Prof. Jiantao Shi | Information Technology | Best Researcher Award

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Prof. Jiantao Shi | Information Technology | Best Researcher Award

Prof. Jiantao Shi, Njing Tech University, China

Prof. Jiantao Shi is a distinguished researcher in control science and information technology, currently serving as a Professor at Nanjing Tech University. He holds a Ph.D. in Control Science and Engineering from Tsinghua University and has extensive experience in multi-robot cooperative control, fault diagnosis, and UAV learning control. His research has been published in leading IEEE journals, and he has significantly contributed to distributed system reliability. With a strong academic background and practical research experience, he has advanced intelligent control methodologies for autonomous systems. His contributions have positioned him as a leader in modern automation and robotics.

🌍 Professional Profile:

ORCID

🏆 Suitability for Best Researcher Award 

Prof. Jiantao Shi is an outstanding candidate for the Best Researcher Award due to his pioneering contributions to intelligent control systems, multi-robot cooperation, and UAV learning control. His work integrates cutting-edge AI techniques with control science, enabling the development of robust and fault-tolerant autonomous systems. With over 60 high-impact journal and conference papers in prestigious IEEE and SCI-indexed publications, he has made fundamental advances in the field. His leadership in both academic and applied research underscores his influence on the next generation of intelligent automation technologies. His innovative solutions make him highly deserving of this recognition.

🎓 Education

Prof. Jiantao Shi obtained his Bachelor’s degree in Electrical Engineering and Automation from Beijing Institute of Technology in 2011. He then pursued a Ph.D. in Control Science and Engineering at Tsinghua University, earning his doctorate in 2016. His academic journey at these top institutions equipped him with expertise in control systems, automation, and intelligent sensing technologies. His doctoral research focused on advanced fault diagnosis and cooperative control of multi-agent systems. This solid educational foundation has propelled him to the forefront of intelligent control and automation, enabling him to address complex challenges in distributed autonomous systems.

💼 Work Experience

Prof. Jiantao Shi has an extensive research career spanning academia and industry. From 2016 to 2018, he worked as an Associate Research Fellow at the Nanjing Research Institute of Electronic Technology, specializing in intelligent sensing. He was promoted to Research Fellow in 2019, leading projects in autonomous systems and fault-tolerant control. Since 2021, he has been a Professor at Nanjing Tech University, where he mentors students and advances research in AI-driven control methodologies. His experience in both applied research and academia allows him to bridge theoretical advancements with real-world applications in robotics, UAVs, and industrial automation.

🏅 Awards & Honors

Prof. Jiantao Shi has received several prestigious awards recognizing his contributions to control science and automation. His research has been featured in top-tier IEEE Transactions journals, demonstrating its high impact. He has been honored with multiple best paper awards at international conferences. Additionally, his work on UAV control and multi-robot systems has been acknowledged with research grants and government funding for innovation in automation. As a key contributor to cutting-edge intelligent control systems, he continues to earn accolades for his groundbreaking contributions, positioning himself as a leading researcher in distributed autonomous system control.

🔬 Research Focus

Prof. Jiantao Shi’s research centers on advanced control methodologies for intelligent automation. His key areas of expertise include cooperative control of multi-robot systems, fault diagnosis and fault-tolerant control of distributed systems, and learning-based control of UAVs. His work integrates AI and machine learning with traditional control science to enhance system resilience and autonomy. By developing robust, intelligent algorithms, he aims to improve automation reliability in real-world applications. His research has profound implications for robotics, autonomous vehicles, and industrial automation, paving the way for next-generation intelligent systems with enhanced adaptability, efficiency, and fault resilience.

