Heba Afify | Engineering | Editorial Board Member

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Dr. Heba Afify | Engineering | Editorial Board Member

Cairo | Egypt

Dr. Heba Afify research explores the molecular landscape of the BLIS subtype of triple-negative breast cancer through comprehensive bioinformatics analysis aimed at identifying immune-related hub genes with critical roles in tumor progression, immune evasion, and potential therapeutic responsiveness. Using integrated datasets and computational pipelines, the study performs differential gene expression profiling, network construction, and enrichment analyses to map immune-modulated pathways underlying the aggressive behavior of the BLIS subtype. Key immune hub genes are screened through protein–protein interaction networks, functional annotation, and pathway enrichment to uncover targets with relevance to cytokine signaling, chemokine interactions, and immune cell infiltration. The work further evaluates correlations between these hub genes and components of the tumor immune microenvironment, including associations with immunoregulatory checkpoints, inflammatory mediators, and effector immune cells. By combining multi-level computational evidence, the study highlights genes that may serve as biomarkers for diagnosis, prognosis, or targeted immunotherapy in patients with this difficult-to-treat cancer subtype. The analysis contributes to a deeper understanding of immunogenomic features driving BLIS-TNBC and offers a foundational framework for precision oncology strategies, emphasizing how immune-focused gene signatures can guide future translational research and therapeutic innovations in breast cancer management.

Featured Publications

Adel, H., Abdel Wahed, M., & Afify, H. M. (2025). Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer. Egyptian Journal of Medical Human Genetics. https://doi.org/10.1186/s43042-025-00745-0

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2025). Stress detection based EEG under varying cognitive tasks using convolution neural network. Neural Computing and Applications, Advance online publication. https://doi.org/10.1007/s00521-024-10737-7

Afify, H. M., Mohammed, K. K., & Hassanien, A. E. (2024). Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-023-03422-8

Waleed Algriree | Engineering | Editorial Board Member

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Dr. Waleed Algriree | Engineering | Editorial Board Member

Putra university malaysia | Malaysia

Dr. Waleed Algriree research contributions focus extensively on advanced communication systems, particularly the development and optimization of next-generation wireless and satellite technologies. Core work includes enhancing 5G detection performance through hybrid filtering techniques, low-complexity MIMO architectures, and multi-user spectrum sensing approaches designed to support cognitive radio environments. Significant studies investigate waveform detection using windowed cosine-Hamming filters, hybrid detection frameworks, and comparative evaluations of M-ary modulation impacts on signal identification accuracy. Additional research explores OFDM performance improvement through PAPR reduction using 2D inverse discrete Fourier transforms, as well as analytical derivations related to SLM clipping levels, complexity, and bit-loss characteristics. Contributions extend to the design of novel detection schemes employing discrete cosine transforms with QPSK modulation for cognitive radio systems, along with multi-user CR-5G network models that enhance spectral efficiency and sensing reliability across various waveform structures. Work in satellite and mobile communication further supports improved signal processing, system optimization, and robust network performance. Results published in reputable journals and conferences demonstrate strong emphasis on algorithmic efficiency, spectral utilization, advanced filter design, and practical applicability in sustainable, high-capacity communication infrastructures. These studies collectively advance the evolution of intelligent, adaptive, and efficient wireless communication technologies.

Featured Publication

Algriree, W. K. H. (Year). Advancing healthcare through piezoresistive pressure sensors: A comprehensive review of biomedical applications and performance metrics.

Uwayesu Happy Edwards | Engineering | Excellence in Research Award

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Mr. Uwayesu Happy Edwards | Engineering | Excellence in Research Award

Suzhou university of science and technology | China

Mr. Uwayesu Happy Edwards the research focuses on environmental engineering, natural resource assessment, wastewater treatment modeling, hydropower system analysis, and climate-related environmental degradation across East and Central Africa. Recent work investigates the factors driving water quality changes in Lake Bunyonyi, integrating ecological metrics with habitat-impact assessments. Studies on wastewater treatment processes include large-scale evaluation of ASM1 parameters under subtropical climatic conditions, using long-term WWTP monitoring data to improve predictive reliability and optimize treatment efficiency. Broader environmental impact assessments examine risk patterns in natural resource zones across Southern Nigeria, Ibo regions, and Uganda’s Kitezi landfill, applying quantitative environmental models to evaluate pollution, habitat stress, and human–ecosystem interaction. Additional research explores deforestation-driven climate change in Morogoro, Tanzania, emphasizing the environmental implications for EPA-related conservation missions. Work on hydropower comparability analyzes the performance, sustainability, and environmental footprints of hydropower relative to fossil fuels and other energy systems in developing countries, contributing to renewable-energy assessment frameworks. Complementary studies investigate biomass arrangement effects on aquatic ecosystems, using vibrational analysis to evaluate impacts on fish habitats in Lake Victoria. Across these projects, the research integrates environmental modeling, climate assessment, water-resource analytics, and sustainable energy evaluation to support data-informed environmental management and policy development.

