Alireza Tamaddoni‐Nezhad

1.6k citations

24 papers · 491 indexed · h-index 11

Impact in

Ecological Modeling top 10%
Artificial Intelligence top 5%
- Logic, Reasoning, and Knowledge
- Machine Learning and Algorithms
- Explainable Artificial Intelligence (XAI)
- Bayesian Modeling and Causal Inference
- Semantic Web and Ontologies

Papers in ⓘ

Artificial Intelligence 12
- Logic, Reasoning, and Knowledge 4
- Machine Learning and Algorithms 3
- Adversarial Robustness in Machine Learning 3
- Evolutionary Algorithms and Applications 2
Molecular Biology 4
- Microbial Metabolic Engineering and Bioproduction 3
- Bioinformatics and Genomic Networks 3

Co-authors: Stephen Muggleton (15 shared papers)Dianhuan Lin (2 shared papers)Alan Raybould (3 shared papers)David A. Bohan (3 shared papers)Guy Woodward (2 shared papers)Corinne Vacher (1 shared paper)Alex J. Dumbrell (1 shared paper)Raphaël A. G. Chaleil (3 shared papers)
Journals: Machine Learning (7 papers)Nature Ecology & Evolution (1 paper)Trends in Ecology & Evolution (1 paper)Biochemical Society Transactions (1 paper)Journal of Molecular Biology (1 paper)
Partner nations: United Kingdom Switzerland Italy

In The Last Decade

Alireza Tamaddoni‐Nezhad

22 papers receiving 472 citations

Peers

Countries citing papers authored by Alireza Tamaddoni‐Nezhad

Since Specialization

Citations

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

Fields of papers citing papers by Alireza Tamaddoni‐Nezhad

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alireza Tamaddoni‐Nezhad. 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 Alireza Tamaddoni‐Nezhad. The network helps show where Alireza Tamaddoni‐Nezhad may publish in the future.

