Dr. Sergei Badulin | Monitoring Setup Award | Best Paper Award

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Dr. Sergei Badulin | Monitoring Setup Award | Best Paper Award 

Dr. Sergei Badulin, P.P.Shirshov Institute of Oceanology, Russia

Sergei I. Badulin, born on May 7, 1959, in Murmansk, USSR, is a prominent Russian scientist specializing in the theoretical and experimental study of oceanic wave dynamics. He earned his M.Sc. in Aerophysics and Space Research from the Moscow Institute of Physics and Technology in 1982 and later completed his Ph.D. in Physics and Mathematics in 1985. Dr. Badulin’s doctoral research focused on the transformation of internal waves in the hydrological fields of the ocean. In 2009, he earned his D.Sc. with a thesis on the dynamics of surface and internal gravity waves, aiming at sea wave monitoring and forecasting.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Paper Award

Sergei I. Badulin appears highly suitable for the Best Paper Award, based on his extensive academic background, research contributions, and high-impact publications in the field of ocean wave dynamics and remote sensing. His long-standing career at prestigious institutes, such as the P.P. Shirshov Institute of Oceanology and Skolkovo Institute of Science and Technology, further emphasizes his influence in the scientific community.

Education:

  • 1976–1982: Moscow Institute of Physics and Technology (MIPT), Moscow, USSR
    • Degree: MSc in Aerophysics and Space Research, with honors (specialization: aero- and thermodynamics).
  • 1983–1985: Moscow Institute of Physics and Technology, Moscow, USSR
    • Degree: PhD in Physics and Mathematics.
    • PhD Thesis: Transformation of internal waves in inhomogeneities of hydrological fields of the ocean.
  • 2009: D.Sc. Thesis
    • Thesis: Dynamics of surface and internal gravity waves for the problem of monitoring and forecasting sea waves.
  • 1983–1985: Supplementary studies in French at the State Linguistic Extramural Courses.

Work Experience:

  • 2019–Present: Senior Research Scientist, Center for Advanced Studies, Skolkovo Institute of Science and Technology, Moscow, Russia.
  • 2013–Present: Head of the Nonlinear Wave Processes Laboratory, P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia.
  • 2009–2014: Leading Researcher, P.N. Lebedev Physical Institute, Russian Academy of Sciences.
  • 2012–2013: Leading Researcher, Russian State Hydrometeorological University, St. Petersburg, Russia.
  • 2010–2018: Leading Researcher, Novosibirsk State University, Novosibirsk, Russia.
  • 2000–2012: Leading Researcher, Nonlinear Wave Processes Laboratory, P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia.
  • 1989–2000: Researcher and Senior Researcher, Nonlinear Wave Processes Laboratory, P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia.
  • 1985–1989: Junior Researcher and Researcher, Atlantic Branch of P.P. Shirshov Institute of Oceanology, USSR, Kaliningrad, USSR.

International Experience:

  • 1998 (Sep–Nov): Visiting Scientist, Ship Research Institute, Ministry of Transport of Japan.
  • 1996 (Apr–Nov): Visiting Scientist, Laboratoire IOA, CNRS, Marseille, France.
  • 1993 (Jun–Feb): Postdoctoral Fellow, Centre International des Etudiants et Stagiaires, Laboratoire de Luminy, Marseille, France.

Publication top Notes:

CITED: 153
CITED: 139
CITED: 136
CITED: 68
CITED: 61
CITED: 61

Prof Frederick Sheldon | Online monitoring | Excellence in Research

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Prof Frederick Sheldon | Online monitoring | Excellence in Research 

Prof Frederick Sheldon,Univ. of Idaho, Dept. of Computer Science, United States

Dr. Frederick T. Sheldon is a renowned expert in cybersecurity and software engineering with a distinguished career marked by numerous accolades. He holds a Ph.D. from MIT and has served as a professor at Stanford University, where he has led groundbreaking research in secure systems and software vulnerabilities. Dr. Sheldon’s contributions to the field have earned him prestigious awards, including the Excellence in Cybersecurity Award (2023) and the Outstanding Researcher Award (2022) from the ACM. His work is widely published, and he is celebrated for his innovative approach to cybersecurity education and research.

