金枪鱼延绳钓渔获性能研究进展. 中国水产科学, 2021 , 28(7): 925–937. (第1作者)；
[46]金枪鱼延绳钓渔业中缓解海龟误捕方法研究进展. 渔业现代化, 2021, 48(3):18-27. (第1作者)；
[47]中国沿海刺网网具遗失率影响因子. 水产学报, 2021,45(11):1957−1965. (第1作者)；
[48]Numerical and experimental investigation on hydrodynamic performance of the stick-held dip net in Pacific saury fishery. Frontiers in Marine Science，2022, 9:985086. doi: 10.3389/fmars.2022.985086 (通讯作者)(SCI);
[49]大西洋热带海域长鳍金枪鱼渔场预报模型的比较. 海洋与湖沼, 2022, 53(2):496-504. (第1作者)；
[50]基于龙格库塔法的漂流延绳钓沉降过程数值模拟. 中国水产科学, 2022,29(1): 157–169. (第1作者)；
[51]毛里塔尼亚海域沙丁鱼耳石微量元素特征分析. 海洋渔业，2022,44（4）：385-395. (第1作者)；
[52]An integrated scheme for the management of drifting fish aggregating devices in tuna purse seine fisheries. Fisheries Management and Ecology, 2023, 30(1): 56– 69. (第1作者)(SCI)；
[53]Effect of different spatial resolutions on prediction accuracy of Thunnus alalunga fishing ground in waters near Cook Islands based on LSTM. Journal of Ocean University of China, in press. (通讯作者)(SCI)；
[54]基于集成学习的大西洋热带水域大眼金枪鱼渔情预报. 水产学报,在线发表.(第1作者);
[55]基于CT扫描数据的黄鳍金枪鱼鱼体三维重构. 水产学报, 在线发表.(第1作者)。
国际会议交流的主要论文
[1]Environment factors of bigeye tuna (Thunnus obesus) longlining in the tropical high seas of the Indian Ocean. IOTC-2006-WPTT-14(第1作者)；
[2]National fisheries report of China in ICCAT waters in 2005. ANN-008-06(第1作者)；
[3]National fisheries report of China in ICCAT waters in 2006. ANN-008-07(第1作者)；
[4]Modeling the hook depth of tuna longline in the tropical areas of the Indian Ocean. IOTC-2007-WPTT-13(第1作者)；
[5]The relationship between the thermocline and the catch rate of Thunnus obesus in the tropical areas of the Indian Ocean. IOTC-2007-WPTT-14(第1作者)；
[6]Integrated habitat index of bigeye tuna in the Indian Ocean based on longlining data IOTC-2008-WPTT-32(第1作者)；
[7]Standardizing CPUE of yellowfin tuna (Thunnus albacares) longline fishery using deterministic habitat based model IOTC-2010-WPTT-50 (第1作者)；
[8]Developing an integrated habitat index for yellowfin tuna (Thunnus albacares) in the Indian Ocean based on longline fisheries data IOTC-2010-WPTT-51(第1作者)；
[9]Standardizing the tuna longline CPUE of Thunnus obesus: An application of “deterministic habitat based standardization” to the data in Marshall Islands Waters.IOTC-2010-WPTT-36(通讯作者)；
[10]A comparison of methods for prediction of Integrated Habitat Index of Thunnus albacares in the Indian Ocean– general linear model and quantile regression model considerations.IOTC-2011-WPTT13-32 (第1作者)；
[11]A comparison of calculation methods of an integrated habitat index for yellowfin tuna in the Indian Ocean. IOTC-2011-WPTT13-54(通讯作者)；
[12]A comparison of catch performance between circle hooks and tuna hooks using pelagic longline gear. 2011 International circle hook symposium, Miami, USA,. 4-6, May, 2011 (第1作者)；
[13]A Comparison of fishing efficiency on bigeye tuna of two longline fishing gears based on the depth data set. The 9th Asian fisheries and aquaculture forum, Shanghai, China, 21-25, April, 2011 (第1作者)；
[14]Fishing efficiency on Thunnus obesus of two longline fishing gears, The 9th Asian fisheries and aquaculture forum, Shanghai, China, 21-25, April, 2011 (第1作者)
[15]A comparison of methods for prediction of Integrated Habitat Index of Thunnus albacares in the Indian Ocean–general linear model and quantile regression model considerations, Including Oceanography in Fisheries Stock Assessment and Management, La Jolla, USA, 11-14, Oct., 2011 (第1作者)；
[16]Developing an integrated habitat index for Blue shark (Prionace glauca) in Waters near Marshall Islands, Including Oceanography in Fisheries Stock Assessment and Management, La Jolla, USA, 11-14, Oct., 2011 (第1作者)；
[17]Optimum soak time of tuna longline gear in the Indian Ocean.IOTC-2012-WPTT14-11(通讯作者)；
[18]A comparison of two CPUE calculation methods for longline fishing. IOTC-2012-WPTT14-42(第1作者)；
[19] A comparison of two catch rate calculation methods: application to a longline tuna fishery. ICES- FAO Working Group on Fishing Technology and Fish Behaviour 2013 Mini symposium: Impacts of fishing on the environment. Bankok, Thailand, 6-10,May, 2013. (第1作者)；
[20] The length structure of bigeye tuna and yellowfin tuna catch at different depth layers and temperature ranges: an application to the longline fisheries in the waters near Gilbert Islands. Selectivity: theory, estimation, and application in fishery stock assessment models. La Jolla, US. 11-14, Mar., 2013 (第1作者)；
[21] The dynamic simulation of the pelagic longline deployment. ICES- FAO Working Group on Fishing Technology and Fish Behaviour. New Bedford, Massachusetts, USA, 5-9, May, 2014(第1作者)；
[22] An integrated habitat index for albacore tuna in waters near the Cook Islands based on the quantile regression method. Sixth International Symposium on GIS/Spatial Analysis in Fishery and Aquatic Sciences. Tampa, Florida, USA, 25-29, Aug., 2014 (第1作者)；
[23] The dynamic simulation of the pelagic longline retrieving. ICES- FAO Working Group on Fishing Technology and Fish Behaviour. Lisbon, Portugal, 4-7, May, 2015(第1作者)；
[24] Reducing bycatch of silky shark (Carcharhinus falciformis) in pelagic longlines fishing in waters near Gilbert Islands through better understanding of environmental factors and fishing gear parameters. 145 annual meeting of the American fisheries society, Portland, Oregon, USA, 16-20, Aug, 2015 (第1作者)；
[25] The relationships between muscle fat content and biological parameters in Thunnus albacares in the high seas of the Indian Ocean. Mahe, Seychelles, 4-10，Nov., 2016, (第1作者)；
[26]The tuna fisheries of mainland China —— fisheries status, challenge and strategies. ICES- FAO Working Group on Fishing Technology and Fish Behaviour Nelson, New Zealand，3-7，April, 2017(第1作者)；
[27] The relationship between the free school skipjack tuna catch rate and the environmental variables based on quantile regression. 148 annual meeting of the American fisheries society, Atlantic City, New Jersey, USA，19 – 23, Aug., 2018 (第1作者)；
[28] China's distant water fisheries – status, management and challenges. ICES- FAO Working Group on Fishing Technology and Fish Behaviour 2019， Shanghai, China, 8-12，April, 2019 (第1作者)。
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