Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

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Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

Ms. Priyanka Manchegowda | Computer Vision | Amrita Vishwa Vidyapeetham | India

Ms. Priyanka Manchegowda is a results-driven Assistant Professor and researcher, currently pursuing her Ph.D., with over 12 years of combined experience in teaching computer science, academic leadership, and curriculum development. She holds an M.Sc. in Computer Science from Pooja Bhagavat Memorial Mahajana Post Graduate Centre, affiliated with the University of Mysore, Mysuru, India, and has actively contributed to higher education by delivering advanced courses in Exploratory Data Analysis using Python, Digital Image Processing, Design and Analysis of Algorithms, Data Structures, Problem Solving and Programming, Operations Research, Numerical Analysis, Statistical Techniques, Programming in C/C++, and Database Management Systems, consistently achieving strong student satisfaction. Professionally, she has served as an Assistant Professor at SBRR Mahajana First Grade College, Mysuru, from 2013 to 2020, and currently at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus since 2020, where she also contributes as a member of the Board of Studies and has developed curricula in alignment with university standards. In addition to teaching, she has guided Bachelor’s and Master’s students on research projects, focusing her research on computer vision-based human age estimation tailored for Indian medico-legal scenarios, demonstrating expertise in analytical methods, quantitative aptitude, image processing, and programming with Python, C, and C++, alongside database management using MS SQL Server and tools such as MATLAB and Anaconda. Ms. Manchegowda has actively contributed to institutional initiatives and student development, serving as the SWAYAM MOOC Nodal Officer, and as convener for the Rotaract Club and SARANTHA, while also engaging in faculty evaluations for the Internal Quality Assurance Cell (IQAC). She brings strong leadership, teamwork, administrative, and communication skills, alongside a commitment to lifelong learning and academic engagement. Her professional recognition includes citations in Scopus with an h-index reflecting the impact of her scholarly contributions.

Professional Profiles: ORCID | Scopus

Selected Publications

  • Priyanka, M., Divyashree, M., & Madhu, V. (2022). Computer Vision-Based Approach for Estimating Age and Gender using Wrist X-Ray Images.

  • Priyanka, M., Sreekumar, S., & Arsh, S. (2022). Detection of Covid-19 from the Chest X-Ray Images: A Comparison Study between CNN and Resnet-50.

Prof. Zhang Wenli | Computer Vision | Excellence in Research Award

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Prof. Zhang Wenli | Computer Vision | Excellence in Research Award 

Prof. Zhang Wenli | Computer Vision | Beijing University of Technology | China

Dr. Wenli Zhang is a distinguished scholar and innovative technology leader currently serving as a Professor in the Faculty of Information Technology at Beijing University of Technology, recognized for impactful contributions in signal and information processing, artificial intelligence, computer vision, 3D point cloud processing, unmanned aerial vehicle inspection technology, and brain-computer interfaces, positioning Dr. Wenli Zhang as a key figure advancing intelligent sensing and human-machine interaction research in China and globally. Building a strong academic foundation through advanced studies in computer science and informatics in both China and Japan, Dr. Wenli Zhang earned a Ph.D. in Engineering from the University of Tokyo, where a passion for applied research and innovation in intelligent systems was further strengthened. Prior to joining academia in China, Dr. Wenli Zhang developed extensive industrial innovation experience as Chief Researcher at Panasonic Corporation’s Tokyo Research Institute, driving real-world AI and vision-based solutions for next-generation automated applications. In her current role, Dr. Wenli Zhang leads interdisciplinary research that spans multiple sectors including smart agriculture, UAV-based intelligent inspection, and medical rehabilitation, effectively bridging fundamental theories with emerging societal needs and technological transformation. With strong collaboration networks and a commitment to promoting scientific excellence, Dr. Wenli Zhang serves actively in influential professional roles, including council member of the Beijing Interdisciplinary Science Society and committee member of the Innovation Engineering Branch of China Creative Studies Institute, contributing leadership within China’s innovation and engineering communities. Skilled in advanced algorithm development, intelligent visual perception, sensor network data fusion, and neural signal decoding, Dr. Wenli Zhang empowers her research team to develop practical systems that enhance automation, sustainability, and accessibility across industries. Her exceptional commitment to teaching and mentorship has earned her the prestigious “Distinguished Teacher” recognition at Beijing University of Technology, reflecting her dual dedication to academic excellence and student success.