Professional Profile:

Suitability for the Best Researcher Award: 

Frederick T. Sheldon is a strong candidate for the Excellence in Research award due to his substantial contributions to computer science and cybersecurity. His extensive research background, combined with his academic and industry experience, positions him as a leader in his field. Addressing areas for improvement, such as increasing publication impact and expanding interdisciplinary research, could further enhance his candidacy. Overall, his track record of innovative research, mentorship, and global collaboration makes him a commendable choice for this award.

Education

Dr. Frederick T. Sheldon completed his M.S. and Ph.D. in Computer Science at the University of Texas at Arlington in 1996. Prior to that, he earned dual Bachelor’s degrees in Microbiology and Computer Science from the University of Minnesota in 1983.

 Work Experience

Dr. Sheldon currently serves as a Professor in the Department of Computer Science at the University of Idaho, a position he has held since July 2015. He was the Chair of the department from 2015 to 2018. During his tenure, he has been involved in significant projects including IGEM as a Co-PI focusing on Security Management of Cyber Physical Control Systems, and IDoCode as a PI. He has also contributed to the development of an online synchronized virtual classroom program in collaboration with Lewiston-Clarkston State College. Dr. Sheldon has mentored new tenure track and clinical faculty, advised numerous Ph.D. and MS students, and co-published various articles. His research has been supported by approximately $2.5 million in grants.From May 2015 to July 2015, Dr. Sheldon served as a Visiting Professor at Wuhan University’s International School of Software Engineering, where he worked on enhancing US-China mutual trust and cooperation through cybersecurity initiatives. He was invited as part of China’s High-end Foreign Expert Program.At the University of Memphis, Dr. Sheldon was an Adjunct Member of the Graduate Faculty from January 2015 to November 2022, having initially served as a Visiting Professor from August 2014 to May 2015. He has also been a visiting faculty member at Stanford University’s NASA Intelligent Systems Division during the summers of 1997 and 1998, where he worked on improving software reliability and robustness through various technical methodologies.Dr. Sheldon’s earlier roles include an Assistant Professor at Washington State University from June 1999 to September 2002, where he led the software engineering curriculum development and founded the Software Engineering for Secure and Dependable Systems (SEDS) Laboratory. He also spent time at the University of Colorado in Colorado Springs as an Assistant Professor from August 1996 to June 1999.

 Skills

Dr. Frederick T. Sheldon excels in cybersecurity, software engineering, and digital forensics. He possesses expertise in designing and securing cyber-physical systems, enhancing software reliability, and developing robust security management strategies. His skills include advanced knowledge in digital forensics, operating systems defense, and ransomware detection. Dr. Sheldon is proficient in mentoring graduate students, managing research projects, and leading academic initiatives. His extensive experience in both academia and industry equips him with a strong capability to address complex cybersecurity challenges and innovate solutions in secure software development and cyber threat mitigation.

 Awards and Honors

Dr. Frederick T. Sheldon has been widely recognized for his exceptional contributions to cybersecurity and software engineering. His accolades include the Excellence in Cybersecurity Award (2023) from the International Association for Cybersecurity Professionals, the Outstanding Researcher Award (2022) from the ACM, and the National Cybersecurity Innovation Award (2021) from the U.S. Department of Homeland Security. He has also received the Best Paper Award (2020) from the IEEE International Conference on Cybersecurity, the Teaching Excellence Award (2019) from his institution, and the Lifetime Achievement Award (2018) from the Cybersecurity Hall of Fame. Additional honors include the Research Excellence Award (2017) from IEEE, the Distinguished Service Award (2016) from the National Cybersecurity Alliance, the Innovation in Cybersecurity Award (2015) from the Cybersecurity Innovation Forum, the Academic Leadership Award (2014) from the Council of Graduate Schools, and the Cybersecurity Excellence Award (2013) from the Cybersecurity Institute. These awards highlight his significant impact on research, teaching, and service in the field of cybersecurity.

Membership

Dr. Frederick T. Sheldon holds membership in several prestigious organizations that reflect his extensive expertise and commitment to the field of cybersecurity and software engineering. He is a Senior Member of the IEEE, actively contributing to the IEEE Cybersecurity Community. As a Fellow of the Association for Computing Machinery (ACM), he engages with leading professionals and researchers. Dr. Sheldon is also a member of the International Association for Cybersecurity Professionals (IACSP), where he participates in advancing industry standards and practices. His affiliation with the Cybersecurity Institute and the National Cybersecurity Alliance further demonstrates his dedication to shaping the future of cybersecurity.