📖 Publication Top Notes 

  1. A Parallel Weighted ADTC-Transformer Framework with FUnet Fusion and KAN for Improved Lithium-Ion Battery SOH Prediction
    • Publication Year: 2025
  2. Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph
    • Publication Year: 2025
  3. Iterative Learning-Based Fault Estimation for Stochastic Systems with Variable Pass Lengths and Data Dropouts
    • Publication Year: 2025
  1. A Two-Stage Fault Diagnosis Method with Rough and Fine Classifiers for Phased Array Radar Transceivers
    • Publication Year: 2024
  2. An Intuitively-Derived Decoupling and Calibration Model to the Multi-Axis Force Sensor Using Polynomials Basis
    • Publication Year: 2024
  3. Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots with Communication Limits
    • Publication Year: 2024

 

Pandaba Pradhan | Cloud Computing | Best Researcher Award

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Pandaba Pradhan | Cloud Computing | Best Researcher Award

Dr. Pandaba Pradhan, BJB Auto College, Bhubaneswar, India.

Publication profile

Googlescholar

Education 🎓

  • 🏫 HSC: Board of Secondary Education, Odisha (1st Division)
  • 📘 +2 Science: Ravenshaw College, CHSE, Odisha (1st Division)
  • 💻 B.E.: BPUT, Rourkela (1st Division)
  • 🖥️ M.Tech: BPUT, Rourkela (1st Division)
  • 📜 Ph.D.: Utkal University, Odisha (Resource Management in Cloud Computing, Awarded 2021)

Experience 👩‍🏫

  • Over 16 years of teaching experience at UG and PG levels
  • Specialized in Cloud Computing, Compiler Design, and Computer Architecture

Suitability For The Award

Dr. Pandaba Pradhan is a seasoned academic and researcher with over 16 years of teaching and research experience in computer science, specializing in cloud computing, compiler design, and computer architecture. His contributions to the field, demonstrated by his scholarly output and technical expertise, make him a strong candidate for the Best Researcher Award.

Professional Development 

Dr. Pandaba Pradhan has continuously enriched his professional journey through substantial academic and research contributions. He has published over 20 scholarly articles in reputed national and international journals 📄, secured a patent for innovative research 🔍, and edited a significant academic book 📘. His expertise spans diverse domains, including digital logic, operating systems, and advanced software engineering. Beyond academia, Dr. Pradhan is a mentor to emerging scholars and a catalyst for research in cloud computing ☁️. He remains dedicated to staying ahead in the fast-evolving tech landscape, bridging the gap between theoretical knowledge and practical applications. 🚀💡

Research Focus 

Awards and Honors

  • 🏅 Merit-Based Scholarship: For outstanding academic performance during M.Sc. at COMSATS University.
  • 🏆 Best Research Poster Award: Recognized at a national mathematics conference for innovative work on PDE applications.
  • 🎖️ Distinction in FSc: Achieved top honors in Federal Board examinations.
  • 🌟 Programming Excellence Certificate: Awarded for proficiency in Python and C++ during Ph.D. coursework.
  • 📜 Recognition of Contribution: For active participation in research collaboration projects at International Islamic University Islamabad.

Publoication Top Notes

  • Integrated Artificial Intelligence and Non-Similar Analysis for Forced Convection of Radially Magnetized Ternary Hybrid Nanofluid of Carreau-Yasuda Fluid Model Over a Curved Stretching Surface (2024) 🧠
  • Advanced Intelligent Computing ANN for Momentum, Thermal, and Concentration Boundary Layers in Plasma Electro Hydrodynamics Burgers Fluid (2024) – Cited by: 0 🤖
  • Analysis of Nonlinear Complex Heat Transfer MHD Flow of Jeffrey Nanofluid Over an Exponentially Stretching Sheet via Three Phase Artificial Intelligence and Machine Learning Techniques (2024) 🔥
  • Modeling and Predicting Heat Transfer Performance in Bioconvection Flow Around a Circular Cylinder Using an Artificial Neural Network Approach (2024) 🌡️
  • Advanced Computational Framework to Analyze the Stability of Non-Newtonian Fluid Flow Through a Wedge with Non-Linear Thermal Radiation and Chemical Reactions (2024) – Cited by: 1 🧪
  • Computational Intelligence Approach for Optimising MHD Casson Ternary Hybrid Nanofluid Over the Shrinking Sheet with the Effects of Radiation (2023) – Cited by: 17 ⚡
  • Artificial Neural Network Simulation and Sensitivity Analysis for Optimal Thermal Transport of Magnetic Viscous Fluid Over Shrinking Wedge via RSM (2023) – Cited by: 20 🔍

