Patrick Chernjavsky | Additive Manufacturing | Best Researcher Award

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Mr Patrick Chernjavsky | Additive Manufacturing | Best Researcher Award

Research Assistant, Worcester Polytechnic Institute, United States

Patrick Chernjavsky is a Ph.D. candidate in Mechanical & Materials Engineering at Worcester Polytechnic Institute (WPI), specializing in advanced manufacturing, design for manufacturing, and surface metrology. His research focuses on material characterization, corrosion control, and optimizing manufacturing processes for enhanced performance and durability. With extensive experience in metallurgical engineering, additive manufacturing, and tribology, Patrick has contributed significantly to industry and academia through innovative projects and research publications. His work in material removal rate analysis, flexible spindle polishing, and vibration control has been recognized in leading journals. Patrick has also interned at Saint-Gobain, Liquid Piston, and NAWCAD, where he developed advanced coatings, automated analysis tools, and thermo-mechanical models. His contributions to aerospace, medical devices, and energy systems showcase his interdisciplinary expertise. Patrick continues to advance precision manufacturing technologies through research, experimentation, and industry collaborations.

PROFESSIONAL PROFILE

Google Scholar

STRENGTHS FOR THE AWARD

✅ Diverse Research Portfolio: Patrick Chernjavsky has an extensive research background spanning Advanced Manufacturing, Surface Polishing, and Additive Manufacturing, making significant contributions to both industry and academia.
✅ High-Impact Publications: His work is published in reputable journals and conferences, covering grinding processes, HydroFlex polishing, vibration control, and tribological coatings, demonstrating strong experimental and analytical expertise.
✅ Industrial and Government Research Experience: His internships at Liquid Piston, Saint-Gobain, and NAWCAD highlight his ability to bridge academic research with real-world engineering applications, including materials selection, coatings, and mechanical performance testing.
✅ Innovation and Problem-Solving: Contributions to corrosion control, wear resistance, and material removal rate optimization show a strong problem-solving ability in high-performance materials and surface metrology.
✅ Recognition and Security Clearance: His scholarship award for developing an automated vibration analysis tool for aircraft components and SECRET-level security clearance underline his trustworthiness and excellence in classified research.

AREAS FOR IMPROVEMENTS

🔹 Higher Citation Impact: While his research is well-regarded, increasing citations and extending collaborations in emerging materials science and sustainable manufacturing could strengthen his influence.
🔹 Broader Research Leadership: Leading more interdisciplinary projects or securing external funding for research grants could further solidify his standing as a top researcher.
🔹 Industry-Academia Partnerships: Expanding on industry collaborations for real-world applications, particularly in robotic surface finishing and aerospace materials, could enhance research applicability.

EDUCATION 🎓

Patrick Chernjavsky is pursuing a Doctor of Philosophy in Mechanical & Materials Engineering at Worcester Polytechnic Institute (WPI), Worcester, Massachusetts, with an expected completion in May 2025. His research areas include advanced manufacturing, surface metrology, design for manufacturing, and corrosion control. Patrick has also developed expertise in experimental techniques such as non-destructive CT, profilometry, XRD, SEM, and wear testing. Prior to WPI, he actively participated in engineering projects, including drone design and hydropower device development. His academic journey is complemented by certifications such as Engineering Simulation with ANSYS (2024), reinforcing his proficiency in simulation tools. His educational background has laid a strong foundation for his research contributions to material characterization, tribology, and manufacturing processes.

EXPERIENCE 🏭

Patrick Chernjavsky has gained diverse industrial and research experience through multiple internships and assistantships. As a Metallurgical Engineering Intern at Liquid Piston (December 2024 – March 2025), he worked on advanced coating tribopairs and surface crosshatch designs for rotary engine seals. At Saint-Gobain (May 2021 – August 2021), he collaborated on thermo-mechanical modeling of grinding processes and conducted validation testing. During his tenure at NAWCAD (June 2019 – February 2021), he developed an automated vibration analysis tool for aircraft component testing, earning a scholarship award. Additionally, as a Research Assistant at WPI, he has contributed to various projects in additive manufacturing, polishing, and tribology. His experience spans material characterization, design for manufacturing, and aerospace engineering, bridging the gap between theoretical research and practical applications.

