Daniel Lo

1.5k citations
13 papers · 811 indexed · 2 hit papers · h-index 7

Daniel Lo

13 papers receiving 792 citations

Hit Papers

A Configurable Cloud-Scale DNN Processor for Real-Time AI3632016202620192022100200300

Peers

Daniel Lo
Comparison fields: 5 of 47
  • Hardware and Architecture 426
  • Computer Networks and Communications 378
  • Computer Vision and Pattern Recognition 197
  • Artificial Intelligence 228
  • Information Systems 153
Replace Stephen Heil with:
Stephen Heil United Kingdom
Todd Massengill United Kingdom
Lifeng Nai United States
Sitaram Lanka United States
Tae Jun Ham South Korea
Yuze Chi United States
Omer Khan United States
Jae W. Lee South Korea
Emmanuel Amaro United States
Mehrzad Samadi United States
Daniel Lo relative to Stephen Heil United Kingdom Stephen Heil's profile →
Citations per field
00.5×1.5×
Stephen Heil · 1×
Citations per year

Countries citing papers authored by Daniel Lo

Since Specialization
Citations

This map shows the geographic impact of Daniel Lo'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 Lo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Lo more than expected).

Fields of papers citing papers by Daniel Lo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Lo. 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 Lo. The network helps show where Daniel Lo may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Daniel Lo, 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 Lo Line = papers co-authored together Daniel Lo links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20241
2 20233
3 20199
4
A Configurable Cloud-Scale DNN Processor for Real-Time AIbreakdown →
2018363
5 20176
6 201721
7
A cloud-scale acceleration architecturebreakdown →
2016315
8 20165
9 20155
10 201519
11 20149
12 20123
13 201052

About Daniel Lo

Daniel Lo is a scholar working on Hardware and Architecture, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Electrical and Electronic Engineering, having authored 13 papers that have together received 811 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Interconnection Networks and Systems (4 papers), Embedded Systems Design Techniques (4 papers), Real-Time Systems Scheduling (3 papers), Cloud Computing and Resource Management (2 papers), Advanced Memory and Neural Computing (2 papers), Radiation Effects in Electronics (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Hardware and Architecture (426 citations), Computer Networks and Communications (378 citations), Computer Vision and Pattern Recognition (197 citations), Artificial Intelligence (228 citations) and Information Systems (153 citations). Daniel Lo has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Michael Papamichael, Todd Massengill, Adrian M. Caulfield, Eric S. Chung, Doug Burger, Jeremy Fowers, Stephen Heil, Sitaram Lanka, Kalin Ovtcharov and Michael Haselman. Their work appears in journals such as IEEE Micro, Proceedings of the ACM on Programming Languages and eCommons (Cornell University).

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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