Professional Profiles: ORCID  

Selected Publications:

  • Jiang, K., Guo, W., & Zhang, W. (2025). Amodal Segmentation and Trait Extraction of On-Branch Soybean Pods with a Synthetic Dual-Mask Dataset. Sensors.

  • Zhang, W., Peng, X., Bai, T., Wang, H., Takata, D., & Guo, W. (2024). A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees. Remote Sensing.

  • Zhang, W., Peng, X., Cui, G., Wang, H., Takata, D., & Guo, W. (2023). Tree Branch Skeleton Extraction from Drone-Based Photogrammetric Point Cloud. Drones.

  • Li, Y., Liu, B., & Zhang, W. (2024). Driving-Related Cognitive Abilities Prediction Based on Transformer’s Multimodal Fusion Framework. Sensors.

  • Pang, G., Liu, B., & Zhang, W. (2025). Cloud Rehabilitation System Based on Automatic sEMG Signal Processing. Book Chapter.

  • Zhai, R., Gao, Y., Li, G., Ding, Q., Zhang, Y., & Zhang, W. (2025). Control System for Rehabilitation Bionic Hand Based on Precise Control Algorithms.

  • Wang, Y., Pang, G., Liu, B., Li, Y., & Zhang, W. (2025). Gesture Recognition Method Based on Hybrid Classifier Under Non-ideal Conditions.

Ms. Devinder Kaur | Computer Science | Women Researcher Award

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Ms. Devinder Kaur | Computer Science | Women Researcher Award 

Ms. Devinder Kaur, Mata Gujri College, India

Dr. Devinder Kaur is an experienced academician currently serving as an Assistant Professor in the Department of Computer Applications at Mata Gujri College, Fatehgarh Sahib, with over 20 years of teaching experience. She holds a Bachelor’s degree in Computer Applications from Punjabi University, Patiala, and a Master’s degree in Computer Applications from Punjab Technical University, Jalandhar. She is presently pursuing her Ph.D. in Computer Science at Sri Guru Granth Sahib World University, Fatehgarh Sahib. Dr. Kaur has authored two academic books—A Practical Approach to Java Programming and An Introduction to System Software—and contributed numerous research papers and book chapters in both national and international journals and conference proceedings. Her recent research interests focus on IoT and machine learning applications in livestock health monitoring, cybersecurity, environmental sustainability, and green computing. She has also actively participated in national-level conferences, addressing critical topics like social media addiction, privacy concerns, and e-waste management. Dr. Kaur’s scholarly contributions reflect her dedication to bridging practical technology with real-world challenges in both academic and agricultural domains.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

Summary of Suitability for Women Researcher Award 

Dr. Devinder Kaur is a highly qualified and accomplished academic with over 20 years of teaching experience in Computer Science, currently serving as an Assistant Professor at Mata Gujri College, Fatehgarh Sahib. She holds Bachelor’s and Master’s degrees in Computer Applications and is currently pursuing her Ph.D. in Computer Science from Sri Granth Sahib World University, highlighting her continuous academic advancement.

🎓 Education

  • 🎓 Bachelors of Computer Applications (BCA) from Punjabi University, Patiala.

  • 🎓 Masters of Computer Applications (MCA) from Punjab Technical University, Jalandhar.

  • 📚 Pursuing PhD in Computer Science from Sri Granth Sahib World University, Fatehgarh Sahib.

👩‍🏫 Work Experience

  • 🏫 Assistant Professor at Mata Gujri College, Fatehgarh Sahib.

  • 📅 20 years of teaching experience in the field of Computer Science.

