Graduate Program of Global Environmental Studies (GENV)
genv-co[at]sophia.ac.jp
+81-3-3238-4368
Address:
Room 1520 Bldg No.2, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554 Japan
Our laboratory applies remote sensing data, machine learning, and deep learning to clarify how local and global environments, as well as human health, are affected by natural alterations caused by human development.
Environmental Data Science, Fundamentals and Applications of Deep Learning
I did an internship at World Health Organization while studying at New York Medical College, and earned a master’s degree in Public Health. I was engaged in public health research at National Institute for Environmental Studies and NASA Ames Research Center, CHAART while studying at Kobe University, and received a doctoral degree of medical science. I had worked as a full-time lecturer and an associate professor at Shibaura Institute of Technology before I became a professor here at Sophia University.
I specialize in environmental health and spatial information science. Anno Laboratory is committed to making a contribution to research aimed at solving problems in environmental hygiene/health by applying remote sensing and machine/deep learning.
The framework of my study is comprised of a mixture of environmental hygiene/health, spatial information science, and earth science with a common vision: to solve real problems in environmental hygiene/health by using remote sensing and machine/deep learning.
Hold a seminar once a week. This seminar provides students with the academic, communication, and critical thinking skills needed to conduct research in the field of environmental hygiene/health. Students will be required to read research articles and prepare for the discussion on the reading. Also, students will learn the principle and applications of remote sensing and machine/deep learning.
Students will acquire the knowledge and skills, such as environmental hygiene/health, analysis of remote sensing data, machine/deep learning useful for any sort of work.
2016年『Gene-Environment Interaction Analysis – Methods in Bioinformatics and Computational Biology』Pan Stanford Publishing.（監修・共著）
2016 Gene-Environment Interaction Analysis – Methods in Bioinformatics and Computational Biology, Pan Stanford Publishing, (Editor, Coauthor)
2012年・2010年『生理人類士入門』（株）国際文献印刷社（共著）
2009年『カラダの百科事典』丸善株式会社（共著）
2009年『Computational Biology: New Research』 Nova Science Publishers, Inc.（共著）2005年『人間を科学する事典』東京堂出版（共著）
2009 Computational Biology: New Research, Nova Science Publishers, Inc., (Coauthor)
2004 Management Information Systems 2004: Incorporating GIS and Remote Sensing, WIT Press, (Coauthor), and others.
1998年『21世紀・健康・世界 WHO編纂・世界保健報告』英伝社（翻訳分担）
1995年『協同組合と農民組織 –タイ・インド・日本–』筑波書房（共著・翻訳）他
Sumiko Anno, Hirakawa Tsubasa, Satoru Sugita, Shinya Yasumoto, Ming-An Lee, Yoshinobu Sasaki, Kei Oyoshi, Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning, Geo-spatial Information Science, DOI : 10.1080/10095020.2022.2144770. 2023.(査読有/Reviewed)
Awah Rita Engwari, Sumiko Anno, Ako Andrew, Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon, The 37th Congress of Japan Association for International Health, Proceedings, Pp. 92, 2022.(査読有/Reviewed)
Sumiko Anno, Tsubasa Hirakawa, Satoru Sugita, Shinya Yasumoto, A Graph Convolutional Network for Predicting COVID-19 Dynamics in 190 Regions/Countries, Frontiers in Public Health, 10: 911336. 2022.(査読有/Reviewed)
Sumiko Anno, Takeshi Hara, Hiroki Kai, Yi Chang, Ming-An Lee, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning, Geospatial Health, Vol. 14, No. 771, Pp. 183- 194, 2019.(査読有/Reviewed)
