Carl Poelking

Carl Poelking

University of Cambridge

H-index: 16

Europe-United Kingdom

About Carl Poelking

Carl Poelking, With an exceptional h-index of 16 and a recent h-index of 16 (since 2020), a distinguished researcher at University of Cambridge, specializes in the field of Computational Physics.

His recent articles reflect a diverse array of research interests and contributions to the field:

CESPED: a new benchmark for supervised particle pose estimation in Cryo-EM

Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions

A multilevel generative framework with hierarchical self-contrasting for bias control and transparency in structure-based ligand design

Open-circuit voltage of organic solar cells: interfacial roughness makes the difference

3D pride without 2D prejudice: Bias-controlled multi-level generative models for structure-based ligand design

Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns

BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale

Chemical Design Rules for Non‐Fullerene Acceptors in Organic Solar Cells (Adv. Energy Mater. 44/2021)

Carl Poelking Information

University

Position

___

Citations(all)

2366

Citations(since 2020)

1576

Cited By

1500

hIndex(all)

16

hIndex(since 2020)

16

i10Index(all)

17

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Carl Poelking Skills & Research Interests

Computational Physics

Top articles of Carl Poelking

CESPED: a new benchmark for supervised particle pose estimation in Cryo-EM

arXiv preprint arXiv:2311.06194

2023/11/10

Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions

arXiv preprint arXiv:2308.09086

2023/8/17

Lucian Chan
Lucian Chan

H-Index: 3

Carl Poelking
Carl Poelking

H-Index: 15

A multilevel generative framework with hierarchical self-contrasting for bias control and transparency in structure-based ligand design

Nature Machine Intelligence

2022/12

Open-circuit voltage of organic solar cells: interfacial roughness makes the difference

Communications Physics

2022/11/29

3D pride without 2D prejudice: Bias-controlled multi-level generative models for structure-based ligand design

arXiv preprint arXiv:2204.10663

2022/4/22

Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns

arXiv preprint arXiv:2204.06348

2022/3/25

BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale

Machine Learning: Science and Technology

2022/1/19

Carl Poelking
Carl Poelking

H-Index: 15

Chemical Design Rules for Non‐Fullerene Acceptors in Organic Solar Cells (Adv. Energy Mater. 44/2021)

Advanced Energy Materials

2021/11

Investigating 3D Atomic Environments for Enhanced QSAR

arXiv preprint arXiv:2010.12857

2020/10/24

William Mccorkindale
William Mccorkindale

H-Index: 2

Carl Poelking
Carl Poelking

H-Index: 15

See List of Professors in Carl Poelking University(University of Cambridge)