🏆 Achievements, Awards & Honors

  • 📖 Published Books:

    • “A Practical Approach to Java Programming” – 📘 Unistar Books Pvt Ltd (2018)

    • “An Introduction to System Software” – 📗 Narosa Publishing House (2020)

  • 📝 Research Contributions:

    • 📚 Multiple book chapters and conference papers on topics such as:

      • Green Computing 🌱

      • Social Media Psychology 📱

      • E-Waste Management ♻️

      • IoT and Machine Learning in Livestock Health 🐄💡

      • Breast Cancer Classification Using ML 🎗️🧠

  • 🔗 Featured in IEEE, Auerbach Publications, and peer-reviewed journals like Discover Internet of Things, IJIRAE, Journal of Electrical Systems.

  • 🌐 Contributed to multidisciplinary and international conferences on smart tech, computing trends, and innovative research in AI & IoT.

Publication Top Notes:

CITED:409
CITED:135
CITED:118
CITED:102
CITED:97
CITED:87
CITED:81

Prof. Yanlong Tai | Machine Learning | Best Researcher Award

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Prof. Yanlong Tai | Machine Learning | Best Researcher Award

Prof. Yanlong Tai, shenzhen institute of science and technology, China academic of science, China

Prof. Dr. Yanlong Tai is a distinguished researcher and professor in the field of smart sensing and flexible electronics. He is the Principal Investigator of the Smart-Sensing-Lab (SM-SE Lab.-SIAT) and serves as the Head of both the SIAT-UAEU International Smart Sensing & Energy Joint Lab and the SIAT-Fudan University (Zhuhai) Joint Innovation Center. Currently, he is a Full Professor at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), China, and a Joint Professor at the University of Science & Technology Shenzhen. Dr. Tai earned his Ph.D. from Fudan University, China (2009-2012), and was a visiting student at OHM University, Germany (2011-2012). He also holds Bachelor’s and Master’s degrees from Anhui University (2001-2008). His professional journey includes extensive research experience across multiple international institutions. He served as a Postdoctoral Researcher at University of California, Davis, USA (2012-2013), Fraunhofer ENAS, Chemnitz, Germany (2013-2014), and KAUST, Saudi Arabia (2014-2017). He later worked as a Research Scientist at Masdar Institute, UAE (2017-2019) before joining SIAT as a Professor in 2019.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Prof. Dr. Yanlong Tai

Prof. Dr. Yanlong Tai is an outstanding researcher and innovator, making him a highly suitable candidate for the Best Researcher Award. His extensive experience, leadership roles, and impactful research in smart materials, energy harvesting, and wearable electronics position him as a global leader in advanced sensing technologies.

🎓 Education

  • Ph.D. (2009 – 2012) – Fudan University, China

  • Visiting Student (2011 – 2012) – OHM University, Germany

  • Bachelor & Master Degree (2001 – 2008) – Anhui University, China

💼 Work Experience

  • Professor (2019 – Present) – Shenzhen Institutes of Advanced Technology (SIAT), CAS, China

  • Research Scientist (2017 – 2019) – Masdar Institute, United Arab Emirates

  • Postdoc Researcher (2014 – 2017) – King Abdullah University of Science and Technology (KAUST), Saudi Arabia

  • Postdoc Researcher (2013 – 2014) – Fraunhofer ENAS, Chemnitz, Germany

  • Postdoc Researcher (2012 – 2013) – University of California, Davis, USA

🏆 Achievements, Awards & Honors

  • 📌 Principal Investigator of Smart-Sensing-Lab (SM-SE Lab.-SIAT)

  • 🏅 Head of SIAT-UAEU International Smart Sensing & Energy Joint Lab

  • 🏅 Head of SIAT-Fudan University (Zhuhai) Joint Innovation Center

  • 🎖️ Full Professor at SIAT, CAS, Shenzhen, China

  • 🎖️ Joint Professor at the University of Science & Technology, Shenzhen

Publication Top Notes:

CITED:663
CITED:154
CITED:152
CITED:142
CITED:92
CITED:78

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

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Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award 

