Corey Trahan | Quantum Science | Best Researcher Award

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Dr. Corey Trahan | Quantum Science | Best Researcher Award

Physicist, United States Army Corps of Engineers, United States

Corey Jason Trahan, Ph.D. is a distinguished Research Physicist at the US Army Corps of Engineers, Engineering Research and Development Center (ERDC), Information Technology Laboratory, and a Lecturer at the University of Texas in Austin. With a Ph.D. in Theoretical Chemistry from UT Austin, Dr. Trahan specializes in applied mathematics, computational mechanics, and fluid dynamics. His career includes roles at various prestigious institutions, focusing on high-performance computing and innovative software design. In addition to his research, Dr. Trahan has contributed to numerous publications and has been recognized with several awards for his impactful work. 🏆🔬

Publication Profile

Strengths for the Award:

  1. Diverse Expertise: Dr. Corey J. Trahan’s research spans a wide range of cutting-edge fields, including applied mathematics, computational mechanics, fluid dynamics, and quantum physics. His ability to work across various domains, including high-performance computing and uncertainty quantification, demonstrates a high level of versatility and expertise.
  2. Extensive Experience: With a robust background in both academic and practical applications, Dr. Trahan has significant experience in innovative research and software design. His current role as a Research Physicist at USACE-ERDC and his role as a Lecturer at the University of Texas showcase his dual commitment to research and education.
  3. Notable Publications: Dr. Trahan has published extensively in reputable journals and conferences, demonstrating a strong record of scholarly contributions. His work covers a broad spectrum of topics, including quantum dynamics, fluid dynamics, and computational methods.
  4. Awards and Honors: His receipt of several prestigious awards, including the USACE-ERDC Research and Development Achievement Award and the Civilian Service Commendation Medal, underscores his significant impact and recognition in his field.
  5. Innovative Contributions: Dr. Trahan’s involvement in developing advanced numerical models and software for solving complex scientific problems, such as partial differential equations and adaptive hydraulics, highlights his contributions to both theoretical and applied research.

Areas for Improvement:

  1. Broader Impact and Outreach: While Dr. Trahan has an impressive academic and research portfolio, increasing visibility through broader outreach activities, such as public lectures or collaborations with industry stakeholders, could further enhance his impact.
  2. Diverse Research Areas: Expanding into emerging research areas or interdisciplinary fields might offer additional opportunities for innovation and influence, particularly in integrating new technologies or methodologies into his work.
  3. Collaborative Projects: Increasing participation in collaborative projects with international researchers or industry partners could further broaden the scope and application of his research.

Conclusion:

Dr. Corey J. Trahan is a highly qualified candidate for the Research for Best Researcher Award. His extensive expertise in multiple scientific disciplines, significant contributions to both theoretical and practical aspects of research, and recognition through prestigious awards make him an exemplary candidate. His continued focus on innovative research and his dual role in academia and applied research demonstrate a profound commitment to advancing knowledge and solving complex problems. While there are opportunities for expanding his outreach and collaborative efforts, Dr. Trahan’s achievements and ongoing contributions strongly support his suitability for this award.

 

Education

Dr. Trahan earned his Ph.D. in Theoretical Chemistry from the University of Texas in Austin in 2003. He also holds dual B.S. degrees in Physics and Chemistry from Lamar University, both completed in 1999. His academic background underpins his expertise in computational mechanics and quantum physics. 🎓📚

Professional Experience

Dr. Trahan has extensive experience in computational research and software design. He has been a Research Physicist at USACE-ERDC since 2013, where he focuses on solving partial differential equations and uncertainty quantification. He also serves as an Adjunct Professor at the University of Texas in Austin, teaching advanced scientific computing. His previous roles include postdoctoral fellowships and positions at High Performance Technologies and Sight Software, where he contributed to the development of advanced computational methods and software. 💼🔍

Research Focus

Dr. Trahan’s research interests span applied mathematics, computational mechanics, fluid dynamics, and uncertainty quantification. He is also deeply involved in quantum physics, computer science, and high-performance computing. His work includes developing innovative solutions for partial differential equations, finite element methods, and applications in computational fluid dynamics. 🔎💻