 

Dr. Manvi Breja | Cloud Computing | Best Researcher Award

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Dr. Manvi Breja | Cloud Computing | Best Researcher Award

Dr. Manvi Breja, Northcap university, India

Dr. Manvi Breja is an accomplished Assistant Professor and researcher specializing in Natural Language Processing (NLP), Artificial Intelligence, and Data Mining. Holding a Ph.D. in Computer Science from NIT Kurukshetra, her doctoral research focused on non-factoid question-answering systems. With over a decade of academic and industry experience, Dr. Breja has taught core computer science courses, authored 20+ impactful publications, and contributed as a reviewer for prestigious journals. She has held prominent roles at universities like Gurugram University, NorthCap University, and Manav Rachna University. Dr. Breja has also contributed to computational linguistics through edited books and technical committee leadership. Her commitment to research, innovation, and teaching excellence has earned her accolades and awards, inspiring her to advance academic pursuits in NLP, AI, and beyond.

Professional Profile:

Google scholar

Scopus

Suitability For Best Researcher Award:

Dr. Manvi Breja’s extensive contributions to research in NLP and Information Retrieval, her robust academic record, and her commitment to advancing knowledge through publications and technical roles make her an outstanding candidate for the Best Researcher Award. Her work not only demonstrates academic excellence but also bridges theoretical research with practical applications, impacting fields like artificial intelligence and data mining.

🎓 Education 

Dr. Manvi Breja’s educational journey highlights her unwavering commitment to academic excellence. She earned her Ph.D. in Computer Science from NIT Kurukshetra, graduating with an impressive 9.75/10 CGPA. Her doctoral research focused on non-factoid question-answering systems, showcasing her expertise in advanced AI applications. She completed her M.Tech in Information Technology at YMCA University with a stellar 9.7/10 CGPA, earning the prestigious Dean Merit Award. Her undergraduate studies in Computer Science and Engineering were marked by scholarships and awards for outstanding academic performance. Additionally, Dr. Breja has demonstrated exceptional aptitude through multiple GATE qualifications with top percentiles in 2012, 2013, and 2015, as well as her CBSE UGC-NET and JRF qualification, where she ranked among the top 72 candidates nationally. These achievements have laid a strong foundation for her robust career in artificial intelligence and data science.

💼 Experience

Dr. Manvi Breja’s professional journey exemplifies her dedication to teaching, research, and innovation. She is currently an Assistant Professor (Contractual) at Gurugram University (2022–2024), where she spearheads the NLP and AI curriculum while mentoring graduate researchers. Previously, she served as an Assistant Professor (Senior Scale) at NorthCap University (2018–2020), where she taught advanced courses in AI and machine learning and managed program coordination. Her earlier tenure as an Assistant Professor at Manav Rachna University (2014–2018) was marked by significant contributions to NLP research and departmental growth. Throughout her career, Dr. Breja has seamlessly balanced academic instruction with impactful research, further enhancing her profile through active participation in technical committees and her role as a reviewer for high-impact journals. Her professional experience reflects her unwavering commitment to excellence and her passion for advancing AI and data science education.

🏅Awards and Honors 

Dr. Manvi Breja’s illustrious academic and professional career is adorned with numerous awards and recognitions. She received the prestigious Dean Merit Award for exceptional performance during her M.Tech at YMCA University. Her technical proficiency and dedication are further validated by her multiple GATE qualifications, where she consistently achieved top percentiles in 2012, 2013, and 2015. She also excelled in the CBSE UGC-NET and JRF examinations, securing a top national rank of 72. Demonstrating her commitment to lifelong learning, Dr. Breja earned top-tier NPTEL certifications, ranking in the top 2% for Cryptography & Network Security and the top 5% for Social Networks. Her academic distinction was recognized early on, with consistent scholarships and awards throughout her undergraduate and postgraduate studies. These accolades underscore her excellence in the field of computer science and her dedication to academic and professional advancement.