Co-authors

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

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Next-Generation Global Biomonitoring: Large-scale, Automated Reconstruction of Ecological Networks Trends in Ecology & Evolution ·David A. Bohan, Corinne Vacher, Alireza Tamaddoni‐Nezhad, Alan Raybould, Alex J. Dumbrell, Guy Woodward	2017	117
2	Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited Machine Learning ·Stephen Muggleton, Dianhuan Lin, Alireza Tamaddoni‐Nezhad	2015	77
3	Meta-interpretive learning: application to grammatical inference Machine Learning ·Stephen Muggleton, Dianhuan Lin, Niels Pahlavi, Alireza Tamaddoni‐Nezhad	2013	55
4	Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP Machine Learning ·Stephen Muggleton, Ute Schmid, Christina Zeller, Alireza Tamaddoni‐Nezhad, Tarek R. Besold	2018	53
5	Application of abductive ILP to learning metabolic network inhibition from temporal data Machine Learning ·Alireza Tamaddoni‐Nezhad, Raphaël A. G. Chaleil, Antonis Kakas, Stephen Muggleton	2006	42
6	Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning PLoS ONE ·David A. Bohan, Geoffrey Caron-Lormier, Stephen Muggleton, Alan Raybould, Alireza Tamaddoni‐Nezhad	2011	35
7	Ecological networks reveal resilience of agro-ecosystems to changes in farming management Nature Ecology & Evolution ·Athen Ma, Xueke Lu, Clare Gray, Alan Raybould, Alireza Tamaddoni‐Nezhad, Guy Woodward, David A. Bohan	2018	21
8	Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach Journal of Molecular Biology ·Michael J.E. Sternberg, Alireza Tamaddoni‐Nezhad, Victor I. Lesk, Emily J. Kay, Paul G. Hitchen, Adrian P. Cootes, Lieke B. van Alphen, Marc P. Lamoureux, Harold C. Jarrell, Chris Rawlings, Evelyn C. Soo, Christine M. Szymanski, Anne Dell, Brendan W. Wren, Stephen Muggleton	2012	16
9	Meta-Interpretive Learning from noisy images Machine Learning ·Stephen Muggleton, Wang-Zhou Dai, Claude Sammut, Alireza Tamaddoni‐Nezhad, Jing Wen, Zhi‐Hua Zhou	2018	16
10	QG/GA: a stochastic search for Progol Machine Learning ·Stephen Muggleton, Alireza Tamaddoni‐Nezhad	2007	12
11	The lattice structure and refinement operators for the hypothesis space bounded by a bottom clause Machine Learning ·Alireza Tamaddoni‐Nezhad, Stephen Muggleton	2009	11
12	Systems analysis of bacterial glycomes Biochemical Society Transactions ·Emily J. Kay, Victor I. Lesk, Alireza Tamaddoni‐Nezhad, Paul G. Hitchen, Anne Dell, Michael J.E. Sternberg, Stephen Muggleton, Brendan W. Wren	2010	9
13	Modeling the effects of toxins in metabolic networks IEEE Engineering in Medicine and Biology Magazine ·Alireza Tamaddoni‐Nezhad, Raphaël A. G. Chaleil, Antonis Kakas, Michael J.E. Sternberg, Jeremy K. Nicholson, Stephen Muggleton	2007	8
14	Prediction Based Decision Making for Autonomous Highway Driving 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) ·Mustafa Yıldırım, Sajjad Mozaffari, Luc McCutcheon, Mehrdad Dianati, Alireza Tamaddoni‐Nezhad, Saber Fallah	2022	4
15	Abduction and Induction for Learning Models of Inhibition in Metabolic Networks Alireza Tamaddoni‐Nezhad, Raphaël A. G. Chaleil, Antonis Kakas, Stephen Muggleton	2006	3
16	Proceedings of the 21st international conference on Inductive Logic Programming Stephen Muggleton, Alireza Tamaddoni‐Nezhad, Francesca A. Lisi	2011	2
17	Using Genetic Algorithms for learning clauses in first-order logic Genetic and Evolutionary Computation Conference ·Alireza Tamaddoni‐Nezhad, Stephen Muggleton	2001	2
18	Inductive logic programming : 21st International Conference, ILP 2011, Windsor Great Park, UK, July 31-August 3, 2011 : revised selected papers DIAL (Catholic University of Leuven) ·Stephen Muggleton, Alireza Tamaddoni‐Nezhad, Francesca A. Lisi	2012	2
19	Explainable and Trustworthy Traffic Sign Detection for Safe Autonomous Driving: An Inductive Logic Programming Approach Electronic Proceedings in Theoretical Computer Science ·Zahra Chaghazardi, Saber Fallah, Alireza Tamaddoni‐Nezhad	2023	2
20	A data-driven approach for characterising revenues of South-Asian long-haul low-cost carriers per equivalent flight capacity per block hour Journal of Air Transport Management ·Amr Soliman, John F. O’Connell, Alireza Tamaddoni‐Nezhad	2022	2

About Alireza Tamaddoni‐Nezhad

Alireza Tamaddoni‐Nezhad is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Ecology, Evolution, Behavior and Systematics and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 491 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (4 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Machine Learning and Algorithms (3 papers), Adversarial Robustness in Machine Learning (3 papers), Bioinformatics and Genomic Networks (3 papers), Evolutionary Algorithms and Applications (2 papers), Salmonella and Campylobacter epidemiology (2 papers) and Plant and animal studies (2 papers). The work is most often cited by research in Ecological Modeling (41 citations), Artificial Intelligence (245 citations), Ecology (119 citations), Computational Theory and Mathematics (55 citations) and Nature and Landscape Conservation (38 citations). Alireza Tamaddoni‐Nezhad has collaborated with scholars based in United Kingdom, Switzerland and Italy. Frequent co-authors include Stephen Muggleton, Dianhuan Lin, Alan Raybould, David A. Bohan, Guy Woodward, Corinne Vacher, Alex J. Dumbrell, Raphaël A. G. Chaleil, Antonis Kakas and Ute Schmid. Their work appears in journals such as Machine Learning, Nature Ecology & Evolution, Trends in Ecology & Evolution, Biochemical Society Transactions and Journal of Molecular Biology.

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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