安納住子，山崎和博，改井洋樹，張懿，李明安，大吉慶，水上陽誠，田殿武雄，人工衛星データ×人工知能を応用したデング熱発生予測について，第30回日本医学会総会 2019 中部，学術講演要旨，Pp. 129，2019.(査読無)
Sumiko Anno, Takeshi Hara, Hiroki Kai, Yi Chang, Ming-An Lee, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Prediction of dengue fever outbreaks from satellite remote sensing data using deep learning, Asia Conference on Machine Learning and Computing, Proceedings, Pp. 22, 2018.(査読有/Reviewed)
関晃伸，安納住子，開発・参加型GIS教育における性格別による学習上のつまずきの特徴の解明，土木学会論文集H(教育)，Vol. 73，No. 1．Pp. 12-21, 2017.(査読有/Reviewed)
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Space–time clustering characteristics of dengue based on ecological, socio-economic, and demographic factors in northern Sri Lanka, Geospatial Health, Vol. 10, No. 376, Pp. 215-222, 2015. (査読有/Reviewed)
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Assessing the Temporal and Spatial Dynamics of the Dengue Epidemic in Northern Sri Lanka using Remote Sensing Data, GIS and Statistical Analysis, Journal of Geophysics & Remote Sensing, Vol. 3, No. 4，Pp. 1-5，2014.(査読有/Reviewed)
安納住子，大島一彦，阿部貴志，田殿武雄，山本彩，五十嵐保，遺伝子工学・リモートセンシング・地理情報システムの技術を応用したヒトの環境適応能における遺伝－環境の相互作用解明への新研究法，日本生理人類学会誌, Vol. 19, No. 1，Pp. 13-18，2014. (査読有/Reviewed)
Sumiko Anno, Kazuhiko Ohshima, Takashi Abe, Takeo Tadono, Aya Yamamoto, Tamotsu Igarashi, Approaches to Detecting Gene-Environment Interactions in Human Variation Using Genetic Engineering, Remote Sensing and GIS, Journal of Earth Science and Engineering, Vol. 3, No. 6, Pp. 371-378, 2013.(査読有/Reviewed)
Raimondi S, Gandini S, Fargnoli MC, Bagnardi V, Maisonneuve P, Specchia C, Kumar R, Nagore E, Han J, Hansson J, Kanetsky PA, Ghiorzo P, Gruis NA, Dwyer T, Blizzard L, Fernandez-de-Misa R, Branicki W, Debniak T, Morling N, Landi MT, Palmieri G, Ribas G, Stratigos A, Cornelius L, Motokawa T, Anno S, Helsing P, Wong TH, Autier P, García-Borrón JC, Little J, Newton-Bishop J, Sera F, Liu F, Kayser M, Nijsten T, Study Group G., Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project: study design and methods for pooling results of genetic epidemiological studies, BMC Medical Research Methodology, 12(1), Pp. 1-16. 2012.(査読有/Reviewed)
安納住子，大島一彦，阿部貴志，SNP解析によって明らかにされたハプロタイプ構造に基づくヒト皮膚色候補遺伝子の自然選択検出の可能性，日本生理人類学会誌, Vol. 16, No. 2，Pp. 99-102，2011. (査読有/Reviewed)
Sumiko Anno, Kazuhiko Ohshima, and Takashi Abe, Approaches to understanding adaptations of skin color variation by detecting gene-environment interactions, Expert Review of Molecular Diagnostics, Vol. 10, No. 8, Pp. 987-991, 2010.(査読有/Reviewed)
S. Kannathasan, A. Antonyrajan, N.D. Karunaweera, S. Anno, S.N. Surendran, Identification of potential malaria risk areas of the Jaffna district of northern Sri Lanka: A GIS approach, Journal of the National Science Foundation of Sri Lanka, Vol. 37, No. 3, Pp. 223-225, 2009. (査読有/Reviewed)
Sumiko Anno, Takashi Abe, Takushi Yamamoto, Interactions between SNP Alleles at Multiple Loci Contribute to Skin Color Differences between Caucasoid and Mongoloid Subjects, International Journal of Biological Sciences, Vol. 4, No. 2, Pp. 81-86, 2008.(査読有/Reviewed)
安納住子，阿部貴志，山本卓志，コーカソイドおよびモンゴロイドの皮膚色の違いに関与する多遺伝子座のSNP 対立遺伝子の組み合わせについて，日本生理人類学会誌，Vol. 13, No. 1，Pp. 1-7，2008. (査読有/Reviewed)
Sumiko Anno, Takashi Abe, Koichi Sairyo, Susumu Kudo, Takushi Yamamoto，Koretsugu Ogata, and Vijay K. Goel, Interactions between SNP Alleles at Multiple Loci Contribute to Variation in Skin Pigmentation in 122 Caucasians, Evolutionary Bioinformatics, Vol.3, Pp. 169–178, 2007.(査読有/Reviewed)
安納住子，阿部貴志，西良浩一，工藤奨，山本卓志，緒方是嗣，Vijay K. Goel，多遺伝子座におけるSNP対立遺伝子の相互作用が及ぼすヒトの皮膚色の多様性について，日本生理人類学会誌, Vol. 12, No. 1，Pp. 1-10，2007. (査読有/Reviewed), 他/and others.
