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2021 Parlar Research Incentive Award : Hulusi Kafalıgönül

Parlar foundation gives Honorary, Science, Service, Research and Technology Incentive Awards every year in order to evaluate the research studies and services carried out in science and industry and to encourage the growing generations. Hulusi Kafalıgönül, faculty member at UMRAM, has received 2021 Parlar Research Incentive Award. Dr.Kafalıgönül’s research group at Bilkent University carries out […]

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PhD Graduation: Emin Çelik

Emin Çelik has presented his PhD thesis titled ”Spatially Informed Voxelwise Modeling and Dynamic Scene Category Representation in the Human Brain” on December 15, 2021.   ABSTRACT Humans have an impressive ability to rapidly process global information in natural scenes to infer their category. Yet, it remains unclear whether and how scene categories observed dynamically […]

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Tolga Çukur Receives TÜSEB Aziz Sancar Incentive Award

Assoc. Prof. Tolga Çukur of the Department of Electrical and Electronics Engineering and UMRAM has received an award from TÜSEB (the Health Institutes of Turkey). Named after Nobel laureate Aziz Sancar, the TÜSEB awards honor outstanding work by the country’s researchers in fields related to the health sciences. Dr. Çukur is the recipient of a […]

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Semantic Change Detection with Gaussian Word Embeddings

To tackle the problem of lexical semantic change, KocLab has developed the first Gaussian word embedding (w2g)-based approach, which has been described in the paper “Semantic Change Detection with Gaussian Word Embeddings” published at IEEE Transactions on Audio, Speech and Language Processing. The proposed method reached high rankings (including the first rank at one of […]

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Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance

The work of Dr. Koç and his collaborators on sentiment analysis has been published in IEEE Transactions on Neural Networks and Learning Systems. The paper entitled “Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance” proposes a novel method to overcome the inherent label imbalance problem in multi-label classification by balancing losses […]

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