Ruslan Asfandiyarov | Engineering | Best Researcher Award

Mr. Ruslan Asfandiyarov | Engineering | Best Researcher Award

Researcher, Independent, Switzerland

Ruslan Asfandiyarov is a seasoned professional with a 19-year career that spans theoretical physics, data science, and AI. He has made significant strides in digital transformation across various sectors, including medical devices and renewable energy. Ruslan’s expertise blends fundamental science, engineering, and advanced data analysis, leading to patents in microelectronics and sensor design. His leadership, combined with extensive multi-cultural experience, has positioned him as a visionary in navigating complex interdisciplinary landscapes. 🌟🔬

Profile

 

Strengths for the Award

  1. Innovative Contributions: Ruslan Asfandiyarov has a strong record of pioneering advancements in data science, AI, and digital transformation. His work in medical devices, renewable energy, and next-gen technology solutions aligns well with the award’s focus on community impact.
  2. Global Experience and Leadership: His leadership roles across multiple sectors and international experience demonstrate his capability to drive impactful research and development. This global perspective is beneficial for understanding and addressing diverse community needs.
  3. Significant Achievements:
    • MedTech Innovations: Co-founding Spiden and developing new diagnostic medical devices shows a direct impact on healthcare.
    • Renewable Energy: His work in geothermal and solar power projects contributes to sustainable development and environmental protection.
    • AI and Digital Transformation: His involvement in digital transformation and AI research, including applications in labor market analysis, showcases his commitment to leveraging technology for societal benefits.
  4. Academic and Industry Accomplishments:
    • Contribution to Nobel Prize-winning research and substantial patents in various fields underscore his research excellence.
    • His high citation impact and recognition in Swiss media highlight his influence in the scientific and entrepreneurial communities.
  5. Strategic Vision and Execution: His ability to secure funding, scale startups, and build cross-functional teams reflects his strategic planning and execution skills.

Areas for Improvement

  1. Direct Community Engagement: While his innovations have broad impacts, the profile could benefit from more explicit examples of how his work has directly engaged and benefited specific communities or underserved populations.
  2. Documentation of Community Impact: Providing more detailed case studies or data on how his projects have improved community health, economic conditions, or environmental sustainability would strengthen his application.
  3. Integration of Community Feedback: Demonstrating how community feedback has shaped his projects or led to adaptations that better serve community needs would be valuable.

Education

Ruslan earned his PhD in Physics from the University of Geneva and Rutherford Laboratory, Oxford, UK (2010–2014). He also holds a degree in Engineering & Physics from National Research Nuclear University, Moscow, Russia (2001–2007), where he specialized in experiments in natural sciences and engineering. 🎓📚

Experience

Ruslan has held influential roles including Adviser on Digital Transformation and AI at the Ministry of Labor in Qatar, AI Researcher, and Founder & CEO of Deepeex. He has also founded and co-founded several ventures, including startups and consulting firms, raising over CHF 20 million and creating numerous high-paid jobs. His career highlights include contributing to a Nobel Prize-winning discovery and managing significant projects in space science and medical technology. 🚀💼

Research Interests

Ruslan’s research interests encompass AI and data science, particularly in the intersection of Large Language Models (LLMs) with scientific discovery and creativity. He explores how AI can augment scientific inference and has a strong focus on Natural Language Processing (NLP), machine learning, and high-performance computing. 🤖🔍

Awards

Ruslan’s accolades include being featured by Bilan magazine as a top entrepreneur in Swiss Romand and his startup, Spiden, being named the No.1 MedTech venture in 2021 by Top 100 Swiss Startups. His h-index of 103 underscores his impactful contributions to the field. 🏆🌍

Publications

  1. The ATLAS Simulation Infrastructure
    ATLAS Collaboration. The European Physical Journal C, 2010.Link
  2. Improved Luminosity Determination in pp Collisions Using the ATLAS Detector at the LHC
    ATLAS Collaboration. The European Physical Journal C, 2013.Link
  3. Performance of Missing Transverse Momentum Reconstruction in Proton-Proton Collisions at √s = 7 TeV with ATLAS
    ATLAS Collaboration. The European Physical Journal C, 2012.Link
  4. Measurement of the Inclusive Isolated Prompt Photon Cross Section in pp Collisions at √s = 7 TeV with the ATLAS Detector
    ATLAS Collaboration. arXiv preprint arXiv:1012.4389, 2010.Link
  5. Observation of a Centrality-Dependent Dijet Asymmetry in Lead-Lead Collisions at √sNN = 2.76 TeV with the ATLAS Detector at the LHC

 

Chao-Chen Gu | Engineering | Best Researcher Award

Prof Dr. Chao-Chen Gu | Engineering | Best Researcher Award

Prof., Shanghai Jiao Tong University, China

Chao-Chen Gu is a distinguished professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. Renowned for his contributions to the fields of electromechanical systems, intelligent robotics, and precision instruments, he has pioneered research in intelligent machine vision and advanced motion control. With numerous national and provincial key projects under his belt, Professor Gu is a leading figure in his domain, recognized for his innovative approach to solving complex engineering problems.