🔍Research Focus

Dr. Manvi Breja’s research delves into cutting-edge areas at the intersection of artificial intelligence and language technologies. Her work prominently focuses on developing advanced non-factoid question-answering systems to tackle complex queries. She has also contributed to social network analysis, exploring network dynamics for meaningful real-world applications, and text and web analytics, uncovering insights from unstructured data through sophisticated AI and NLP techniques. Dr. Breja’s research emphasizes practical applications, bridging the gap between computational linguistics and artificial intelligence to address real-world challenges in information retrieval and data processing. Her innovative approaches have paved the way for impactful contributions in the fields of NLP, machine learning, and AI-driven technologies, with her research consistently aiming to drive meaningful advancements in academia and industry.

Publication Top Notes:

 

Dr. Ashish Mishra | Cloud Computer Awards | Best Researcher Award

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Dr. Ashish Mishra | Cloud Computer Awards | Best Researcher Award

Dr. Ashish Mishra, Rajkiya Engineering College Ambedkar Nagar, India

Dr. Ashish Kumar Mishra is an accomplished academic and researcher with a Ph.D. in Computer Science and Engineering from Motilal Nehru National Institute of Technology Allahabad, where he also earned his M.Tech. as a Gold Medalist. Currently an Assistant Professor in the Department of Information Technology at Rajkiya Engineering College Ambedkar Nagar, he has previously held a similar role at LDC Institute of Technical Studies in Allahabad. Dr. Mishra has received several accolades, including a Gold Medal for his M.Tech. and the NPTEL Discipline Star award in Computer Science and Engineering. His contributions to academia are further highlighted by his involvement in innovative patent work and his dedication to teaching and mentoring students.

Professional Profile:

Orcid
Google Scholar

🎓 Education

Dr. Ashish Kumar Mishra is a distinguished academic and researcher with a robust educational background in Computer Science and Engineering. He earned his Ph.D. from Motilal Nehru National Institute of Technology (MNNIT) Allahabad in 2020, achieving a commendable GPA of 8.25/10 in coursework. Dr. Mishra completed his M.Tech. from MNNIT Allahabad in 2015, graduating as a Gold Medalist with a CPI of 9.78/10. Additionally, he holds an M.C.A. from the Ewing Christian Institute of Management and Technology Allahabad (U.P. Technical University, Lucknow), where he graduated with honors, scoring 75.98%. His academic excellence and dedication to his field are evident through these accomplishments.

👨‍🏫 Experience

Dr. Ashish Kumar Mishra is currently serving as an Assistant Professor in the Department of Information Technology at Rajkiya Engineering College Ambedkar Nagar since December 11, 2017. He specializes in teaching courses such as Object Oriented Programming with Java, Web Technology, Cloud Computing, and Machine Learning. Previously, he worked as an Assistant Professor in the CSE/MCA Department at LDC Institute of Technical Studies, Allahabad from February 2010 to January 2016, where he taught various computer science subjects and played a key role in curriculum development.

🏆 Awards

Dr. Ashish Kumar Mishra is an accomplished Assistant Professor in the Department of Information Technology at Rajkiya Engineering College Ambedkar Nagar. With a Ph.D. in Computer Science and Engineering from Motilal Nehru National Institute of Technology Allahabad (2020), he has a robust academic background. His outstanding achievements include a Gold Medal in M.Tech. from MNNIT Allahabad (2016) and the prestigious NPTEL Discipline Star in Computer Science and Engineering awarded by the Ministry of HRD, Government of India (2023). Dr. Mishra’s expertise and dedication to teaching and research have significantly contributed to the field of Information Technology.