Mr. Mohammed Aljamal, University of Bridgeport, United States

Mohammed Aljamal is a Laboratory Engineer and Ph.D. candidate in Computer Science & Engineering, based in the New York City Metropolitan Area. He holds a Master’s degree in Artificial Intelligence from the University of Bridgeport and is actively engaged in academic and professional communities as the President of the UB Robotics Club and a member of AIAA, UPE, and the Honor Society. With over four years of experience at the University of Bridgeport, he has contributed as a Laboratory Engineer, Graduate Research Assistant, and Teaching Assistant, specializing in laboratory management, hardware and software solutions, and IT infrastructure. His expertise spans project leadership, problem-solving, cross-functional team management, and innovative solution design. Beyond academia, Mohammed has a strong background in consulting, resource allocation, and international collaboration, having successfully led and completed critical projects. Passionate about technology and innovation, he continuously seeks opportunities to develop solutions that enhance user experiences and drive technological advancement.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Mohammed Aljamal for the Best Researcher Award

Mohammed Aljamal is a highly skilled and innovative researcher with a strong background in Artificial Intelligence, Computer Science, and Engineering. His Ph.D. candidacy, extensive teaching experience, and leadership roles at the University of Bridgeport demonstrate his dedication to academic excellence and technological advancements.

Education 🎓

  • Ph.D. Candidate in Computer Science & Engineering – University of Bridgeport (Ongoing)
  • Master’s Degree in Artificial Intelligence – University of Bridgeport
  • Bachelor’s Degree in [Field Not Specified] – [University Not Specified]

Work Experience 💼

University of Bridgeport (4 years 1 month)

  • Labs Engineer (Feb 2022 – Present) ⚙️

    • Improved and maintained laboratory equipment.
    • Developed detailed hardware and software data for lab management.
    • Conducted inspections and routine maintenance on lab equipment.
    • Implemented new technology solutions and disaster recovery plans.
    • Coordinated IT services to ensure data availability and security.

  • Graduate Research & Teaching Assistant (Jan 2022 – Feb 2022) 📚

    • Assisted in research projects and student instruction.

  • Teaching and Laboratory Assistant (Feb 2021 – Dec 2021) 🏫

    • Assisted undergraduate and graduate students in Intro to Robotics.
    • Managed lab hours, discussions, assignments, and exams.

Achievements & Leadership 🌟

  • President of UB Robotics Club 🤖 – Leading robotics initiatives and student projects.
  • Successfully completed two delayed projects 🎯 – Resolved critical issues and met client satisfaction.
  • Consulted and collaborated with international vendors 🌍 – Gained experience in global tech solutions.
  • Designed and implemented innovative lab solutions 🔧 – Optimized university lab resources.

Awards & Honors 🏆

  • Member of AIAA (American Institute of Aeronautics and Astronautics) 🚀
  • Member of UPE (Upsilon Pi Epsilon – International Honor Society for Computing) 🖥️
  • Honor Society Member 🎖️

Publication Top Notes:

 

 

Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award

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Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award 

Mr. Shiraz Kaderuppan, Newcastle University, Singapore

Shiraz is a Singaporean educator and data analytics enthusiast with extensive experience in enhancing deep neural network (DNN) architectures for feature recognition and extraction in image processing applications. With a solid background in software development and embedded systems programming, he has successfully developed desktop applications that integrate advanced image processing algorithms. Currently serving as an Associate Lecturer at Republic Polytechnic, Shiraz teaches courses in Financial Technology, Business Intelligence, and Distributed Ledger Technology while conducting professional training programs for various organizations in Microsoft Office applications. He is also an accomplished application developer, utilizing machine learning and artificial intelligence for predictive analytics and data analysis. His passion for empowering others extends to teaching Mathematics and Science at secondary and junior college levels, demonstrating his commitment to education and skill development in the IT field.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: 

Shiraz S/O Kaderuppan stands out as a highly suitable candidate for the Best Researcher Award due to his extensive experience and impressive contributions to the field of data analytics and deep learning, particularly in image processing applications. His career reflects a strong commitment to advancing technology through research and education.

