Biography

Having nailed a Bachelor's degree in Communications Engineering from Beijing University of Posts and Telecommunications, I completed a Master's Degree in Software Engineering from Tsinghua University. Since graduating, I have been actively involved in FinTech, AI, and Decentralized Technology sectors.

I am holding roles such as Tech Lead, Chief Product Officer (CPO), and Chief Technology Officer (CTO) at multiple startups. I am recognized for my exceptional learning abilities and communication skills. I adapt quickly to diverse working environments, easily integrate into new communities, and efficiently complete tasks under significant constraints. I am a dedicated worker with a strong sense of responsibility and a robust team spirit.

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Projects

• Flexshield [2025-Now]: Revolutionary insurance app utilizing AI to enable daily brokerage payments and tokenized incentives for users.
• Matchain [2024-Now]: Decentralized network leveraging AI to return data sovereignty to users through a tokenized Data DAO.
• GROWLA app [2021-2023]: Educational app providing tailored AI-driven services to institutions, teachers, and students.
• Orient app [2018-2020]: Educational app offering AI-enhanced services tailored for student needs.
• CAMDroid [2014-2017]: Developed an AI-driven multitasking framework for Android enhancing real-time user-app interaction.
• MusicLinks app [2012-2013]: Audio-driven music search engine on iOS for discovering, downloading, and socially sharing songs.

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Publications

• Proceedings of the First International Workshop on Human-centered Sensing, Networking, and Systems
  2017-11-05 | Conference paper
  DOI: 10.1145/3144730.3144740
  CONTRIBUTORS: Kouemo Ngayo Anatoli Dimitrov; Xiaolong Zheng; Fu Xiao
  Subtitle: An Adaptation Framework for Android Context-Aware Multitasking
  Contributors: Kouemo Ngayo Anatoli Dimitrov (Author: first), Xiaolong Zheng (Author: additional), Fu Xiao (Author: additional)
  Citation (bibtex):

  @inproceedings{Dimitrov_2017, series = {SenSys ’17}, title = {CAMDroid: An Adaptation Framework for Android Context-Aware Multitasking}, url = {http://dx.doi.org/10.1145/3144730.3144740}, DOI = {10.1145/3144730.3144740}, booktitle = {Proceedings of the First International Workshop on Human-centered Sensing, Networking, and Systems}, publisher = {ACM}, author = {Dimitrov, Kouemo Ngayo Anatoli and Zheng, Xiaolong and Xiao, Fu}, year = {2017}, month = {nov}, pages = {55–60}, collection = {SenSys ’17} }

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Books

• Fundamentals of Software Culture

This book chapter delves into the classification and cultural impact of software development, featuring:

• DOI: 10.1007/978-981-13-0701-0_3
• Part of ISBN: 9789811307010
Contributors:
• Zheng Qin (Lead Author)
• Huidi Zhang, Xin Qin, Kaiping Xu, Kouemo Ngayo Anatoli Dimitrov, Guolong Wang, Wenhui Yu (Additional Authors)
Citation (bibtex):

                        @inbook{Qin_2018,
                            title = {Classification and Software Culture},
                            ISBN = {9789811307010},
                            url = {http://dx.doi.org/10.1007/978-981-13-0701-0_3},
                            DOI = {10.1007/978-981-13-0701-0_3},
                            booktitle = {Fundamentals of Software Culture},
                            publisher = {Springer Singapore},
                            author = {Qin, Zheng and Zhang, Huidi and Qin, Xin and Xu, Kaiping and Dimitrov, Kouemo Ngayo Anatoli and Wang, Guolong and Yu, Wenhui},
                            year = {2018},
                            pages = {83–136}
                        }
                        

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Patents

• Android-Based System Resource Management Method

This method involves an algorithm for managing system resources within an Android environment, characterized by:

1. S1, utilizing an internal command context-aware framework to assess the usage rate of any application.
2. S2, ranking all applications based on their usage rates from highest to lowest to form an initial application set.
3. S3, applying an adaptive mechanism to adjust the initial set and obtain the final application collection.
Further, step S1 includes:
• Acquiring internal context awareness through the internal command context-aware framework, which includes each application's foreground time, first count, and second count during a preset period.
• The foreground time is the time an application occupies in the foreground, the first count is the number of times an application is launched, and the second count is the number of times an application is opened before it becomes the foreground app.
• Based on this internal context awareness, the usage rate of any application is determined as: vi = vti + vhi + vci, where vi is the usage rate of the ith application, vti is the foreground time, vhi is the first count, and vci is the second count.
For more details, tap this link.

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Contact

•  hoopsdoogy@gmail.com