Awards

Dr. Trahan has been recognized with several prestigious awards, including the Laboratory University Collaboration Initiative Award for fostering collaboration between DoD lab scientists and academics, the USACE-ERDC Research and Development Achievement Award in Spring 2022, and the USACE-ERDC Award for Outstanding Team Effort in Spring 2020. 🏅🎖️

 

Publication Top Notes

Quantum Physics-Informed Neural Networks

A Variational Quantum Linear Solver Application to Discrete Finite-Element Methods

Urban and overland flow modeling with dynamic adaptive mesh and implicit diffusive wave equation solver

Surface trajectories of oil transport along the Northern Coastline of the Gulf of Mexico

Local time-stepping in Runge–Kutta discontinuous Galerkin finite element methods applied to the shallow-water equations

Diego Resende Faria | Multisensory AI | Excellence in Research

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Assoc Prof Dr. Diego Resende Faria | Multisensory AI | Excellence in Research

Reader in Robotics and Intelligent Adaptive Systems, University of Hertfordshire, United Kingdom

Dr. Diego Resende Faria is a Reader (Associate Professor) in Robotics and Intelligent Adaptive Systems at the University of Hertfordshire, UK. He has been contributing to the field of robotics and intelligent systems since 2022. With extensive experience in human-centered robotics, he has led and participated in various high-profile research projects across Europe. His work focuses on the integration of artificial intelligence in robotics to enhance human-robot interaction and autonomous systems. 🤖🌟

Publication Profile

Strengths for the Award

  1. Research Contributions:
    • Diverse Expertise: Dr. Faria’s research covers a broad range of topics, including cognitive robotics, affective robotics, artificial perception, and autonomous systems. His work on human manipulation, robotic grasping, and human-robot interaction is notable and demonstrates a significant contribution to his field.
    • Project Coordination and Leadership: He has successfully coordinated significant projects such as the EU CHIST-ERA InDex project and the Sim2Real project, showcasing his leadership and ability to manage high-impact research.
    • High-Quality Publications: His publications in well-regarded journals, such as Complexity and the Journal of Social Robotics, indicate a strong research output with relevance and impact in his field.
  2. Funding and Grants:
    • Secured Funding: Dr. Faria has obtained substantial funding for various projects, including EU Horizon projects and industry collaborations. His ability to attract significant grants demonstrates recognition and trust in his research capabilities.
  3. Academic and Professional Roles:
    • Positions of Influence: His roles as a Reader (Associate Professor) and past positions at prestigious institutions like Aston University and the University of Coimbra highlight his academic leadership and influence in robotics and intelligent systems.
  4. Editorial and Review Activities:
    • Journals and Conferences: Dr. Faria’s involvement as a guest editor for several journals and his role in program committees and conference chairs showcase his active participation in shaping the research community.

Areas for Improvement

  1. Broader Impact and Outreach:
    • Public Engagement: While his research is robust, there could be more emphasis on how his work impacts broader societal challenges or contributes to public understanding of robotics and artificial intelligence.
  2. Collaborative Networks:
    • Interdisciplinary Collaborations: Expanding his research to include interdisciplinary collaborations beyond robotics and AI could enhance the application and visibility of his work in other fields.
  3. Recognition and Awards:
    • Professional Awards: Achieving recognition through more prestigious awards or accolades specific to his research area could further validate his contributions and enhance his profile.

Conclusion

Dr. Diego Resende Faria is highly suitable for the “Research for Excellence in Research” award due to his extensive research contributions, leadership in significant projects, and strong publication record. His ability to secure substantial funding and his active involvement in the academic community further strengthen his candidacy. Addressing areas such as public engagement and expanding interdisciplinary collaborations could enhance his impact and recognition even further. Overall, his profile demonstrates a high level of excellence in research, making him a strong candidate for this award.