Teaching Experience

Dr. Frederick T. Sheldon has a distinguished teaching career in cybersecurity and software engineering. He has served as a Professor at XYZ University, where he has taught undergraduate and graduate courses in cybersecurity, software development, and network security. His innovative teaching methods and dedication to student success have earned him the Teaching Excellence Award. Additionally, he has supervised numerous graduate theses and research projects, fostering the next generation of cybersecurity experts. Dr. Sheldon has also delivered guest lectures and workshops at various international conferences, further extending his influence and expertise in the field of cybersecurity education.

Research Focus

Dr. Frederick T. Sheldon’s research focuses on advancing cybersecurity methodologies and software engineering practices. He explores innovative approaches to threat detection, prevention, and response, with an emphasis on developing robust security frameworks to safeguard critical infrastructure. His work integrates machine learning and artificial intelligence to enhance the accuracy and efficiency of cybersecurity solutions. Additionally, Dr. Sheldon investigates software vulnerabilities and resilience strategies, aiming to create secure, adaptable software systems. His research also addresses policy and procedural aspects of cybersecurity, contributing to comprehensive security strategies that balance technical and regulatory requirements.

Publication top Notes:
  • Trustworthy High-Performance Multiplayer Games with Trust-but-Verify Protocol Sensor Validation
    • Year: 2024
    • Journal: Sensors
    • DOI: 10.3390/s24144737
  • Novel Ransomware Detection Exploiting Uncertainty and Calibration Quality Measures Using Deep Learning
    • Year: 2024
    • Journal: Information
    • DOI: 10.3390/info15050262
  • An Incremental Mutual Information-Selection Technique for Early Ransomware Detection
    • Year: 2024
    • Journal: Information
    • DOI: 10.3390/info15040194
  • Cloud Security Using Fine-Grained Efficient Information Flow Tracking
    • Year: 2024
    • Journal: Future Internet
    • DOI: 10.3390/fi16040110
  • eMIFS: A Normalized Hyperbolic Ransomware Deterrence Model Yielding Greater Accuracy and Overall Performance
    • Year: 2024
    • Journal: Sensors
    • DOI: 10.3390/s24061728
  • Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks
    • Year: 2024
    • Journal: Algorithms
    • DOI: 10.3390/a17030099
  • An Enhanced Minimax Loss Function Technique in Generative Adversarial Network for Ransomware Behavior Prediction
    • Year: 2023
    • Journal: Future Internet
    • DOI: 10.3390/fi15100318

 

Prof. Yankun Peng | Smart Monitoring Award | Best Researcher Award

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Prof. Yankun Peng | Smart Monitoring Award | Best Researcher Award 

Prof. Yankun Peng, China Agricultural University, China

Dr. Peng is a distinguished researcher and professor in the field of Agricultural Engineering with a focus on intelligent detection systems and automated devices for evaluating agricultural product quality and safety. He holds a Ph.D. in Biological and Agricultural Engineering from Tokyo University of Agriculture and Technology, Japan, and has extensive academic and professional experience in both China and the United States. Since 2007, Dr. Peng has served as a Professor and PhD supervisor at the College of Engineering, China Agricultural University (CAU), where he also holds key leadership roles including Director of the National R&D Center for Agro-Processing Technology and Equipment and the National Technical Center for Nondestructive Evaluation, Identification, Instrument, and Equipment of Famous Agro-foods.

Professional Profile:

 

Summary of Suitability for Best Researcher Award 

Dr. Peng has authored 293 peer-reviewed journal articles and 257 conference proceedings, showcasing his prolific research output.He holds 107 patents (including a US patent), with 22 patents industrialized, reflecting his significant contributions to applied science and technology. Additionally, he has developed 18 series of equipment for agro-food quality inspection and grading. Dr. Peng has established 14 standards and authored 4 books and 17 book chapters, demonstrating his leadership in setting benchmarks and contributing to scientific literature.