Education 🎓

  • Republic Polytechnic
    Diploma in Financial Technology, Business Intelligence & Distributed Ledger Technology
    Mar 2023 – Present

Work Experience 💼

  • Associate Lecturer
    Republic Polytechnic
    Mar 2023 – Present

    • Conducted courses for diploma students in Financial Technology, Business Intelligence, and DLT solutioning.
  • Corporate Trainer
    Self-Employed
    Jul 2014 – Present

    • Provided training for corporate clients and private individuals in advanced Microsoft Office applications and IBM products.
  • Application Developer
    Self-Employed
    May 2012 – Present

    • Developed desktop applications using C# .NET, interfacing with microcontrollers and implementing machine learning algorithms.
  • ML/AI Developer
    Self-Employed
    Sep 2008 – Present

    • Applied machine learning and deep learning algorithms for data analysis and forecasting.
  • Educator
    Self-Employed
    Aug 2010 – Present

    • Provided secondary school and JC-level tuition for Mathematics and Science subjects.
  • General Education Officer (Teacher)
    Ministry of Education
    Sep 2007 – Jan 2009

    • Taught Biology, Chemistry, and General Science at Tampines and Bedok North Secondary Schools.
  • Founder & Business Development Manager
    Self-Employed
    Jan 2005 – Jun 2007

    • Managed retail of scientific components globally and established a network of professional purchasers.

Achievements 🌟

  • Successfully conducted numerous training programs for companies and government bodies, focusing on advanced features of Microsoft Office for business intelligence and data analysis.
  • Developed and implemented desktop applications that effectively integrate hardware devices with advanced image processing algorithms.
  • Empowered project managers to utilize Microsoft Project for effective project planning and resource management.

Awards & Honors 🏆

  • Recognized for excellence in teaching and training methodologies at Republic Polytechnic and in corporate training programs.
  • Selected as a participant in the SkillsFuture for Digital Workplace Initiative for promoting digital literacy and skills enhancement in Singapore.

Publication Top Notes:

Θ-Net: A Deep Neural Network Architecture for the Resolution Enhancement of Phase-Modulated Optical Micrographs In Silico

O-Net: A Fast and Precise Deep-Learning Architecture for Computational Super-Resolved Phase-Modulated Optical Microscopy

Smart Nanoscopy: A Review of Computational Approaches to Achieve Super-Resolved Optical Microscopy

Kanika | Machine Learning | Best Researcher Award

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Kanika | Machine Learning | Best Researcher Award

Ms. Kanika, National institute of technology Agartala, India.

Ms. Kanika, hailing from Hasanpur, Haryana, is an enthusiastic researcher with a strong passion for applied mathematics 🧮 and advanced computing technologies 💻. Her expertise spans optimization, uncertainty theory, numerical analysis, graph theory, artificial intelligence 🤖, and machine learning. With an M.Sc. in Mathematics and Computing 🎓 from NIT Agartala, where she ranked 6th, and a B.Sc. in Mathematics, Physics, and Computer Science 🎓 from Banasthali Vidyapith, she has consistently demonstrated academic excellence. Kanika is driven to solve real-life problems 🌍 through mathematics and is currently working on a machine-learning research paper while aspiring to contribute to computational imaging and AI.

Publication Profiles 

Googlescholar

Education and Experience

Education 🎓
  • M.Sc. in Mathematics and Computing (2021–2023), NIT Agartala: 89.5%, 8.95/10, Rank: 6️⃣
  • B.Sc. in Mathematics, Physics, and Computer Science (2017–2020), Banasthali Vidyapith: 85.8%, 8.58/10 🧮
  • Senior Secondary Examination (2016–2017), Board of School Education Haryana: 85.0% 🧑‍🎓
  • Secondary Examination (2014–2015), Board of School Education Haryana: 91.4% 🌟
Experience 🧑‍🔬
  • M.Sc. Thesis (2022–2023) at NIT Agartala: Focused on portfolio optimization under uncertainty 🌐.

Suitability For The Award

Ms. Kanika is an exceptional candidate for the Best Researcher Award, showcasing a strong academic foundation, innovative research contributions, and a deep commitment to advancing applied mathematics, machine learning, and artificial intelligence. Her dedication to leveraging mathematical and computational tools for solving real-world problems highlights her potential to make a significant impact in her field.