AWARDS & HONORS 🏆

Patrick Chernjavsky has been recognized for his contributions to mechanical engineering and research innovation. He received a scholarship award for developing an automated vibration analysis tool at NAWCAD, demonstrating excellence in aerospace engineering. His work in tribology and material characterization has been featured in leading manufacturing and medical device conferences. Additionally, his research contributions in polishing techniques, material removal rate analysis, and corrosion control have been cited in esteemed journals. Patrick’s interdisciplinary expertise in additive manufacturing, advanced coatings, and precision engineering continues to earn accolades in academic and industrial circles. His commitment to innovation and research excellence underscores his dedication to advancing mechanical and materials engineering.

RESEARCH FOCUS 🔬

Patrick Chernjavsky’s research focuses on advanced manufacturing, tribology, and precision surface finishing. His work explores material removal dynamics, flexible spindle polishing, and vibration control for industrial applications. He investigates innovative coating techniques for wear resistance and friction reduction, optimizing material properties for aerospace and medical applications. His studies in hydrodynamic flexible spindle (HydroFlex) polishing have led to advancements in internal surface finishing for high-aspect-ratio channels. Patrick also explores experimental techniques such as SEM, XRD, and profilometry to assess surface integrity. His interdisciplinary approach combines experimental analysis, computational modeling, and real-world validation, contributing to high-performance manufacturing and material durability.

PUBLICATION TOP NOTES 📄

  • Experimental Investigation of the Material Removal Rate in Grinding of Calcified Plaque by Rotational Atherectomy
  • Hydrodynamic Flexible Spindle (HydroFlex) Polishing for Internal Surfaces of Complex Channels with High Aspect Ratio
  • Experimental Investigation of the Calcified Plaque Material Removal Rate in Coronary Rotational Atherectomy
  • Vibration Control Coupler Design for Robot Learning From Human Polishing
  • Grit Size Effect on HydroFlex Polishing Dynamics and Performance
  • Hydrodynamic Flexible Spindle (HydroFlex) Polishing of Turbine Blade Internal Cooling Channels for Oxide Removal
  • Creation of a Fish-Friendly Aquatic Hydropower Device Using an Oscillating Hydrofoil
  • Creation and Distribution of Monetized Online Content for Old Sturbridge Village’s Virtual Village
  • Monroe Community College Drone Design Team

CONCLUSION

Patrick Chernjavsky is a strong candidate for the Best Researcher Award due to his expertise in advanced manufacturing, tribology, and surface metrology, combined with notable industrial experience and impactful publications. With further research leadership and industry partnerships, he has the potential to be a leading figure in the field of materials science and engineering. 🚀

Partha Sengupta | Bayesian updating | Best Researcher Award

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Dr Partha Sengupta | Bayesian updating | Best Researcher Award

Engineer III in Transit, Railways and Transportation, AECOM, India

🌟 Partha Sengupta is a dedicated civil engineer specializing in structural engineering and Bayesian model updating techniques. Currently serving as an Engineer III at AECOM, he has a robust academic foundation with a Ph.D. in Civil Engineering from IIEST, Shibpur. His research contributions span structural health monitoring, model reduction techniques, and advanced Bayesian frameworks, reflected in numerous high-impact publications. With expertise in transit, railways, and transportation, he is recognized for his innovative approaches to solving engineering challenges.