Profile

Strengths for the Award

  1. Extensive Research Projects: Professor Gu has completed over ten national and provincial-level key projects. This demonstrates his active involvement in significant research efforts that likely have substantial community impact.
  2. Innovative Contributions: His work in machine vision and precision control, especially innovations in micro precision measurement, robot vision cognition, and high-order nonlinear system disturbance rejection and control, indicates a focus on advanced technology that can significantly benefit various sectors, including healthcare, manufacturing, and robotics.
  3. High Volume of Patents and Publications: With over 70 patents and 80 published works, Professor Gu’s contributions to his field are well-documented and recognized, highlighting his role in advancing technology and engineering.
  4. Industry Projects: The completion of more than five consultancy or industry projects suggests practical applications of his research, which is a key factor for community impact.

Areas for Improvement

  1. Professional Memberships and Collaborations: There is a lack of listed professional memberships and collaborations. Engaging more with professional organizations and collaborating with other researchers or institutions could enhance the reach and impact of his work.
  2. Books and Editorial Appointments: No books or editorial appointments were mentioned. Authoring books and holding editorial positions could further establish his authority in his field and disseminate his research more broadly.
  3. Explicit Community Impact: While his research is undoubtedly advanced, the specific community impact of his projects could be more explicitly stated. Providing concrete examples of how his work has benefitted communities or specific sectors would strengthen his application.

🎓 Education:

Chao-Chen Gu earned his bachelor’s degree from Shandong University in 2007, followed by a Ph.D. in Mechanical Engineering from Shanghai Jiao Tong University in 2013. His academic journey has equipped him with a solid foundation in mechanical engineering and advanced technological systems, propelling his research career forward.

🧑‍💼 Experience:

Currently serving as a professor at Shanghai Jiao Tong University, Chao-Chen Gu has led more than ten key national and provincial-level projects. His expertise spans electromechanical systems, intelligent robotics, and precision instruments, with a notable focus on intelligent machine vision and advanced motion control.

🔬 Research Interests:

Chao-Chen Gu’s research interests lie in the realms of electromechanical systems, intelligent robotics, and precision instruments. He is particularly focused on intelligent machine vision and advanced motion control, contributing significantly to innovations in micro precision measurement, robot vision cognition, and high-order nonlinear system disturbance rejection and control.

🏆 Awards:

Chao-Chen Gu has not specified individual awards, but his prolific contributions to research and numerous completed projects reflect his standing as a leader in his field.

Publications 

  1. An integrated AHP and VIKOR for design concept evaluation based on rough number
    Authors: GN Zhu, J Hu, J Qi, CC Gu, YH Peng
    Journal: Advanced Engineering Informatics
    Year: 2015
    Cited by: 329 articles
    Link to publication
  2. Complementary patch for weakly supervised semantic segmentation
    Authors: F Zhang, C Gu, C Zhang, Y Dai
    Journal: Proceedings of the IEEE/CVF International Conference on Computer Vision
    Year: 2021
    Cited by: 131 articles
    Link to publication
  3. FCBS model for functional knowledge representation in conceptual design
    Authors: CC Gu, J Hu, YH Peng, S Li
    Journal: Journal of Engineering Design
    Year: 2012
    Cited by: 48 articles
    Link to publication
  4. Corporate innovation and R&D expenditure disclosures
    Authors: C Chen, J Gu, R Luo
    Journal: Technological Forecasting and Social Change
    Year: 2022
    Cited by: 30 articles
    Link to publication
  5. Imaging Mueller matrix ellipsometry with sub-micron resolution based on back focal plane scanning
    Authors: C Chen, X Chen, C Wang, S Sheng, L Song, H Gu, S Liu
    Journal: Optics Express
    Year: 2021
    Cited by: 26 articles
    Link to publication
  6. SVMs multi-class loss feedback based discriminative dictionary learning for image classification
    Authors: BQ Yang, XP Guan, JW Zhu, CC Gu, KJ Wu, JJ Xu
    Journal: Pattern Recognition
    Year: 2021
    Link to publication