Michał Łukasik

1.1k total citations
16 papers, 313 citations indexed

About

Michał Łukasik is a scholar working on Artificial Intelligence, Molecular Biology and Sociology and Political Science. According to data from OpenAlex, Michał Łukasik has authored 16 papers receiving a total of 313 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Molecular Biology and 4 papers in Sociology and Political Science. Recurrent topics in Michał Łukasik's work include Point processes and geometric inequalities (4 papers), Misinformation and Its Impacts (4 papers) and Diffusion and Search Dynamics (4 papers). Michał Łukasik is often cited by papers focused on Point processes and geometric inequalities (4 papers), Misinformation and Its Impacts (4 papers) and Diffusion and Search Dynamics (4 papers). Michał Łukasik collaborates with scholars based in United Kingdom, Australia and United States. Michał Łukasik's co-authors include Trevor Cohn, Kalina Bontcheva, Arkaitz Zubiaga, P. K. Srijith, Rob Procter, Maria Liakata, Duy Vu, Elena Kochkina, Isabelle Augenstein and Andreas Veit and has published in prestigious journals such as Information Processing & Management, ACM Transactions on Information Systems and Frontiers in Computational Neuroscience.

In The Last Decade

Michał Łukasik

15 papers receiving 297 citations

Peers

Countries citing papers authored by Michał Łukasik

Since Specialization

Citations

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

Fields of papers citing papers by Michał Łukasik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michał Łukasik

This figure shows the co-authorship network connecting the top 25 collaborators of Michał Łukasik. A scholar is included among the top collaborators of Michał Łukasik based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michał Łukasik. Michał Łukasik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

#	Work	Indexed citations
1	Regression Aware Inference with LLMs 2024 ·Michał Łukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar	0
2	Large Language Models with Controllable Working Memory 2023 ·Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michał Łukasik, Andreas Veit, Felix Yu, Sanjiv Kumar	22
3	Hawkes Process Classification through Discriminative Modeling of Text 2022 ·2022 International Joint Conference on Neural Networks (IJCNN) ·(unknown), (unknown), P. K. Srijith, Michał Łukasik	2
4	Gaussian Processes for Rumour Stance Classification in Social Media 2019 ·ACM Transactions on Information Systems ·Michał Łukasik, Kalina Bontcheva, Trevor Cohn, Arkaitz Zubiaga, Maria Liakata, Rob Procter	27
5	A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems 2018 ·Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad) ·(unknown), P. K. Srijith, Michał Łukasik	2
6	Longitudinal Modeling of Social Media with Hawkes Process Based on Users and Networks 2017 ·P. K. Srijith, Michał Łukasik, Kalina Bontcheva, Trevor Cohn	5
7	Discourse-aware rumour stance classification in social media using sequential classifiers 2017 ·Information Processing & Management ·Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michał Łukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein	94
8	Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis 2016 ·Frontiers in Computational Neuroscience ·(unknown), (unknown), (unknown), Michał Łukasik, (unknown), Dariusz Plewczyński	12
9	Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter 2016 ·Michał Łukasik, P. K. Srijith, Duy Vu, Kalina Bontcheva, Arkaitz Zubiaga, Trevor Cohn	87
10	PHEME D4.3.2: Algorithms for Detecting Misinformation and Disinformation: Final Version 2016 ·Ahmet Aker, Michał Łukasik, Arkaitz Zubiaga, Kalina Bontcheva, Trevor Cohn	1
11	Convolution Kernels for Discriminative Learning from Streaming Text 2016 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Michał Łukasik, Trevor Cohn	3
12	Metrics for Evaluation of Word-level Machine Translation Quality Estimation 2016 ·Varvara Logacheva, Michał Łukasik, Lucia Specia	3
13	Modeling Tweet Arrival Times using Log-Gaussian Cox Processes 2015 ·Michał Łukasik, P. K. Srijith, Trevor Cohn, Kalina Bontcheva	13
14	Point Process Modelling of Rumour Dynamics in Social Media 2015 ·Michał Łukasik, Trevor Cohn, Kalina Bontcheva	19
15	PHEME : computing veracity : the fourth challenge of big social data 2014 ·Warwick Research Archive Portal (University of Warwick) ·Leon Derczynski, Kalina Bontcheva, Michał Łukasik, Thierry Declerck, Arno Scharl, Georgi Georgiev, Petya Osenova, (unknown), (unknown), R.W. Stewart, (unknown), Geraldine Wong, Christian Bürger, Arkaitz Zubiaga, Rob Procter, Maria Liakata	21
16	Evaluation of Features for Author Name Disambiguation Using Linear Support Vector Machines 2012 ·CeON Repository (Centre for Evaluation in Education and Science) ·(unknown), Łukasz Bolikowski, Michał Łukasik	2

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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