PROFESSIONAL PROFILE

Orcid

Scopus

STRENGTHS FOR THE AWARD

  1. Academic Excellence:
    • Ph.D. in Civil Engineering with a perfect CGPA (10/10), demonstrating exceptional academic rigor and expertise in structural engineering.
    • M.Tech and B.Tech degrees with high CGPAs, showcasing consistent academic performance.
  2. Professional Experience:
    • Currently serving as Engineer III at AECOM, contributing to transit, railways, and transportation projects at a global scale.
    • Rich experience in academia and research as a Senior Research Fellow and Project Executive Officer, indicating proficiency in structural health monitoring and advanced modeling techniques.
  3. Research Contributions:
    • Published multiple high-impact journal articles, book chapters, and conference papers in renowned journals like ASCE-ASME Journal, Journal of Sound and Vibration, and Mechanical Systems and Signal Processing.
    • Key focus on Bayesian model updating, finite element model updating, and model reduction techniques, addressing critical challenges in structural engineering.
  4. Innovative Approaches:
    • Developed advanced methodologies, including Gaussian mixture-based autoregressive error models and enhanced iterative model reduction techniques, contributing to the structural engineering field.
    • Significant advancements in Bayesian frameworks for model updating, which have direct applications in structural health monitoring and risk assessment.
  5. Recognition and Credentials:
    • ORCID and ResearcherID profiles reflect a verified and active engagement in research.
    • Scopus Author ID and a substantial publication record validate his impact and credibility in the scientific community.

AREAS FOR IMPROVEMENT

  1. Global Outreach:
    • Expanding collaboration with international researchers and organizations could enhance his global impact and visibility.
    • Engaging in international conferences and workshops more frequently to share expertise on a broader platform.
  2. Industrial Applications:
    • Further integration of research findings into large-scale industrial applications to demonstrate the practical relevance of theoretical contributions.
  3. Teaching and Mentorship:
    • Although academic positions are noted, increased involvement in mentoring and teaching could strengthen his profile as an educator.

EDUCATION

🎓 Ph.D. in Civil Engineering (2018–2023)
Indian Institute of Engineering Science and Technology (IIEST), Shibpur
Thesis: Finite Element Model Updating in Bayesian Framework.

🎓 M.Tech in Civil Engineering (2014–2016)
IIEST, Shibpur
Thesis: Application of Ground Penetrating Radar in Concrete and Pavement Evaluation.

🎓 B.Tech in Civil Engineering (2010–2014)
West Bengal University of Technology
CGPA: 9.02/10

EXPERIENCE

💼 Engineer III (2024–Present)
AECOM: Specializing in transit, railways, and transportation.

💼 Project Executive Officer (Feb–May 2024)
IIT Kanpur: Oversaw high-impact civil engineering projects.

💼 Senior Research Fellow (2020–2023)
IIEST, Shibpur: Focused on structural health monitoring.

💼 Civil Design Engineer (2016–2018)
Netguru Engineering Pvt. Ltd.: Worked on critical civil design projects.

AWARDS AND HONORS

🏅 ResearcherID GRF-0355-2022: Recognized for impactful research.
🏅 Scopus Author ID 57219656397: Acknowledged for significant contributions to civil engineering.
🏅 10/10 CGPA in Ph.D.: Demonstrating academic excellence.
🏅 Multiple journal publications in prestigious platforms like ASCE, Elsevier, and IOP.

RESEARCH FOCUS

🔬 Structural Health Monitoring: Advancing techniques for real-time infrastructure evaluation.
🔬 Bayesian Frameworks: Developing innovative model updating methodologies.
🔬 Model Reduction Techniques: Enhancing computational efficiency in structural analysis.
🔬 Risk Assessment in Civil Engineering: Pioneering stochastic modeling approaches.

PUBLICATION TOP NOTES

📘 Gaussian Mixture–Based Autoregressive Error Model for Bayesian Updating (2024).
📘 An Improved Iterative Model Reduction Technique for Limited Responses (2023).
📘 Bayesian Model Updating in Time Domain Using Iterative Techniques (2023).
📘 Two-Stage Bayesian Model Updating Framework with Modal Responses (2023).
📘 Enhanced Iterative Model Reduction in Time Domain (2023).
📘 Metropolis-Hastings Bayesian Updating with Heteroscedastic Models (2022).
📘 Markov Chain Monte Carlo Simulation for Bayesian Model Updating (2022).
📘 Model Reduction for Bayesian Updating of Structural Parameters (2022).
📘 Bayesian Approach for Model Updating with Simulated Modal Data (2020).

CONCLUSION

Partha Sengupta stands out as an exceptional candidate for the Best Researcher Award due to his strong academic foundation, significant contributions to structural engineering research, and innovative methodologies in model updating techniques. While expanding international collaboration and integrating research into practical applications could further elevate his profile, his current achievements are remarkable and align well with the criteria for this prestigious recognition.

