World's Best Scientists 2026 revealed!
Tomoaki Ohtsuki

Tomoaki Ohtsuki

D-Index & Metrics

Computer Science

D-Index
50
Citations
11002
World Ranking
5584
National Ranking
72

Research.com Recognitions

  • 1984 - IEEE Fellow For contributions to circuit theory and computer-aided circuit analysis.

Overview

Tomoaki Ohtsuki is affiliated with Keio University in Japan and has an extensive publication record spanning engineering and computer science disciplines. Their work encompasses a variety of research areas, with a strong focus on electrical and electronic engineering as well as artificial intelligence. The scientist's breadth of expertise includes computer networks and communications, aerospace engineering, and computer vision and pattern recognition.

The research topics addressed by Ohtsuki include advanced MIMO systems optimization, non-invasive vital sign monitoring, wireless signal modulation classification, ECG monitoring and analysis, millimeter-wave propagation and modeling, UAV applications and optimization, and network security and intrusion detection.

Ohtsuki has frequently published in the following venues:

  • IEEE Internet of Things Journal
  • IEEE Access
  • Sensors
  • IEEE Transactions on Vehicular Technology
  • arXiv (Cornell University)

Some of the recent papers authored or co-authored by Ohtsuki include:

  • "An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression", 2021, IEEE Journal on Selected Areas in Communications
  • "A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things", 2021, IEEE Internet of Things Journal
  • "Deep Reinforcement Learning for Economic Dispatch of Virtual Power Plant in Internet of Energy", 2020, IEEE Internet of Things Journal
  • "Multi-Task Learning for Generalized Automatic Modulation Classification Under Non-Gaussian Noise With Varying SNR Conditions", 2021, IEEE Transactions on Wireless Communications
  • "Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things", 2022, IEEE Internet of Things Journal

Ohtsuki has collaborated extensively with several co-authors, including:

  • Guan Gui
  • Mondher Bouazizi
  • Hikmet Sari
  • Yu Wang
  • Kohei Yamamoto

The scientist was awarded the IEEE Fellow distinction in 1984 for contributions to circuit theory and computer-aided circuit analysis. This recognition highlights a significant point in their academic career.

Best Publications

  • A Novel Blockchain-Based Product Ownership Management System (POMS) for Anti-Counterfeits in the Post Supply Chain

    Kentaroh Toyoda;P. Takis Mathiopoulos;Iwao Sasase;Tomoaki Ohtsuki

  • Hate Speech on Twitter: A Pragmatic Approach to Collect Hateful and Offensive Expressions and Perform Hate Speech Detection

    Hajime Watanabe;Mondher Bouazizi;Tomoaki Ohtsuki

  • A Pattern-Based Approach for Sarcasm Detection on Twitter

    Mondher Bouazizi;Tomoaki Otsuki Ohtsuki

  • An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression

    Yu Wang;Guan Gui;Haris Gacanin;Tomoaki Ohtsuki

  • A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things

    Ruijie Zhao;Guan Gui;Zhi Xue;Jie Yin

  • A Pattern-Based Approach for Multi-Class Sentiment Analysis in Twitter

    Mondher Bouazizi;Tomoaki Ohtsuki

  • Design criteria for phase sequences in selected mapping

    N. Ohkubo;T. Ohtsuki

  • Multiple-subcarrier modulation in optical wireless communications

    T. Ohtsuki

  • Pre-Rake Diversity Combining for UWB Systems in IEEE 802.15 UWB Multipath Channel

    Shunsuke Imada;Tomoaki Ohtsuki

  • Performance analysis of direct-detection optical asynchronous CDMA systems with double optical hard-limiters

    T. Ohtsuki

  • Deep Reinforcement Learning for Economic Dispatch of Virtual Power Plant in Internet of Energy

    Lin Lin;Xin Guan;Yu Peng;Ning Wang

  • Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things

    Unknown

  • Performance analysis of atmospheric optical PPM CDMA systems

    T. Ohtsuki

  • Multi-Task Learning for Generalized Automatic Modulation Classification Under Non-Gaussian Noise With Varying SNR Conditions

    Yu Wang;Guan Gui;Tomoaki Ohtsuki;Fumiyuki Adachi

  • Transfer Learning for Semi-Supervised Automatic Modulation Classification in ZF-MIMO Systems

    Yu Wang;Guan Gui;Haris Gacanin;Tomoaki Ohtsuki

  • Low-density parity-check (LDPC) coded OFDM systems

    H. Futaki;T. Ohtsuki

  • Direct-detection optical synchronous CDMA systems with double optical hard-limiters using modified prime sequence codes

    T. Ohtsuki;K. Sato;I. Sasase;S. Mori

  • A Deep Learning-Based Low Overhead Beam Selection in mmWave Communications

    Haruhi Echigo;Yuwen Cao;Mondher Bouazizi;Tomoaki Ohtsuki

  • A peak to average power ratio reduction of multicarrier CDMA using selected mapping

    N. Ohkubo;T. Ohtsuki

  • Multi-Class Sentiment Analysis on Twitter: Classification Performance and Challenges

    Mondher Bouazizi;Tomoaki Ohtsuki

  • RSS-Based Localization in Environments with Different Path Loss Exponent for Each Link

    J. Shirahama;T. Ohtsuki

  • Performance of low-density parity-check (LDPC) coded OFDM systems

    H. Futaki;T. Ohtsuki

  • BER performance of turbo-coded PPM CDMA systems on optical fiber

    T. Ohtsuki;J.M. Kahn

  • Performance evaluation of UWB-IR and DS-UWB with MMSE-frequency domain equalization (FDE)

    Y. Ishiyama;T. Ohtsuki

Frequent Co-Authors

Guan Gui
Guan Gui Nanjing University of Posts and Telecommunications
Fumiyuki Adachi
Fumiyuki Adachi Tohoku University
Min Chen
Min Chen South China University of Technology
Joseph M. Kahn
Joseph M. Kahn Stanford University
Guangjie Han
Guangjie Han Hohai University
Haris Gacanin
Haris Gacanin RWTH Aachen University
Hikmet Sari
Hikmet Sari Nanjing University of Posts and Telecommunications
Zhipeng Cai
Zhipeng Cai Georgia State University
Bamidele Adebisi
Bamidele Adebisi Manchester Metropolitan University
Seiichiro Katsura
Seiichiro Katsura Keio University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens the door to a variety of online degree options and career pathways. Many students are now choosing flexible learning formats, such as an accelerated computer science degree, which allows learners to complete their studies faster while balancing other life commitments.

Interdisciplinary fields are also accessible online. For those interested in sustainability, an online environmental engineering degree offers specialized courses in ecology, energy, and technology solutions for the environment.

Cost is an important factor in choosing any program. You can compare options based on affordability, such as the mechanical engineering cost of education across top institutions, helping you balance quality with budget.

For students drawn to fundamental sciences, the best online physics degree programs combine theoretical learning with practical skills in a flexible format.

These pathways illustrate how online degrees are evolving to fit modern student needs, setting graduates on diverse and rewarding technology and engineering careers.

Best Scientists Citing Tomoaki Ohtsuki

Trending Scientists