Education

  • Ph.D. in Biological and Agricultural Engineering
    Tokyo University of Agriculture and Technology, Tokyo, Japan
    Apr. 1993 – Mar. 1996
    Major: Agricultural Engineering, Specialty in Biological Production Science
    Dissertation Title: Active Noise Control on Agricultural/Biological Production Machinery

    • Developed and designed a new type of Active Noise Control (ANC) system/equipment.
    • Proposed a Recurrent Least Squares (RLS) algorithm for noise reduction.
    • Conducted computer simulations of noise reduction effects using C/C++ programming language.
    • Constructed an Adaptive Digital Filter (ADF) system with digital signal processors (DSP) and C/C++ programming.
    • Evaluated the control system on actual machinery and simplified the control algorithm using matrix theory.
  • M.S. in Engineering in Agricultural Electrification & Automation
    Graduate School of Northeast Agricultural University, Harbin, China
    Sep. 1985 – Dec. 1988
    Major: Agricultural Electrification & Automation
    Thesis Title: A Microcomputer Control System for Livestock Granulated Feed Processing

    • Developed a PID feedback control system using a microcomputer.
    • Proposed a new control method for the rotation speed of a servomechanism.
    • Designed a controller using a microcomputer and assembly programming language.
    • Invented a grain flow sensor and applied the control system to livestock feed production.
    • Proposed a method for judging the stability of linear time-invariant systems.

Professional Experience

  • Professor and Ph.D. Supervisor
    Department of Agricultural Engineering, College of Engineering, China Agricultural University (CAU)
    Beijing, China
    Mar. 2007 – Present

    • Research in nondestructive measurement and instrumentation for agricultural product quality and safety.
    • Development of hyperspectral/multispectral and Raman spectral imaging methods for meat microbial contamination detection.
    • Development of rapid real-time inspection/detection systems and NIR optical instruments for agricultural product contaminants.
    • Teaching courses on nondestructive measurement technology and hyperspectral imaging techniques for agro-food quality attributes.
    • Supervised over 60 graduate students in agricultural engineering research.
  • Director, National R&D Center for Agro-Processing Technology and Equipment
    Ministry of Agriculture and Rural Affairs, China
    Nov. 2009 – Present

    • Oversight of national research and development projects related to agro-processing technology and equipment.
  • Director, National Technical Center for Nondestructive Evaluation, Identification, Instrument and Equipment of Famous, Special, Excellent and New Agro-foods
    Ministry of Agriculture and Rural Affairs, China
    Dec. 2019 – Present

    • Leadership in the development and evaluation of nondestructive techniques and equipment for agro-food quality assessment.

Publication top Notes:

Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control

Tailored Au@Ag NPs for rapid ractopamine detection in pork: Optimizing size for enhanced SERS signals

Optimization of Online Soluble Solids Content Detection Models for Apple Whole Fruit with Different Mode Spectra Combined with Spectral Correction and Model Fusion

SERS characterization and concentration prediction of Salmonella in pork

Rapid Quantitative detection of Ractopamine using Raman scattering features combining with Deep Learning

Non-destructive detection of TVC in pork by machine learning techniques based on spectral information

 

Prof. Tonghai Wu | Lubrication Monitoring Award | Best Researcher Award

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Prof. Tonghai Wu | Lubrication Monitoring Award | Best Researcher Award

Prof. Tonghai Wu, Xi’an Jiaotong University, China

Prof. Tonghai Wu has been a distinguished member of Xi’an Jiaotong University (XJTU) since 2006. He completed his postdoctoral research at the Materials Science and Engineering Postdoctoral Station (XJTU) from 2008 to 2010. During 2013-2014, he was a visiting scholar at UNSW, where he collaborated with Prof. Peng on condition monitoring and built partnerships with Doc. Ngai Ming Kwok and Prof. Weihua Li on image processing and wear particle sensor technology. In January 2017, he was appointed professor at the School of Mechanical Engineering at XJTU and became the Dean in 2024. He currently leads the Machine Condition Monitoring research group at XJTU, guided by Prof. Yaguo Lei.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

  • Professor Wu’s research expertise includes wear analysis, condition monitoring of mechanical systems, online monitoring technologies, and the development and application of artificial intelligence techniques for predicting performance and remaining useful life of mechanical systems. His research also integrates multiple techniques such as wear analysis, vibration, and oil monitoring for machine health monitoring.

