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ORCIDJie Pan 0002
Person information
- affiliation: Springer Nature, New York City, NY, USA
- affiliation (2019 - 2020): Michigan State University, East Lansing, MI, USA
- affiliation (2016 - 2019): National Renewable Eenergy Laboratory, Golden, CO, USA
- affiliation (PhD 2016): University of Kentucky, Lexington, KY, USA
Other persons with the same name
- Jie Pan — disambiguation page
- Jie Pan 0001
![[0000-0002-5997-6396]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-5997-6396")
— University of Western Australia, School of Mechanical Engineering, Crawley, WA, Australia (and 1 more) - Jie Pan 0003 — ADVA Optical Networking, Norcross, GA, USA (and 1 more)
- Jie Pan 0004 — Hong Kong University of Science and Technology, Department of Electronic and Computer Engineering, Hong Kong (and 1 more)
- Jie Pan 0005 — Hong Kong University of Science and Technology, Department of Electronic and Computer Engineering, Hong Kong (and 1 more)
- Jie Pan 0006 — Yangzhou University, College of Information Engineering, China (and 1 more)
- Jie Pan 0007 — Northwest University, Xi'an, China (and 1 more)
- Jie Pan 0008 — Peking University, College of Engineering, Department of Advanced Manufacturing and Robotics, Beijing, China
- Jie Pan 0009 — Nanjing Forestry University, College of Forestry, Co-Innovation Center for Sustainable Forestry in Southern China, China
- Jie Pan 0010 — Shanghai Jiao Tong University, Department of Industrial Engineering and Management, China
- Jie Pan 0011 — Zhejiang University of Technology, College of Computer Science and Technology, Hangzhou, China
- Jie Pan 0012 — Sun Yat-sen University, School of Computer Science and Engineering, Guangzhou, China
- Jie Pan 0013 — Shandong Normal University, School of Physics and Electronics, Jinan, China
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2020 – today
- 2024
[j39]Jie Pan:
Materials informatics heralds a collaborative future. Nat. Comput. Sci. 4(3): 158-160 (2024)- 2023
- [j38]Jie Pan:
Large language model for molecular chemistry. Nat. Comput. Sci. 3(1): 5 (2023) - [j37]Jie Pan:
Effective phase analyzer learned from stock images. Nat. Comput. Sci. 3(2): 120 (2023) - [j36]Jie Pan:
Transfer learning for metal-organic frameworks. Nat. Comput. Sci. 3(4): 280 (2023) - [j35]Jie Pan:
Towards a welcoming climate for LGBTQ people. Nat. Comput. Sci. 3(6): 473-475 (2023) - [j34]Jie Pan:
Treating quantum states as human faces. Nat. Comput. Sci. 3(6): 479 (2023) - [j33]Jie Pan:
Physics-inspired model for online content dynamics. Nat. Comput. Sci. 3(7): 575 (2023) - [j32]Jie Pan:
Optimal crystal structure solutions. Nat. Comput. Sci. 3(8): 665 (2023) - [j31]Jie Pan:
Adding charge to neural network potentials. Nat. Comput. Sci. 3(10): 816 (2023) - [j30]Jie Pan:
A full-stack platform for spiking deep learning. Nat. Comput. Sci. 3(11): 913 (2023) - [j29]Jie Pan:
Towards programmed protein generation. Nat. Comput. Sci. 3(12): 1003 (2023) - 2022
- [j28]Jie Pan:
Mining literature for perovskite solar cells. Nat. Comput. Sci. 2(1): 3 (2022) - [j27]Jie Pan:
Reinstating functionality of complex systems. Nat. Comput. Sci. 2(2): 64 (2022) - [j26]Kaitlin McCardle, Jie Pan:
Computational chemistry for all. Nat. Comput. Sci. 2(3): 134-136 (2022) - [j25]Jie Pan:
Machine learning for spectral properties. Nat. Comput. Sci. 2(3): 139 (2022) - [j24]Jie Pan:
Quantum Monte Carlo guided by quantum computing. Nat. Comput. Sci. 2(4): 213 (2022) - [j23]Jie Pan:
Expanding the capability of autonomous microscopy. Nat. Comput. Sci. 2(5): 285 (2022) - [j22]Jie Pan:
Stabilizing quantum GANs. Nat. Comput. Sci. 2(6): 351 (2022) - [j21]Jie Pan:
Quantum experiment design via interpretable DL. Nat. Comput. Sci. 2(7): 410 (2022) - [j20]Jie Pan:
Improving segregation prediction. Nat. Comput. Sci. 2(8): 468 (2022) - [j19]Jie Pan:
Making complex systems computable. Nat. Comput. Sci. 2(9): 550-552 (2022) - [j18]Jie Pan:
Mathematically probing membrane fluctuations. Nat. Comput. Sci. 2(9): 554 (2022) - [j17]Jie Pan:
Machine learning proved efficient. Nat. Comput. Sci. 2(10): 619 (2022) - [j16]Jie Pan:
Active learning for alloy design. Nat. Comput. Sci. 2(11): 693 (2022) - 2021
- [j15]Jie Pan:
Characterizing true quantum computing power. Nat. Comput. Sci. 1(1): 15 (2021) - [j14]Jie Pan:
Modeling higher-order lattice anharmonicity. Nat. Comput. Sci. 1(1): 17 (2021) - [j13]Jie Pan:
Scaling up system size in materials simulation. Nat. Comput. Sci. 1(2): 95 (2021) - [j12]Jie Pan:
Simulating thermal physics on quantum computers. Nat. Comput. Sci. 1(3): 174 (2021) - [j11]Jie Pan:
Can machines learn with hard constraints? Nat. Comput. Sci. 1(4): 244 (2021) - [j10]Jie Pan:
Computationally probing exciton dynamics. Nat. Comput. Sci. 1(4): 246 (2021) - [j9]Jie Pan:
Large-scale transport simulation by deep learning. Nat. Comput. Sci. 1(5): 306 (2021) - [j8]Jie Pan:
Mathematically exploring wrinkle evolution. Nat. Comput. Sci. 1(6): 388 (2021) - [j7]Jie Pan:
Improving chemical accuracy with neural networks. Nat. Comput. Sci. 1(7): 453 (2021) - [j6]Jie Pan:
Simulating synthesis of 3D network polymers. Nat. Comput. Sci. 1(8): 506 (2021) - [j5]Jie Pan:
Deep learning boosts RNA prediction. Nat. Comput. Sci. 1(9): 564 (2021) - [j4]Jie Pan:
Reducing qubit budget in quantum machine learning. Nat. Comput. Sci. 1(9): 565 (2021) - [j3]Jie Pan:
Physics-educated DL refines phase mapping. Nat. Comput. Sci. 1(10): 635 (2021) - [j2]Jie Pan:
Coupling mechanics into membrane electrochemistry. Nat. Comput. Sci. 1(11): 708 (2021) - [j1]Jie Pan:
Analyzing noise for quantum advantage. Nat. Comput. Sci. 1(12): 776 (2021)
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last updated on 2024-05-19 02:44 CEST by the dblp team
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