Publication Top Notes:

 

 

 

 

Dr. Arash Bozorgchenani | Cloud Resource Allocation Problems | Best Researcher Award

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Dr. Arash Bozorgchenani | Cloud Resource Allocation Problems | Best Researcher Award

Dr. Arash Bozorgchenani, University of Leeds, United Kingdom

🎓 Dr. Arash Bozorgchenani earned his Ph.D. in Electronic, Telecommunications, and Information Technology from Universita di Bologna, Italy, in 2020, focusing on computation offloading in fog/edge computing and energy harvesting. Currently serving as a Lecturer (Assistant Professor) at the School of Computing, University of Leeds, since July 2023, he teaches Networks and Procedural Programming while supervising students at all levels. With prior roles as a Research Associate at Lancaster University and a Post-doctoral Researcher at Universita di Bologna and DEI-Digicomm Research laboratory, his expertise spans fog networking, cloud/edge computing, wireless networks, machine learning, optimization problems, cybersecurity, and game theory. Dr. Bozorgchenani has a prolific publication record and has received notable awards for his contributions, including the China Electronics Education Society’s Outstanding Doctoral Thesis Award and the Shaanxi Higher Education Institutions Science and Technology Research Outstanding Achievement Award. 🔍

🌐 Professional Profiles :

Scopus

Orcid

Google Scholar

🎓 Education:

Dr. Arash Bozorgchenani completed his Ph.D. in Electronic, Telecommunications, and Information Technology from Universita di Bologna, Italy, in 2020. His doctoral research focused on computation offloading in fog/edge computing and energy harvesting technologies.

💼 Professional Experience:

He has served as a Lecturer (Assistant Professor) at the School of Computing, University of Leeds, since July 2023, where he teaches Networks and Procedural Programming modules and supervises undergraduate, master’s, and Ph.D. students. Prior to this, he worked as a Research Associate at Lancaster University and as a Post-doctoral Researcher at Universita di Bologna and DEI-Digicomm Research laboratory.

🏆 Awards and Honors:

Dr. Arash Bozorgchenani has garnered a host of accolades throughout his career, including being endorsed by UK Research and Innovation under the Global Talent Route in 2021 🌍, securing a Lancaster University Research Grant for a three-year Research Associate position in 2020 🎓, and receiving a prestigious Universita di Bologna Research Fellowship for his post-doctoral work in 2019 🏆. His academic journey began with a full Ph.D. scholarship at Universita di Bologna in 2016, setting the stage for his subsequent research endeavors and accomplishments.

🌍 Research Interests:

Dr. Bozorgchenani’s research interests include fog networking, cloud/edge computing, wireless networks, machine learning, optimization problems, cybersecurity, and game theory. He has published extensively in these areas and has received recognition for his contributions.

📚 Publications:

He has authored numerous papers in prestigious journals and conferences, focusing on topics such as computation offloading, machine learning, vehicular communication, and optimization techniques.

🔍 Research Achievements:

Dr. Bozorgchenani’s research has been recognized with several awards, including the China Electronics Education Society’s Outstanding Doctoral Thesis Award and the Shaanxi Higher Education Institutions Science and Technology Research Outstanding Achievement Award.

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 23 documents indexed in Scopus.
  • 📊 Citations: A total of 419 citations for his publications, reflecting the widespread impact and recognition of Dr. Arash Bozorgchenani’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 576 📖
    • h-index: 12  📊
    • i10-index: 13 🔍
  • Since 2018:
    • Citations: 565 📖
    • h-index: 12 📊
    • i10-index: 13 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes :

  1. Multi-objective computation sharing in energy and delay constrained mobile edge computing environments
    • Published in IEEE Transactions on Mobile Computing in 2020.
    • 116 citations.
  2. Centralized and distributed architectures for energy and delay efficient fog network-based edge computing services
    • Published in IEEE Transactions on Green Communications and Networking in 2018.
    • 60 citations.
  3. On the design of federated learning in latency and energy constrained computation offloading operations in vehicular edge computing systems
    • Published in IEEE Transactions on Vehicular Technology in 2021.
    • 59 citations.
  4. An Energy and Delay-Efficient Partial Offloading Technique for Fog Computing Architectures
    • Published in IEEE Globecom in 2018.
    • 57 citations.
  5. Computation offloading in heterogeneous vehicular edge networks: On-line and off-policy bandit solutions
    • Published in IEEE Transactions on Mobile Computing in 2021.
    • 48 citations.