Professional Development

Kanika’s professional journey showcases her dedication to research and continuous learning 📚. She has gained expertise in machine learning 🤖, MATLAB 🧪, and scientific computing 🖥️. Her technical skills extend to programming languages like C/C++ and database management systems 💾. As a mathematics enthusiast, she has completed rigorous training programs like the Mathematics Training and Talent Research (MTTS) and the National Mathematics Talent Contest 🏅. She actively participates in workshops and online programs, enhancing her skills in cutting-edge mathematical technologies 🌟. Kanika is also a certified karateka 🥋, showcasing her versatile interests beyond academics.

Research Focus

Ms. Kanika’s research interests lie at the intersection of applied mathematics and emerging technologies 🌐. Her focus areas include optimization 📈, uncertainty theory, numerical analysis, graph theory, machine learning 🤖, and artificial intelligence. She aims to bridge theoretical mathematics with practical computing applications 💻, contributing to fields like computational imaging and decision-making under uncertainty. Currently working on a machine-learning research paper 📝, Kanika aspires to tackle real-life problems 🌍 using her expertise in applied mathematics and AI. Her passion for solving complex problems drives her to explore innovative solutions in these interdisciplinary domains.

Awards and Honors

  • IIT JAM 2021 🎓: All India Rank 2169 (Mathematical Sciences).
  • MTTS Level 1 🏅: Selected in the top 20 students, IISER Thiruvananthapuram (2020).
  • Banaras Hindu University Entrance Exam 🎓: All India Rank 363 (Mathematical Sciences, 2020).
  • Common Entrance Exam (CEE) by NCERT 🏆: State Rank 63 (General), NCERT (2017).
  • National Mathematics Talent Contest 🥇: Top 10%ile, Junior Level Screening Test, AMTI (2014).
  • Certified Karateka 🥋: 8th, 7th, and 6th Kyu (Blue Belt), JKMO (2018).
  • Olympic Value Education Program Ambassador 🏅: Honored by Banasthali Vidyapith (2017).

Publication Top Notes 

  • 📚 Tools and techniques for teaching computer programming: A review – Journal of Educational Technology Systems, 2020, Cited by: 88
  • 🤝 Effect of different grouping arrangements on students’ achievement in collaborative learning – Interactive Learning Environments, 2023, Cited by: 12
  • 🧬 Genetic algorithm‐based approach for making pairs and assigning exercises in programming – Computer Applications in Engineering Education, 2020, Cited by: 8
  • 📖 Enriching WordNet with subject-specific out-of-vocabulary terms using ontology – Data Engineering for Smart Systems, 2022, Cited by: 6
  • 🎓 KELDEC: A recommendation system for extending classroom learning with visual cues – Proceedings of SSIC, 2019, Cited by: 6
  • 🎯 VISTA: A teaching aid to enhance contextual teaching – Computer Applications in Engineering Education, 2021, Cited by: 3
  • 🌐 Linking classroom studies with dynamic environment – International Conference on Computing, Power and Communication, 2019, Cited by: 2
  • 🔄 Effect of varying the size of the initial parent pool in genetic algorithm – International Conference on Contemporary Computing and Informatics, 2014, Cited by: 2
  • 🌍 A review of English to Indian language translator: Anusaaraka – International Conference on Advances in Computer Engineering & Applications, 2014, Cited by: 2

Masoud DANESHTALAB | deep learning | Best Researcher Award

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Prof. Masoud DANESHTALAB | deep learning | Best Researcher Award 

Prof. Masoud DANESHTALAB, Mälardalen University, Sweden.

Masoud Daneshtalab, Ph.D., Docent, Full Professor
Masoud Daneshtalab is a globally recognized scholar and Full Professor at Mälardalen University (MDU), Sweden. With over two decades of academic and professional excellence, he has made significant contributions to computer science and engineering, specializing in dependable systems, AI, and hardware/software co-design. A prolific researcher with an H-index of 35 and over 5,100 citations, Dr. Daneshtalab is included in the prestigious World’s Top 2% Scientists Ranking. He serves as the Scientific Director of Fundamental AI at MDU and collaborates internationally, holding adjunct professorships and contributing to cutting-edge research initiatives.