 

Shiyu Liu – Engineering – Best Researcher Award

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Shiyu Liu - Engineering - Best Researcher Award

Hebei University - China

AUTHOR PROFILE

SCOPUS

SHIYU LIU: RESEARCHER IN AI-BASED MONITORING 🔬

Shiyu Liu, currently a lecturer and postdoctoral researcher at Hebei University, has been making significant contributions in the field of spectral detection and analysis using artificial intelligence. His primary research revolves around spectral detection, machine learning, and AI-driven health monitoring systems for lithium-ion batteries, bringing innovative solutions to environmental monitoring and engineering applications.

AI-DRIVEN BATTERY MONITORING 🔋

Liu's work focuses on the health monitoring of lithium-ion batteries through artificial intelligence techniques. He combines electrochemical impedance spectroscopy with machine learning to accurately predict battery capacity and health. This research is vital for improving battery longevity, particularly in electric vehicles and sustainable energy systems, where battery performance is crucial.

SPECTRAL ANALYSIS & AI ALGORITHMS 📊

Liu's expertise extends to spectral detection and analysis, utilizing AI-based algorithms for processing near-infrared (NIR) spectroscopy data. His research aims to address issues such as high noise interference and spectral peak overlap, which often hinder accurate detection of complex organic compounds. By integrating machine learning and chemometric methods, he strives for precision in environmental pollutant measurement and industrial applications.

INNOVATIVE PROJECTS & PARTNERSHIPS 🤝

Shiyu Liu has actively contributed to several national and provincial projects, including the National Natural Science Foundation of China. His projects range from detecting environmental pollutants using spectral analysis to developing remote sensing image processing algorithms for space applications. These collaborations underscore his role in advancing both environmental science and technology.

CUTTING-EDGE PUBLICATIONS 📚

Liu has published extensively in prestigious journals, such as Fuel and Spectrochimica Acta, with a focus on using AI techniques for diesel fuel analysis and NIR spectroscopy. His innovative approach combines deep learning with spectral data to enhance the accuracy of fuel property detection, contributing to advancements in both energy and environmental fields.

PROFESSIONAL ENGAGEMENTS & PRESENTATIONS 🎤

Liu actively participates in international conferences, presenting his research findings to global audiences. Notably, he presented at the 2023 UNIfied International Conference in the UK, where he shared insights on battery health monitoring using AI. His academic activities also include contributions to forums on infrared technology, further solidifying his reputation in AI-driven research.

AWARDS & RECOGNITIONS 🏆

Shiyu Liu has received several prestigious awards, including the CSC Scholarship for his visiting PhD tenure at the University of Huddersfield. His accolades also include national scholarships, recognition as an “excellent graduate,” and top prizes in mathematical and physics competitions. These honors reflect his commitment to academic excellence and innovation in his field.

NOTABLE PUBLICATION

Title: Series fusion of scatter correction techniques coupled with deep convolution neural network as a promising approach for NIR modeling
Authors: Liu, S., Wang, S., Hu, C., Kong, D., Yuan, Y.
Journal: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
Year: 2023

Title: A MLP-Based Transfer Learning Model Using EIS Health Features for State of Health Estimation of Lithium-Ion Battery
Authors: Zhao, X., Wang, Z., Liu, S., Gu, F., Ball, A.
Conference: ICAC 2023 - 28th International Conference on Automation and Computing
Year: 2023

Title: Markov Transform Field Coupled with CNN Image Analysis Technology in NIR Detection of Alcohols Diesel
Authors: Liu, S., Wang, S., Hu, C., Kong, D.
Conference: Mechanisms and Machine Science
Year: 2023

Title: Rapid and accurate determination of diesel multiple properties through NIR data analysis assisted by machine learning
Authors: Liu, S., Wang, S., Hu, C., Kong, D., Wang, J.
Journal: Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
Year: 2022

Title: Determination of alcohols-diesel oil by near infrared spectroscopy based on gramian angular field image coding and deep learning
Authors: Liu, S., Wang, S., Hu, C., Bi, W.
Journal: Fuel
Year: 2022