Education

Dr. Faria earned his Ph.D. in Electrical and Computer Engineering from the University of Coimbra, Portugal, in 2014. His academic journey continued with a postdoctoral fellowship at the Institute of Systems and Robotics, where he specialized in human-centered robotics. 🎓📚

Experience

Before joining the University of Hertfordshire, Dr. Faria was a Lecturer and Senior Lecturer at Aston University, UK, from 2016 to 2022. His career includes leading the EU CHIST-ERA InDex project, which was funded by EPSRC UK, and serving as PI for the Sim2Real project funded by the Royal Society. He is also involved in several industry-linked projects focusing on autonomous vehicles and multimedia retrieval. 🏛️🔬

Research Focus

Dr. Faria’s research interests include Neuro-Affective Intelligence, Cognitive Robotics (including Affective Robotics, Grasping and Dexterous Manipulation, and Human-Robot Interaction), Artificial Perception, Autonomous Systems, and Applied Machine Learning. His work aims to advance the capabilities of robotics in human-centered applications. 🧠🤖📊

Award and honors

Dr. Faria has received recognition for his contributions to robotics and intelligent systems, including significant project funding and accolades from international research bodies. His innovative work in autonomous systems and human-robot interaction has earned him a prominent place in the field. 🏆🔍

Publications Top Notes

  1. A Study on CNN Transfer Learning for Image Classification
  2. A Study on Mental State Classification using EEG-based Brain-Machine Interface
  3. A Probabilistic Approach for Human Everyday Activities Recognition using Body Motion from RGB-D Images
  4. Mental Emotional Sentiment Classification with an EEG-based Brain-Machine Interface
  5. Cross-domain MLP and CNN Transfer Learning for Biological Signal Processing: EEG and EMG

 

Ruslan Asfandiyarov | Engineering | Best Researcher Award

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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

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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

 

Jinwei Bu | Engineering | Best Researcher Award

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Dr. Jinwei Bu | Engineering | Best Researcher Award

Master Supervisor, Kunming University of Science and Technology, China

👨‍🏫  Dr. Jinwei Bu, a dedicated researcher and member of IEEE, is currently a Master Supervisor at the Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, China. With a robust academic and research background, Dr. Bu has significantly contributed to the fields of geodesy and surveying engineering through his extensive publications and active involvement in the scientific community.

Profile

Google Scholar

 

Strengths for the Award

  1. Strong Academic Background: Jinwei Bu has a solid educational foundation in surveying and mapping engineering, geodesy, and surveying engineering, which are crucial for research impacting communities through environmental and spatial informatics.
  2. Extensive Research Experience: With over 50 refereed journal articles authored or coauthored, Dr. Bu has made significant contributions to his field. His publications indicate a robust research portfolio.
  3. International Collaboration: His experience as a Visiting Ph.D. Student at the Universitat Politècnica de Catalunya (UPC) in Spain highlights his international research exposure and collaboration.
  4. Leadership in Academia: Currently serving as a Master Supervisor at Kunming University of Science and Technology, Dr. Bu is in a position to mentor the next generation of researchers, amplifying his impact on the community.
  5. Reviewer for Prestigious Journals: Serving as a reviewer for over 10 international journals underscores his expertise and recognition in the academic community.
  6. Research Interests with Community Impact: His focus on Global Navigation Satellite Systems (GNSS) reflectometry, atmospheric remote sensing, precision positioning, and machine/deep learning has direct applications in improving navigation, environmental monitoring, and disaster management, all of which have significant community impacts.

Areas for Improvement

  1. Direct Community Engagement: While his research has potential community impact, there could be more direct evidence of engagement with community projects or initiatives that translate his research into tangible community benefits.
  2. Interdisciplinary Collaborations: Increasing collaborations with experts from other fields such as public health, urban planning, and environmental science could broaden the application of his research and enhance its community impact.
  3. Public Outreach and Education: Engaging in more public outreach, workshops, and educational programs to disseminate his research findings to a broader audience, including policymakers and community leaders, could increase the practical application and visibility of his work.

🎓 Education:

Dr. Jinwei Bu received his B.S. degree in Surveying and Mapping Engineering (2016) and his M.S. degree in Geodesy and Surveying Engineering (2018) from Kunming University of Science and Technology, Kunming, China. He earned his Ph.D. degree in Geodesy and Surveying Engineering from the School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China, in 2022.

💼 Experience:

Dr. Bu has held various academic positions, including a Visiting Ph.D. Student role at the Department of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, from November 2021 to November 2022. Currently, he is serving as a Master Supervisor with the Faculty of Land Resource Engineering at Kunming University of Science and Technology. He has authored or coauthored over 50 refereed journal articles and serves as a reviewer for more than 10 international journals.