Awah Rita, Sumiko Anno, Ako Andrew, Assessing access to water, sanitation, and hygiene services associated with infectious diseases in the Douala 4th district in Cameroon, The 37th Congress of Japan Association for International Health 2022年11月19日
安納住子, 平川翼, 安本晋也, 杉田暁, AST-GCNモデル・ビッグデータを用いた新型コロナウィルス感染症流行予測, 問題複合体を対象とするデジタルアース共同利用・共同研究拠点 2021年度成果報告会 2022年3月
Sumiko Anno, Tsubasa Hirakawa, Shinya Yasumoto, Satoru Sugita, Ming-An Lee, Yoshinobu Sasaki, Kei Oyoshi, Development of model for temporal and spatial distribution prediction of the dengue fever by deep learning, The Joint PI Meeting of JAXA Earth Observation Missions FY2021 2022年1月
Sumiko Anno, Tsubasa Hirakawa, Shinya Yasumoto, Satoru Sugita, Deep learning for forecasting the COVID-19 cases, The 62nd Annual Meeting for the Japanese Society of Tropical Medicine 2021年11月
安納住子, 平川翼, 安本晋也, 杉田暁, 李明安, 佐々木善信, 大吉慶,深層学習 ・ビッグデータを用いた人獣共通感染症パンデミックの要因解明および時空間分布予測, 問題複合体を対象とするデジタルアース共同利用・共同研究拠点 2020年度成果報告会 2021年2月
Sumiko Anno, Takehiro Maeda, Takeshi Hara, Kazuhiro Yamasaki, Ming-An Lee, Yosei Mizukami, Yoshinobu Sasaki, Kei Oyoshi, Comparison of deep learning models in predicting time points of dengue fever outbreak, The Virtual Edition of the 6th World One Health Congress 2020年11月1日
Sumiko Anno, Takehiro Maeda, Takeshi Hara, Kazuhiro Yamasaki, Ming-An Lee, Yosei Mizukami, Yoshinobu Sasaki, Kei Oyoshi, Development of models for predicting time points of dengue fever outbreak using remote sensing data and deep learning, The Joint PI Meeting of JAXA Earth Observation Missions FY2019, Poster Session 2020年1月20日
安納住子, ACEを通じた連携構築の経験談, 日本・アフリカ大学連携フォーラム (世界銀行東京事務所) 2019年9月3日
Sumiko Anno, Kazuhiro Yamasaki, Ming-An Lee, Yi Chang, Hiroki Kai, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Predicting Spatiotemporal Distribution of Dengue Fever in Taiwan Using Deep Learning, The 32nd International Symposium on Space Technology and Science (ISTS) & the 9th Nano-Satellite Symposium (NSAT) 2019年6月15日
安納住子，山崎和博，改井洋樹，張懿，李明安，大吉慶，水上陽誠，田殿武雄，人工衛星データ×人工知能を応用したデング熱発生予測について，第30回日本医学会総会 2019 中部，愛知県名古屋市，2019．（招待講演・市民公開講座/Invitation lecture）
Sumiko Anno, Kazuhiro Yamasaki, Hiroki Kai, Yi Chang, Ming-An Lee, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Predicting the spatiotemporal distribution of dengue fever outbreaks in Taiwan using deep learning techniques and remote sensing data, The Joint PI Meeting of JAXA Earth Observation Missions FY2018, Tokyo, Japan, January 21-25, 2019.
吉里光喜，安納住子，Twitterのつぶやきデータおよび機械学習による地震予測の可能性について，日本地震予知学会 第5回学術講演会，東京都港区，2018．
Sumiko Anno, Takeshi Hara, Hiroki Kai, Yi Chang, Ming-An Lee, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Deep learning applications for predicting dengue fever outbreak, EuroSciCon Conference on Environmental Science & Technology, Vienna, Austria, March 29-31, 2018.
吉里光喜，安納住子，CGMによる地震予知の検証，第26回生研フォーラム「宇宙からの地球環境・災害のモニタリングとリスク評価」，東京都目黒区，2018．
Sumiko Anno, Takeshi Hara, Hiroki Kai, Yi Chang, Ming-An Lee, Kei Oyoshi, Yosei Mizukami, Takeo Tadono, Predicting dengue fever outbreaks in Taiwan using deep learning techniques and remote sensing data, The Joint PI Meeting of Global Environment Observation Mission FY2017, Tokyo, Japan, January 22-25, 2018.
