FMLDS2026 will bring international experts in Future Machine Learning Technologies, Artificial Intelligence, Computer Vision, Machine Learning Applications in Engineering and Data Science. It will feature keynote addresses from prominent world industry and academic leaders in Machine Learning and Data Science. It will span a wide spectrum of areas within Machine Learning and Data Science research, providing a platform for established and emerging researchers as well as industry practitioners to exchange insights and innovative ideas. FMLDS2026 will host oral, poster, and virtual presentations.
FMLDS2026 will be hosted in The University of Hyogo, Japan. It is a public university located in Hyogo Prefecture. The University of Hyogo is a comprehensive university established by integrating universities with different fields of study against the background of the diverse regional characteristics of the sea and mountains. Kobe is the capital city of Hyōgo Prefecture, Japan, which is the seventh-largest city and the third-largest port city after Tokyo and Yokohama. It is located in the Kansai region, which makes up the southern side of the main island of Honshū, on the north shore of Osaka Bay. It is part of the Keihanshin metropolitan area along with Osaka and Kyoto. It is located about 35 km (22 mi) west of Osaka and 70 km (43 mi) southwest of Kyoto. The nearest International Airport is 'Kansai International Airport', Osaka, Japan.
Kobe is the most famous for its Kobe beef (which is raised in the surrounding Hyōgo Prefecture) and Arima Onsen (hot springs). Notable buildings include the Ikuta Shrine as well as the Kobe Port Tower. Nearby mountains such as Mount Rokkō and Mount Maya overlook the city. The city is recognized as a "Design City" by UNESCO. Kobe is the site of Japan's first golf course, Kobe Golf Club, established by Arthur Hesketh Groom in 1903, and Japan's first mosque, Kobe
Mosque, built in 1935. [*source- Wikipedia]
FMLDS2026 welcomes paper submissions from both academic and industry researchers across all areas of Machine Learning and Data Science. Submissions may be either a 4-6 page regular paper or a 1-page abstract. All submitted papers will undergo a rigorous review process by at least two independent referees. Accepted, registered, and presented regular papers will be published in the conference proceedings.