Professional Profile:

Google Scholar

Suitability of Masoud Daneshtalab for the Best Researcher Award

Dr. Masoud Daneshtalab is a highly suitable candidate for the “Research for Best Researcher Award,” based on his exceptional academic achievements and professional contributions. Here are the key reasons

Education

🎓 Academic Journey

  • Docent (2018): Qualified in Computer Science and Electronics, Mälardalen University, Sweden.
  • Ph.D. (2008–2011): Information and Communication Technology, University of Turku, Finland. Dissertation: Adaptive Implementation of On-Chip Networks under Prof. Hannu Tenhunen.
  • M.Sc. (2004–2006): Computer Engineering, University of Tehran, Iran. Thesis: Low Power Methods in Network-on-Chips under Prof. Ali Afzali-Kusha.
  • B.Sc. (1998–2002): Computer Engineering, Shahid Bahonar University of Kerman, Iran.

Experience

💼 Professional Contributions

  • Scientific Director (2024–Present): Fundamental AI, Mälardalen University, Sweden.
  • Full Professor (2020–Present): Innovation, Design & Engineering, MDU.
  • Adjunct Professor (2019–Present): Computer Systems, Tallinn University of Technology, Estonia.
  • Previous Roles: Associate Professor at MDU (2016–2020), EU Marie Curie Fellow at KTH Royal Institute of Technology (2014–2016), Lecturer at the University of Turku (2011–2014), and Researcher at the University of Tehran (2006–2008).

Research Interests

🔬 Key Areas

  • Optimization and robustness in deep learning models.
  • HW/SW co-design and heterogeneous computing.
  • Dependable systems, memory architectures, and interconnection networks.
  • Cutting-edge projects include sustainable AI, federated learning, and reliable autonomous systems.

Awards

🏆 Recognitions

  • Best Paper Awards: IEEE ECBS (2019), IEEE MCSoC (2018), and multiple HiPEAC Paper Awards (2013–2017).
  • Research Grants: Marie Skłodowska-Curie Fellowship (2014), Nokia Foundation (2009), and others.
  • Top Reviewer: IEEE Transactions on Computers (2013).
  • Fellowships: GETA, Helsinki University of Technology (2008–2011).

Publications

A review on deep learning methods for ECG arrhythmia classification

CITIED: 490

Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities

CITIED: 147

Routing algorithms in networks-on-chip

CITIED: 136

Smart hill climbing for agile dynamic mapping in many-core systems

CITIED: 125

EDXY–A low cost congestion-aware routing algorithm for network-on-chips

CITIED: 124

Deep Maker: A multi-objective optimization framework for deep neural networks in embedded systems

CITIED: 122

 

Ms. Congying Sun | Object Detection Awards | Best Researcher Award

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Ms. Congying Sun | Object Detection Awards | Best Researcher Award 

Ms. Congying Sun, Xi’an University of Technology, China

Congying Sun, a native of Xianyang City, Shaanxi Province, is an emerging researcher specializing in control science, engineering, and multi-modal remote sensing technologies. She earned her Bachelor’s degree in Printing Engineering from Xi’an University of Technology in 2022 and is currently pursuing a Master’s degree in Control Science and Engineering at the same institution, expected to graduate in 2025. Her professional experience includes a tenure at the Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, where she played a pivotal role in developing an infrared-visible aircraft image dataset and deploying state-of-the-art infrared small target detection models. Congying has demonstrated her ability to merge academic excellence with practical application through her contributions to national and engineering projects, including research on multi-source collaborative intelligent perception technology for aircraft and non-cooperative multi-target classification and cognition technology.

Professional Profile:

ORCID

Suitability of Congying Sun for the Best Researcher Award

Congying Sun demonstrates exceptional qualifications and accomplishments, making her an outstanding candidate for the Research for Best Researcher Award. Below is a summary of her key achievements and strengths

🎓 Education

  • Master’s Degree in Control Science and Engineering (August 2022 – July 2025)
    🏫 Xi’an University of Technology
  • Bachelor’s Degree in Printing Engineering (September 2018 – July 2022)
    🏫 Xi’an University of Technology

🧑‍💻 Professional Experience

Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (July 2023 – August 2024)

  • 📸 Independently created an infrared-visible aircraft image dataset, including camera selection, data collection, and image annotation.
  • 📝 Authored project proposals, research papers, and patents with great precision.
  • 🤖 Developed and deployed infrared small target detection models and multi-modal remote sensing image fusion detection models.