池田琢人，吉里光喜，安納住子，地震予知に関するCGM 利用の可能性および信頼性の検証，CSIS DAYS 2017「全国共同利用研究発表大会」，千葉県柏市，2017.
Sumiko Anno, Ming-An Lee, Kuan-Tsung Chang, Yi Chang, Takeo Tadono, Kei Oyoshi, Hiroki Kai, Yusuke Kobayashi, and Tamotsu Igarashi, Hot spot detection and spatiotemporal dispersion of dengue fever in Taiwan associated with meteorological, environmental and demographic factors, 2016 International Conference on Earth Observations and Societal Impacts, Yilan, Taiwan, June 25-27, 2017.
Sumiko Anno, Ming-An Lee, Kuan-Tsung Chang, Yi Chang, Takeo Tadono, Kei Oyoshi, Hiroki Kai, Yusuke Kobayashi, and Tamotsu Igarashi, A Comprehensive Study of Dengue Fever Outbreaks in Taiwan Using Remote Sensing, Unmanned Aerial Vehicles, Big Data, and Open Data, The 31st International Symposium on Space Technology and Science (ISTS), Matsuyama, Ehime, June 3-9, 2017.
Sumiko Anno, Takeo Tadono, Tamotsu Igarashi, Yusuke Kobayashi, Naoki Kobayashi, Ming-An Lee, Framework for the application of remote sensing, unmanned aircraft systems, geographic information systems, cloud computing, and a social networking service to early dengue fever intervention and heat stroke control measures, 2016 International Conference on Earth Observations and Societal Impacts, Keelung, Taiwan, June 26-28, 2016.
Takeo Tadono, Sumiko Anno, Ming-An Lee, Yusuke Kobayashi, Tamotsu Igarashi, Earth observation toward applications of the public health: A case study for dengue in southern Taiwan, 2016 International Conference on Earth Observations and Societal Impacts, Keelung, Taiwan, June 26-28, 2016.
関晃伸，安納住子，開発・参加型GIS教育におけるパーソナリティ別の学習上のつまずきについて，土木学会第43回関東支部技術研究発表会，東京都世田谷区，2016.
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Remote Sensing Applied for a Study of Space Time Geographical Pathology for the Relationships Between Dengue Endemic in Northern Sri Lanka and Ecological, Socio-Economic and Demographic Factors, The 2nd PI Workshop for ALOS-2, Chiyoda-ku, Tokyo, November 18-20, 2015.
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Spatial-Temporal Epidemiology of the Dengue Outbreak in the Northern Region of Sri Lanka, 2010-2013, The 30th International Symposium on Space Technology and Science (ISTS), the 34th International Electric Propulsion Conference (IEPC) & the 6th Nano-Satellite Symposium (NSAT), Kobe, Hyogo, July 4-10, 2015.
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Retrospective space-time cluster analysis of dengue in the northern region of Sri Lanka: remote sensing and GIS based case study, 2015 ICEO&SI and ICLEI Resilience Forum, Kaohsiung, Taiwan, June 28-30, 2015.(基調・招待講演/Invitation lecture)
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Spatial-Temporal Clustering Characteristics of Dengue in the Northern Region of Sri Lanka, 2010-2013, The ICGIS 2015: 17th International Conference on Geographic Information Systems, Paris, France, May 18-19, 2015.
関晃伸，中川雅史，安納住子，GIS教育における学習のつまずきの特徴および原因解明に関する研究，土木学会関東支部第42回技術研究発表会，神奈川県平塚市，2015．
関晃伸，安納住子，参加型GIS教育の有効性について，第23回生研フォーラム「宇宙からの地球環境・災害のモニタリングとリスク評価」，東京都目黒区，2015．
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran, Characterization of the Temporal and Spatial Dynamics of the Dengue Epidemic in Northern Sri Lanka, ISPRS Technical Commission VIII Symposium, Hyderabad, India, December 9–12, 2014.
Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran Remote Sensing Applied to the Analysis of Spatial and Temporal Pattern of Dengue Incidence Based on Ecological and Socio-Economic and Demographic Factors in Sri Lanka, The 12th Pan Ocean Remote Sensing Conference, Bali, Indonesia, November 4-7, 2014, 他/and others.