🔬 Research Interests:

Dr. Jinwei Bu’s research interests include Global Navigation Satellite Systems (GNSS) reflectometry, GNSS atmospheric remote sensing, GNSS precision positioning, and the application of machine/deep learning techniques in these areas. He is particularly focused on developing and testing models for sea surface wind speed estimation with GNSS-R delay Doppler maps and delay waveforms.

🏆 Awards:

Dr. Bu’s excellence in research and contributions to the field have earned him recognition and accolades within the scientific community, underscoring his commitment and impact in geodesy and surveying engineering.

Publications

  1. An indoor Wi-Fi localization algorithm using ranging model constructed with transformed RSSI and BP neural network – IEEE Transactions on Communications, 2022. Cited by: 29
    • Prompt: An innovative approach to indoor Wi-Fi localization using RSSI and neural networks.
  2. Developing and testing models for sea surface wind speed estimation with GNSS-R delay Doppler maps and delay waveforms – Remote Sensing, 2020. Cited by: 25
    • Prompt: Breakthrough in sea surface wind speed estimation using GNSS-R technology.
  3. Multi-classification of UWB signal propagation channels based on one-dimensional wavelet packet analysis and CNN – IEEE Transactions on Vehicular Technology, 2022. Cited by: 23
    • Prompt: Cutting-edge multi-classification of UWB signals utilizing wavelet analysis and CNN.
  4. Performance assessment of positioning based on multi-frequency multi-GNSS observations: signal quality, PPP, and baseline solution – IEEE Access, 2020. Cited by: 20
    • Prompt: Comprehensive evaluation of multi-GNSS positioning performance and solutions.
  5. Sea surface rainfall detection and intensity retrieval based on GNSS-reflectometry data from the CYGNSS mission – Publication details pending.
    • Prompt: Novel methodology for sea surface rainfall detection and intensity estimation using GNSS-reflectometry.

Meikang Qiu | Cloud Computing | Best Researcher Award

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Prof Dr. Meikang Qiu | Cloud Computing | Best Researcher Award

Professor, Augusta University,United States

📚 Dr. Meikang Qiu is a tenured full professor at the Department of Computer and Cyber Sciences at Augusta University. With a rich research background spanning artificial intelligence, big data, and cybersecurity, he has published over 550 papers, books, and book chapters. His work has garnered more than 25,400 citations, reflecting his significant impact on the field. As an ACM Distinguished Member and IEEE Distinguished Visitor, Dr. Qiu has supervised 12 Ph.D. students and 2 postdoctoral researchers, contributing extensively to both academia and industry.

Profile

Strengths for the Award

  1. Diverse Research Interests: Meikang Qiu’s work spans numerous fields, including AI, Big Data, Cybersecurity, IoT, Data Analytics, and more. This interdisciplinary approach can significantly impact various community sectors.
  2. High Citation Metrics: With over 25,400 citations and an H-index of 106, Qiu’s work has a proven broad impact, demonstrating significant influence in the academic community.
  3. Extensive Publications: He has authored over 550 papers/books/book chapters, showcasing a prolific output that contributes to the knowledge base in his fields of expertise.
  4. Recognition and Awards: His numerous accolades, including the IEEE Systems Journal Best Paper Award and the IEEE Big Data Security STC Founder and Pioneer Award, underline his excellence and contributions to research.
  5. Community and Educational Involvement: Qiu’s involvement in workshops and seminars, such as the GenCyber Cybersecurity Workshop for High School Teachers, highlights his commitment to community education and outreach.
  6. Leadership and Mentorship: Supervision of 12 Ph.D. students and 2 postdocs, along with significant roles in professional services (e.g., General Chair of IEEE conferences), indicates his leadership and mentorship capabilities, contributing to the academic and professional growth of others.
  7. Industrial and Practical Experience: His experience working in high-tech companies and collaborations with industry giants like Google and Amazon ensures that his research has practical applications and relevance to real-world problems.