🚀 Research Projects

  • Multi-source Collaborative Intelligent Perception Technology for Aircraft (August 2023 – June 2024) ✈️
  • Non-cooperative Multi-target Classification and Cognition Technology (October 2023 – March 2024) 🎯

🏅 Achievements

  • Granted Invention Patents:
    • 📜 Infrared Small Target Detection Method (CN118762159A)
    • 📜 Multi-modal Feature Fusion Target Detection Model and Method (CN118865046A)

💡 Research Interests

🔍 Machine Learning | 🌍 Multi-modal Remote Sensing | 🎯 Target Detection

Congying Sun’s innovative approach, technical expertise, and impactful contributions to cutting-edge research make her a rising star in the field of control science and engineering. 🌟

Publication Top Notes:

Location-Guided Dense Nested Attention Network for Infrared Small Target Detection

MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images

Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher Award

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Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher Award  

Prof. Yuguo Yu, Fudan University, China

Yuguo Yu, Ph.D., is a distinguished professor in Brain-inspired Artificial Intelligence and Computational Neuroscience at Fudan University, where he has been a faculty member since 2011. He currently serves as a professor at both the Research Institute of Intelligent Complex Systems and the National Key Laboratory of Medical Neurobiology. Yu obtained his Bachelor’s degree in Physics from Lanzhou University in 1995 and completed his Ph.D. in Condensed Matter Physics at Nanjing University in 2001. He pursued postdoctoral training in Computational/Behavior Neuroscience at Carnegie Mellon University from 2001 to 2004 and was an Associate Research Scientist at Yale University from 2005 to 2011, where he continues to contribute as a visiting Research Scientist since 2021. Yu has been recognized for his academic excellence through prestigious awards, including the Shanghai Eastern Scholar Professorship in 2013 and the Shanghai Excellent Academic Leader award in 2021. He is an active member of the Chinese Society of Computational Neuroscience and serves as an associate editor for several prominent journals, including IEEE Transactions on Cognitive and Developmental Systems and Frontiers in Computational Neuroscience. His research interests encompass brain-inspired neural networks, cellular mechanisms of energy-efficient cortical dynamics, synaptic learning mechanisms, and large-scale cortical network modeling, with over 100 publications in leading journals such as Nature and Neuron. Yu has also led or participated in numerous national foundation projects, advancing the field of computational neuroscience.

Professional Profile:

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Research for Best Researcher Award

Candidate Overview: Dr. Yuguo Yu is a prominent researcher and professor in Brain-inspired artificial intelligence and computational neuroscience at Fudan University. With extensive academic and research experience, he is a strong candidate for the Best Researcher Award due to his significant contributions to the field, impactful publications, and leadership roles.

Education

  • B.Sc. in Physics
    Lanzhou University, 1995
  • Ph.D. in Condensed Matter Physics
    Nanjing University, 2001
  • Postdoctoral Researcher in Computational Neuroscience
    Carnegie Mellon University, 2001–2004
  • Research Scientist in Neurobiology
    Yale University, 2005–2011

Work Experience

  • Professor
    Research Institute of Intelligent Complex Systems, Fudan University, 2020–Present
  • Professor
    National Key Laboratory of Medical Neurobiology, Fudan University, 2013–Present
  • Visiting Research Scientist
    Yale University School of Medicine, 2021–Present
  • Associate Research Scientist
    Department of Neuroscience, Yale University, 2005–2011

Research Interests:

  • Brain-inspired Intelligence and Computational Neuroscience
  • Neural Computation Model
  • Neural Coding Theory
  • Network Topology Analysis
  • Sensory Fusion Mechanism
  • Brain Connectome Atlas
  • Self-organizing Learning Algorithm
  • Multi-sensory Fusion Model
  • Low-power Mechanism of the Human Brain 🔍

Publication Top Notes

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