Matthew J. Ellis

2.8k citations
70 papers · 1.5k indexed · 1 hit paper · h-index 20

Matthew J. Ellis

65 papers receiving 1.5k citations

Hit Papers

A tutorial review of economic model predictive control me...5302014202620182022100200300400500

Peers

Matthew J. Ellis
Comparison fields: 5 of 93
  • Control and Systems Engineering 1.2k
  • Building and Construction 87
  • Automotive Engineering 62
  • Statistics, Probability and Uncertainty 37
  • Energy Engineering and Power Technology 12
Replace Helen Durand with:
Helen Durand United States
Ahmad F. Taha United States
Simone Paoletti Italy
Gilberto Reynoso-Meza Brazil
Tapio Westerlund Finland
Gang Rong China
Hubertus Tummescheit Sweden
Gabriel A. Hackebeil United States
Xianbo Wang China
Yunfei Cui China
Matthew J. Ellis relative to Helen Durand United States Helen Durand's profile →
Citations per field
00.5×
Helen Durand · 1×
Citations per year

Countries citing papers authored by Matthew J. Ellis

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Ellis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Ellis. 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 Matthew J. Ellis. The network helps show where Matthew J. Ellis may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20254
3 20242
4 20244
5 20242
6 20239
7 202214
8 202112
9 202043
10 20194
11 201917
12 201841
13 201667
14 20155
15 20159
16 201521
17 201347
18 201386
19 20133
20 201336

About Matthew J. Ellis

Matthew J. Ellis is a scholar working on Control and Systems Engineering, Building and Construction and Hardware and Architecture, having authored 70 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (44 papers), Fault Detection and Control Systems (31 papers), Process Optimization and Integration (26 papers), Building Energy and Comfort Optimization (12 papers), Control Systems and Identification (9 papers), Smart Grid Security and Resilience (7 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Smart Grid Energy Management (6 papers). The work is most often cited by research in Control and Systems Engineering (1.2k citations), Building and Construction (87 citations) and Automotive Engineering (62 citations). Matthew J. Ellis has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Panagiotis D. Christofides, Helen Durand, Jinfeng Liu, Nael H. El‐Farra, Mohsen Heidarinejad, Michael J. Wenzel, Kirk H. Drees, Ví­ctor M. Zavala, Ranjeet Kumar and Jing Zhang.

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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