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6¿ù 27ÀÏ ¸ñ¿äÀÏ
13:00 - 13:30µî·Ï ¹× Çà»çÀå ¾È³»±è¿ëÁÖ (°í·Á´ë)
13:30 - 13:40°³È¸»ç±Ç¿ë¿ì (È«ÀÍ´ë)
Session 1: General materials design using AIÁÂÀå: TBA
13:40 - 14:10AI È°¿ë OLED ¼³°è¹æÇâ - Àç·á & ¼ÒÀÚ¾çÁßȯ (LGµð½ºÇ÷¹ÀÌ)
14:10 - 14:40GNN-based modeling for novel catalyst developments±èµ¿ÈÆ (KIST)
14:40 - 15:10ÅëÇÕÀü»êÀç·á°øÇаú ÀΰøÁö´ÉÀ» È°¿ëÇÑ °í¼º´É ³»Áø³»È­°­ ¼³°è±è°æ´ö (POSTECH)
15:10 - 15:40±â°èÇнÀÀ» È°¿ëÇÑ ¼ÒÀç °áÁ¤±¸Á¶ ¿¹Ãø°­¼º¿ì (KIST)
15:40 - 16:00Coffee Break¡¡
Session 2: Materials design using generative and large language modelÁÂÀå: TBA
16:00 - 16:30
Inverse design of molecule: Generative Chemical Transformer
to reinforcement learning-guided combinatorial chemistry
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16:30 - 17:00»ý¼ºÇü ÀΰøÁö´ÉÀ» È°¿ëÇÑ À¯¹«±â ¼ÒÀç¼³°è³ëÁÖȯ (KRICT)
17:00 - 17:30Inverse Design of MOFs: From ChatGPT to Quantum Computing±èÁöÇÑ (KAIST)
17:30 - 18:00
One-Shot Heterogeneous Transfer Learning from Calculated Crystal
Structures to Experimentally Observed Materials
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18:00 - 20:00Dinner ¡¡
6¿ù 28ÀÏ ±Ý¿äÀÏ
Session 3: AI based catalyst designÁÂÀå: TBA
10:30 - 11:00
Efficient data sampling for surrogate models of active sites and
potential energy surfaces in catalysts design (Zoom)
ÀüÈ£Á¦ (MIT)
11:00 - 11:30
Optimization of reaction parameters of a methane conversion using
machine learning
±èÇö¿ì (GIST)
11:30 - 13:00Lunch Break¡¡
Session 4: Active learning based materials design and machine learning potentialÁÂÀå: TBA
13:00 - 13:30´Éµ¿ÇнÀ ±â¹Ý ±â°èÇнÀ Æ÷ÅÙ¼È °³¹ß ¹× È°¿ëÀÌ»ó¿í (¼º±Õ°ü´ë)
13:30 - 14:00
Searching for EUV-sensitive organic molecules with pre-trained
graph neural networks and Bayesian active learning
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14:00 - 14:30
Bayesian approaches for uncertainty quantification of deep learning
machine learning potential 
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14:30 - 16:00Á¾ÇÕ ÅäÀÇ, »çÁøÃÔ¿µ ¹× Æóȸ»ç¡¡
6¿ù 29ÀÏ Åä¿äÀÏ
10:00 - 12:00Àü»êÀç·á°úÇкаú °Ü¿ï ½ÉÆ÷Áö¾ö ÀÏÁ¤ ¹× ÅäÀÇ¡¡

 

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¹®ÀÇ : ±è¿ëÁÖ ±³¼ö (°í·Á´ëÇб³ ½Å¼ÒÀç°øÇкÎ) : cjyjee@korea.ac.kr

        °­ÁØÈñ ±³¼ö (ºÎ»ê´ëÇб³ ³ª³ë¿¡³ÊÁö°øÇаú) : j.kang@pusan.ac.kr

µî·Ï¹®ÀÇ : ¾ç¼¼Àº ´ë¸® (´ëÇѱݼӷÀç·áÇÐȸ) : kimhak@kim.or.kr

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À§¿øÀå : ±Ç¿ë¿ì ±³¼ö

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