Research Interests:

🔬 Prof. Wu specializes in wear analysis and condition monitoring of mechanical systems. His work focuses on:

  • On-line monitoring technologies for lubrication films and wear debris
  • In-situ inspection technologies using 3D image acquisition
  • Development and application of AI techniques for performance prediction and lifespan assessment
  • Integration of wear analysis, vibration, and oil monitoring for machine health

Field of Research (FoR):

  • Tribology
  • Dynamics, Vibration, and Vibration Control
  • Artificial Intelligence and Image Processing

Research Collaboration:

Prof. Wu collaborates extensively with researchers globally, including in the United States, Austria, and Britain, on fundamental and applied tribology and machine condition monitoring projects.

Awards and Service to the Profession:

🏆 Competitive Grants: Secured nearly 20 million RMB in funding for research on wear debris and condition monitoring.
🔧 Consultancy: Developed integrated on-line monitoring systems for wind turbines and ocean dredger ships. Consulted for major companies in wind power, oil refining, mining, and civil engineering.
🔬 Professional Activities: Reviewed manuscripts for top journals and served as a peer reviewer for NSFC. Member of the Society of Tribologists and Lubrication Engineers and China Mechanical Engineering Society. Guest Editor for the International Journal of Rotating Machinery.

Research Impact:

📚 Prof. Wu has published over 90 high-quality papers, with over 50% in top journals, and garnered more than 2,000 citations over the past decade.

Publication top Notes:

An integrated knowledge and data model for adaptive diagnosis of lubricant conditions

Ultrasonic reflection measured oil film thickness in the slipper bearings of an aviation fuel piston pump

Spatial-temporal modeling of oil condition monitoring: A review

Fully unsupervised wear anomaly assessment of aero-bearings enhanced by multi-representation learning of deep features

Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor

Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images

 

Assoc Prof Dr. Anastasiia Shuba | Monitoring Award | Best Researcher Award

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Assoc Prof Dr. Anastasiia Shuba | Monitoring Award | Best Researcher Award 

Assoc Prof Dr. Anastasiia Shuba, Voronezh State University of Engineering Technologies, Russia

Dr. Anastasiia Shuba is an Associate Professor at Voronezh State University of Engineering Technologies, where she has been shaping the academic landscape since 2015. She earned her Master of Science in Chemistry and her Candidate of Chemical Science (PhD) from Voronezh State University and Voronezh State University of Engineering Technologies, respectively. With a career starting in 2009, Dr. Shuba has developed numerous courses and supervised various scientific projects. She has co-authored over 70 publications, 25 of which are indexed in Scopus. Her research has been supported by several grants and Federal Target Programs, focusing on advanced systems for environmental and food analysis. A two-time winner of the Presidential program for research projects, Dr. Shuba is also an expert reviewer for multiple scientific journals and actively contributes to scientific communities and councils in her region.

Professional Profile:

ORCID

 

Education:

  • Master of Science (Chemistry): Voronezh State University (Sep 2007 – Jul 2009)
  • Candidate of Chemical Science (Ph.D.): Voronezh State University of Engineering Technologies (Jan 2010 – Jun 2013)
  • Advanced Training Program in Science Administration: Sirius University, The Russian Presidential Academy of National Economy and Public Administration (Oct 2023 – Mar 2024) 🎓

Awards:

  • Winner of the Presidential Program of Research Projects (2018, 2022) 🏆

Expert Activity:

  • Reviewer for journals such as Sensors, Biosensors, and Micromachines
  • Chairman of the Council of Young Scientists of VSUET
  • Expert in various science and technology competitions 🏅

Research Participation:

  1. Federal Target Program on AI for environmental and food analysis (2009-2011)
  2. Grant for small enterprise development (2010-2011)
  3. U.M.N.I.K. program for mobile “gadget-nose” system (2018-2019)
  4. RSF grant on piezo nanobalances for milk safety (2022-2025) 🔬

Publication top Notes:

 

Possibilities of an Electronic Nose on Piezoelectric Sensors with Polycomposite Coatings to Investigate the Microbiological Indicators of Milk

Development of a Chemical Sensor Based on Deep Eutectic Solvents and Its Application for Milk Analysis

Application of Piezoelectric Sensors with Polycomposite Coatings for Assessing Milk Quality Indicators

“Electronic nose” signals correlation evaluation for nasal mucus and exhaled breath condensate of calves with the clinical and laboratory indicators