Anand Oka

417 total citations
16 papers, 274 citations indexed

About

Anand Oka is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Anand Oka has authored 16 papers receiving a total of 274 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 9 papers in Computer Networks and Communications and 7 papers in Artificial Intelligence. Recurrent topics in Anand Oka's work include Target Tracking and Data Fusion in Sensor Networks (6 papers), Distributed Sensor Networks and Detection Algorithms (5 papers) and Indoor and Outdoor Localization Technologies (4 papers). Anand Oka is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (6 papers), Distributed Sensor Networks and Detection Algorithms (5 papers) and Indoor and Outdoor Localization Technologies (4 papers). Anand Oka collaborates with scholars based in Canada, United States and Germany. Anand Oka's co-authors include Lutz Lampe, Trung Thành Nguyễn, Yuting Jia, John Beaver, Nicholas L Stucky, Peter Tarczy‐Hornoch, Jennifer Hadlock, Charlotte Baker, Duy Do and Hao Lin and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Journal on Selected Areas in Communications and IEEE Transactions on Communications.

In The Last Decade

Anand Oka

16 papers receiving 264 citations

Peers

Anand Oka
Janghoon Yang South Korea
Richard MacKenzie United Kingdom
Sudarshan Vasudevan United States
L. Clare United States
Een‐Kee Hong South Korea
Anand Oka
Citations per year, relative to Anand Oka Anand Oka (= 1×) peers Biling Zhang

Countries citing papers authored by Anand Oka

Since Specialization
Citations

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

Fields of papers citing papers by Anand Oka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anand Oka

This figure shows the co-authorship network connecting the top 25 collaborators of Anand Oka. A scholar is included among the top collaborators of Anand Oka 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 Anand Oka. Anand Oka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Gratzl, Samuel, Ahmad Algohary, Hao Lin, et al.. (2025). XComposition: multimodal deep learning model to measure body composition using chest radiographs and clinical data. PubMed. 2(5). umaf035–umaf035. 1 indexed citations
2.
Jia, Yuting, et al.. (2020). Microsoft Uses Machine Learning and Optimization to Reduce E-Commerce Fraud. 50(1). 64–79. 27 indexed citations
3.
Oka, Anand, et al.. (2010). A comparison between Unscented Kalman Filtering and particle filtering for RSSI-based tracking. 39. 157–163. 28 indexed citations
4.
Oka, Anand & Lutz Lampe. (2010). Distributed target tracking using signal strength measurements by a wireless sensor network. IEEE Journal on Selected Areas in Communications. 28(7). 1006–1015. 55 indexed citations
5.
Oka, Anand, et al.. (2010). Rateless coding for hybrid free-space optical and radio-frequency communication. IEEE Transactions on Wireless Communications. 9(3). 907–913. 52 indexed citations
6.
Oka, Anand & Lutz Lampe. (2009). Incremental Distributed Identification of Markov Random Field Models in Wireless Sensor Networks. IEEE Transactions on Signal Processing. 57(6). 2396–2405. 7 indexed citations
7.
Oka, Anand & Lutz Lampe. (2009). A compressed sensing receiver for bursty communication with UWB Impulse Radio. 279–284. 9 indexed citations
8.
Oka, Anand & Lutz Lampe. (2009). Compressed Sensing Reception of Bursty UWB Impulse Radio is Robust to Narrow-Band Interference. 1–7. 16 indexed citations
9.
Oka, Anand & Lutz Lampe. (2009). Data extraction from wireless sensor networks using distributed fountain codes. IEEE Transactions on Communications. 57(9). 2607–2618. 10 indexed citations
10.
Oka, Anand & Lutz Lampe. (2009). Distributed Scalable Multi-Target Tracking with a Wireless Sensor Network. 1–6. 2 indexed citations
11.
Oka, Anand & Lutz Lampe. (2009). A compressed sensing receiver for UWB impulse radio in bursty applications like wireless sensor networks. Physical Communication. 2(4). 248–264. 25 indexed citations
12.
Oka, Anand, et al.. (2008). Decoding with Early Termination for Raptor Codes. IEEE Communications Letters. 12(6). 444–446. 23 indexed citations
13.
Oka, Anand & Lutz Lampe. (2008). Energy Efficient Distributed Filtering With Wireless Sensor Networks. IEEE Transactions on Signal Processing. 56(5). 2062–2075. 11 indexed citations
14.
Oka, Anand, et al.. (2008). Decoding with Early Termination for Rateless (Luby Transform) Codes. 249–254. 5 indexed citations
15.
Oka, Anand & Lutz Lampe. (2007). Data Extraction from Wireless Sensor Networks Using Fountain Codes. 21. 229–232. 1 indexed citations
16.
Oka, Anand & Lutz Lampe. (2007). Model Identification for Wireless Sensor Networks. 3013–3018. 2 indexed citations

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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