Daniel Lam

866 citations
17 papers · 714 indexed · 1 hit paper · h-index 9

Daniel Lam

17 papers receiving 694 citations

Hit Papers

Pseudomonas Genome Database: improved comparative analysi...5102010202620152020100200300400500

Peers

Daniel Lam
Comparison fields: 5 of 82
  • Molecular Medicine 155
  • Endocrinology 77
  • Genetics 214
  • Molecular Biology 392
  • Microbiology 29
Replace Satya Prathyusha Bhamidimarri with:
Satya Prathyusha Bhamidimarri Germany
Derek B. Gordon United Kingdom
Akanksha Rajput India
Emma J. Hayhurst United Kingdom
Rashmi Gupta United States
R. González Argentina
Catherine E. Petersen United States
Jehangir Cama United Kingdom
Gilles Phan France
T. Sawai Japan
Daniel Lam relative to Satya Prathyusha Bhamidimarri Germany Satya Prathyusha Bhamidimarri's profile →
Citations per field
00.5×4.1×
Satya Prathyusha Bhamidimarri · 1×
Citations per year

Countries citing papers authored by Daniel Lam

Since Specialization
Citations

This map shows the geographic impact of Daniel Lam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Lam more than expected).

Fields of papers citing papers by Daniel Lam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Lam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Lam. The network helps show where Daniel Lam may publish in the future.

Co-authorship network

The 21 scholars most cited alongside Daniel Lam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Lam Line = papers co-authored together Daniel Lam links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20222
2 201912
3 20171
4 201517
5 20144
6 201351
7 20124
8
Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomesbreakdown →
2010510
9 198710
10 19877
11 19864
12 19867
13 19858
14 19849
15 198411
16 198424
17 198433

About Daniel Lam

Daniel Lam is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Hardware and Architecture, Condensed Matter Physics and Aerospace Engineering, having authored 17 papers that have together received 714 indexed citations. Recurring topics across this work include Photonic and Optical Devices (9 papers), Semiconductor Quantum Structures and Devices (4 papers), Semiconductor Lasers and Optical Devices (4 papers), Optical Network Technologies (4 papers), Radio Frequency Integrated Circuit Design (3 papers), Advanced Photonic Communication Systems (3 papers), Terahertz technology and applications (2 papers) and Photorefractive and Nonlinear Optics (1 paper). The work is most often cited by research in Molecular Medicine (155 citations), Endocrinology (77 citations), Genetics (214 citations), Molecular Biology (392 citations) and Microbiology (29 citations). Daniel Lam has collaborated with scholars based in Canada, United States and Denmark. Frequent co-authors include Geoffrey L. Winsor, Robert E. W. Hancock, Louise Fleming, Matthew D. Whiteside, Fiona S. L. Brinkman, Nancy Yu, R Y Lo, R.I. MacDonald, Bahram Jalali and Brandon Buckley. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Electron Devices, IEEE Electron Device Letters, Applied Physics Letters and Optics Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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