Tim Oates

7.4k citations

157 papers · 4.0k indexed · 2 hit papers · h-index 27

Impact in

Signal Processing top 0.5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Data Management and Algorithms
Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
- Topic Modeling

Papers in ⓘ

Artificial Intelligence 105
- Natural Language Processing Techniques 19
- AI-based Problem Solving and Planning 17
- Reinforcement Learning in Robotics 16
- Advanced Text Analysis Techniques 14
- Anomaly Detection Techniques and Applications 14
- Topic Modeling 13
Signal Processing 36
- Time Series Analysis and Forecasting 28
- Music and Audio Processing 12

Co-authors: Zhiguang Wang (7 shared papers)Weizhong Yan (1 shared paper)David Jensen (6 shared papers)Paul R. Cohen (19 shared papers)Foster Provost (1 shared paper)Tim Finin (10 shared papers)Pranam Kolari (4 shared papers)Rebecca Gregory (1 shared paper)
Journals: AI Magazine (3 papers)The Journal of the Acoustical Society of America (2 papers)The Curriculum Journal (1 paper)Solar Physics (1 paper)IEEE Transactions on Circuits & Systems II Express Briefs (1 paper)
Partner nations: United States United Kingdom Australia

In The Last Decade

Tim Oates

146 papers receiving 3.8k citations

Hit Papers

align trajectories log scale

Time series classification from scratch with deep neural networks: A strong baseline 2017 · 1.2k citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2017 Time series classification from scratch with deep neural networks: A strong baseline
2015 National Conference on Artificial Intelligence

Peers

Countries citing papers authored by Tim Oates

Since Specialization

Citations

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

Fields of papers citing papers by Tim Oates

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tim Oates, 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 Tim Oates Line = papers co-authored together Tim Oates 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 157 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Time series classification from scratch with deep neural networks: A strong baseline Zhiguang Wang, Weizhong Yan, Tim Oates Hit paper breakdown →	2017	1235
2	Encoding Time Series as Images for Visual Inspection and Classification Using Tiled Convolutional Neural Networks National Conference on Artificial Intelligence ·Zhiguang Wang, Tim Oates Hit paper breakdown →	2015	258
3	Efficient progressive sampling Foster Provost, David Jensen, Tim Oates	1999	237
4	Electroencephalogram epileptiform abnormalities in candidates for aircrew training Electroencephalography and Clinical Neurophysiology ·Rebecca Gregory, Tim Oates, R.T.G. Merry	1993	153
5	Could do better: using international comparisons to refine the National Curriculum in England The Curriculum Journal ·Tim Oates	2011	95
6	Modeling the Spread of Influence on the Blogosphere Maryland Shared Open Access Repository (USMAI Consortium) ·Akshay Java, Pranam Kolari, Tim Finin, Tim Oates	2006	94
7	Detecting Spam Blogs: A Machine Learning Approach Maryland Shared Open Access Repository (USMAI Consortium) ·Pranam Kolari, Akshay Java, Tim Finin, Tim Oates, Anupam Joshi	2006	92
8	A Flexible Multichannel EEG Feature Extractor and Classifier for Seizure Detection IEEE Transactions on Circuits & Systems II Express Briefs ·Adam Page, Chris Sagedy, Emily A. Smith, Nasrin Attaran, Tim Oates, Tinoosh Mohsenin	2014	83
9	The Effects of Training Set Size on Decision Tree Complexity International Conference on Machine Learning ·Tim Oates, David Jensen	1997	82
10	SensorNet: A Scalable and Low-Power Deep Convolutional Neural Network for Multimodal Data Classification IEEE Transactions on Circuits and Systems I Regular Papers ·Ali Jafari, Ashwinkumar Ganesan, Chetan Sai Kumar Thalisetty, Varun Sivasubramanian, Tim Oates, Tinoosh Mohsenin	2018	76
11	Identifying distinctive subsequences in multivariate time series by clustering Tim Oates	1999	64
12	Cooperative information-gathering: a distributed problem-solving approach Tim Oates, Munaga V. N. K. Prasad, Victor Lesser	1997	62
13	Large datasets lead to overly complex models: an explanation and a solution Knowledge Discovery and Data Mining ·Tim Oates, David Jensen	1998	53
14	Visualizing Variable-Length Time Series Motifs Yuan Li, Jessica Lin, Tim Oates	2012	52
15	The framework for the national curriculum : a report by the expert panel for the national curriculum review Digital Education Resource Archive (University College London) ·Mary James, Tim Oates, Andrew J. Pollard, Dylan Wiliam	2011	51
16	A Method for Clustering the Experiences of a Mobile Robot that Accords with Human Judgments National Conference on Artificial Intelligence ·Tim Oates, Matthew D. Schmill, Paul R. Cohen	2000	50
17	Searching for Structure in Multiple Streams of Data. International Conference on Machine Learning ·Tim Oates, Paul R. Cohen	1996	49
18	Time series anomaly discovery with grammar-based compression Movebank ·Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein	2015	49
19	PERUSE: An unsupervised algorithm for finding recurring patterns in time series Tim Oates	2003	48
20	Early Detection of Cybersecurity Threats Using Collaborative Cognition Sandeep Nair Narayanan, Ashwinkumar Ganesan, Karuna Pande Joshi, Tim Oates, Anupam Joshi, Tim Finin	2018	41

About Tim Oates

Tim Oates is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Information Systems and Computer Networks and Communications, having authored 157 papers that have together received 4.0k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (28 papers), Natural Language Processing Techniques (19 papers), AI-based Problem Solving and Planning (17 papers), Reinforcement Learning in Robotics (16 papers), Advanced Text Analysis Techniques (14 papers), Anomaly Detection Techniques and Applications (14 papers), Topic Modeling (13 papers) and Music and Audio Processing (12 papers). The work is most often cited by research in Signal Processing (1.2k citations), Artificial Intelligence (1.9k citations), Information Systems (543 citations), Computer Vision and Pattern Recognition (471 citations) and Cognitive Neuroscience (389 citations). Tim Oates has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Zhiguang Wang, Weizhong Yan, David Jensen, Paul R. Cohen, Foster Provost, Tim Finin, Pranam Kolari, Rebecca Gregory, Michael L. Anderson and Akshay Java. Their work appears in journals such as AI Magazine, The Journal of the Acoustical Society of America, The Curriculum Journal, Solar Physics and IEEE Transactions on Circuits & Systems II Express Briefs.

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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