Areas for Improvement

  1. Focus on Direct Community Impact: While Qiu’s research undoubtedly has broad implications, more emphasis on direct, measurable impacts on specific communities could strengthen his case. Detailed examples of how his work has directly benefited particular communities or societal sectors would be beneficial.
  2. Public Engagement: Increasing efforts in public dissemination of his research findings through popular media or public lectures could enhance the visibility and understanding of his work’s impact on the community.
  3. Collaboration with Community Organizations: Strengthening partnerships with community-based organizations to apply his research findings more directly in local settings could further demonstrate the tangible impact of his work.

Education

🎓 Dr. Meikang Qiu earned his Ph.D. in Computer Science from the University of Texas at Dallas in May 2007. Prior to that, he completed his M.S. in Computer Science with a perfect GPA of 4.0 from the same institution in December 2003. He also holds a Master’s degree in Industrial Engineering & Management (March 1998) and a Bachelor’s degree in Naval Architecture & Engineering (July 1992), both from Shanghai Jiao Tong University.

Experience

💼 Before joining academia, Dr. Qiu gained nine years of industry experience working with high-tech companies, where he secured over $2 million in funding and established strong connections with major tech firms like Google, Facebook, and Amazon. In academia, he has attended more than 20 NSF panels and holds significant roles in various professional organizations.

Research Interests

🔍 Dr. Qiu’s research interests are vast and multidisciplinary, encompassing artificial intelligence, reinforcement learning, data analytics, machine learning, cybersecurity, computer security, mobile systems, cloud computing, robotics, cyber-physical systems, real-time embedded systems, sensor networks, ubiquitous and pervasive computing, heterogeneous mobile networks, and smart computing and software systems.

Awards

🏆 Dr. Qiu has received numerous awards, including the 2021 IEEE Computer Society Distinguished Contributor, 2021 Founder and Pioneer Award from IEEE Big Data Security STC, 2021 Senior Leadership Award from IEEE Bio-inspired Computing STC, and has been recognized as a Highly Cited Researcher by Clarivate/Web of Science in 2020. Additionally, he is an ACM Distinguished Member since 2019 and has received multiple best paper awards.

Publications

  1. 🌟 J. Li, M. Qiu, Z. Ming, G. Quan, X. Qin, Z. Gu, “Online Optimization for Scheduling Preemptable Tasks on IaaS Cloud Systems,” Journal of Parallel and Distributed Computing, Vol. 72, No. 5, pp. 666-677, May 2012.
  2. 🌟 K. Gai, M. Qiu, H. Zhao, L. Tao, Z. Zong, “Dynamic Energy-Aware Cloudlet-based Mobile Cloud Computing Model for Green Computing,” Journal of Network and Computer Applications, Vol. 59, No. 1, pp. 46-54, 2016. (Best Research Paper 2018)
  3. 🌟 M. Qiu, Z. Ming, J. Li, K. Gai, Z. Zong, “Phase-Change Memory Optimization for Green Cloud with Genetic Algorithm,” IEEE Transactions on Computers, Vol. 64, No. 12, pp. 3528-3540, Dec. 2015. (Hot Paper 2017, Highly Cited Paper 2017-2021)
  4. 🌟 Y. Li, W. Dai, Z. Ming, M. Qiu, “Privacy Protection for Preventing Data Over-Collection in Smart City,” IEEE Transactions on Computers, Vol. 65, No. 5, pp. 1339-1350, May 2016. (Highly Cited Paper 2017-2018)
  5. 🌟 X. Gao, M. Qiu, “Energy-Based Learning for Preventing Backdoor Attack,” 15th Intl. Conf. on Knowledge Science, Eng., and Management (KSEM, Springer), Vol. 3, pp. 706-721, Aug. 2022. (Best Student Paper Award)
  6. 🌟 Y. Zeng, H. Qiu, G. Memmi, M. Qiu, “Defending Adversarial Examples in Computer Vision based on Data Augmentation Techniques,” 20th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2020), Oct. 2020. (Best Paper Award)
  7. 🌟 Y. Zhang, M. Qiu, C.-W. Tsai, M. Hassan, A. Alamri, “Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data,” IEEE Systems Journal, Vol. 11, No. 1, pp. 88-95, 2017. (Best Paper Award, Highly Cited Paper 2017-2019)

 

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

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Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.