| Baseline model for predicting protein–ligand unbinding kinetics through machine learning N Amangeldiuly, D Karlov, MV Fedorov Journal of Chemical Information and Modeling 60 (12), 5946-5956, 2020 | 17 | 2020 |
| High performance of gradient boosting in binding affinity prediction D Gavrilev, N Amangeldiuly, S Ivanov, E Burnaev arXiv preprint arXiv:2205.07023, 2022 | 1 | 2022 |
| Engagement assessment in project-based education: a machine learning approach in team chat analysis S Farshad, E Zorin, N Amangeldiuly, C Fortin Education and Information Technologies, 1-27, 2023 | | 2023 |
| Global Trends in Carbon Fiber Research N Amangeldiuly, MV Fedorov Voprosy Materialovedeniya 97 (1), 147-163, 2019 | | 2019 |
| UTILIZATION OF SULFURIC ACID AND CAPROLACTAM PRODUCTION WASTES (SULFURIC SLUDGE AND POD OIL) FOR THE PRODUCTION OF SULFUR CONCRETE N Amangeldiuly, MF Faskhutdinov, KM Beketov, BF Rasulev, VK Yu ИЗВЕСТИЯ НАУЧНО-ТЕХНИЧЕСКОГО ОБЩЕСТВА «КАХАК» 52 (1), 37-42, 2016 | | 2016 |
| SYNTHESIS OF PROPARGYL DERIVATIVES OF SOME NATURAL AND SYNTHETIC AZAHETEROCYCLES K Askar, SM Koiyssova, KD Praliev, TM Seylhanov, N Amangeldiuly, ... ИЗВЕСТИЯ НАУЧНО-ТЕХНИЧЕСКОГО ОБЩЕСТВА «КАХАК» 48 (1), 19-24, 2015 | | 2015 |
| Improving Collaborative Design Learning: Which Feedback System is More Effective; Can Ai Take the Wheel? S Farshad, E Zorin, N Amangeldiuly, C Fortin Available at SSRN 4395314, 0 | | |
| NEWSLETTER winter 2020-21 QR Code | | |
Sabah FarshadPhD - PE在 skoltech.ru 的电子邮件经过验证