Featured Publications

Uwayesu, H. E., & Mulangila, J. (2025). Factor contributing to change of water in Lake Bunyonyi [Dataset]. Figshare. https://doi.org/10.6084/m9.figshare.30041587

Uwayesu, H. E. (2025). Address of Edwards line of emissions in reducing/positive impact to climate [Dataset]. OSF. https://doi.org/10.17605/osf.io/csz8x

 Uwayesu, H. E. (2025). Environmental impact and risk assessment of natural resource areas around Southern Nigeria, particularly Ibo and Uganda in the Kitezi landfill [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/EJ4Z7E

 Uwayesu, H. E. (2025). Evaluation of ASM1 parameters using large-scale WWTP monitoring data from a subtropical climate in Entebbe [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/BG5VJB

Yunwen Xu | Engineering | Best Researcher Award

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Dr. Yunwen Xu l Engineering
| Best Researcher Award

Shanghai Jiao Tong University | China

Dr. Yunwen Xu’s research focuses on advancing intelligent transportation systems, autonomous driving control, and predictive control for complex and embedded systems. Her innovative work integrates graph-based spatial-temporal modeling, data-driven control algorithms, and real-time optimization to enhance vehicle trajectory prediction, traffic signal management, and collaborative control in large-scale dynamic environments. Through over 50 high-impact publications, including 15 in top-tier journals and several ESI highly cited papers, Dr. Xu has significantly contributed to the theoretical and practical foundations of predictive control and intelligent mobility. Her research achievements include developing FPGA-based predictive controllers, robust model predictive frameworks, and reinforcement learning-based control systems for V2X-enabled autonomous vehicles. By leading national and provincial research projects and collaborating internationally with institutions like Purdue University and industrial partners such as Shanghai Electric Wind Power Group, she bridges the gap between academic innovation and industrial application. Her patents and successful technology transfers in microgrid energy management and advanced temperature control demonstrate the translational strength of her research. Recognized with prestigious honors, including the Best Paper Award at the Chinese Process Control Conference and championship at the Autonomous Driving Algorithm Challenge, Dr. Xu continues to pioneer next-generation control and automation technologies that drive the evolution of intelligent, efficient, and sustainable transportation ecosystems.

Profile:  Google Scholar 

Featured Publications

Mujeeb Abiola Abdulrazaq | engineering | Young Scientist Award

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Mr. Mujeeb Abiola Abdulrazaq l engineering
| Young Scientist Award

University of North Carolina at Charlotte | United States

Mr. Mujeeb Abiola’s research focuses on advancing transportation safety and efficiency through data-driven methodologies and emerging technologies. His work extensively employs large-scale traffic and crash data, including millions of federal highway administration records, to investigate the spatiotemporal dynamics of pedestrian crashes and the evolution of crash hotspots. Utilizing advanced statistical and machine learning models, he has developed predictive frameworks that outperform traditional Highway Safety Manual standards, providing robust insights into risk factors and injury severity in both human-driven and autonomous vehicle contexts. His research on connected and autonomous vehicles (CAVs) has led to the development of traffic control algorithms that significantly enhance safety, operational efficiency, and environmental sustainability in freeway work zones. Furthermore, his studies integrate GPU-accelerated data processing, simulation-based optimization, and multi-level heterogeneity modeling to evaluate vulnerable road user behavior and assess dynamic collision risks. Through simulation platforms such as VISSIM and SUMO, combined with Python-based data analysis and GIS applications, his work systematically addresses complex traffic scenarios, including merging, diverging, and weaving segments, while also accounting for seasonal variations and temporal constraints in crash determinants. His contributions include empirical analyses of autonomous vehicle incidents, methodological advancements in microsimulation accuracy, and development of actionable strategies for real-world traffic management, ultimately aiming to improve roadway safety, inform policy, and guide evidence-based planning in modern transportation systems.

Profile:  Google Scholar 

Featured Publications

  • Abdulrazaq, M. A., & Fan, W. D. (2024). Temporal dynamics of pedestrian injury severity: A seasonally constrained random parameters approach. International Journal of Transportation Science and Technology, 9.

  • Abdulrazaq, M. A., & Fan, W. (2025). A priority based multi-level heterogeneity modelling framework for vulnerable road users. Transportmetrica A: Transport Science, 1–34. https://doi.org/10.1080/23249935.2025.2516817

  • Abdulrazaq, M. A., & Fan, W. (2025). Seasonal instability in crash determinants: A partially temporally constrained modeling analysis. SSRN 5341417. https://doi.org/10.2139/ssrn.5341417

Haneen Alamirah | Engineering | Best Researcher Award

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Ms. Haneen Alamirah l Engineering
| Best Researcher Award

United Arab Emirates University | United Arab Emirates

Ms. Haneen Alamirah is an accomplished Architectural Engineer and researcher from the United Arab Emirates, specializing in occupant comfort in the built environment and sustainable building design. She holds a Bachelor’s degree in Architectural Engineering from the UAE University, a Master’s degree in Sustainable Critical Infrastructure from Khalifa University, and is currently pursuing her Ph.D. in Architectural Engineering at the UAE University . Her professional experience includes serving as a Graduate Teaching and Research Assistant at both Khalifa University and UAE University, where she has been involved in teaching, mentoring, and conducting advanced research in sustainability and human–environment interaction. Ms. Alamirah’s research contributions focus on the integration of immersive virtual environments for evaluating occupant comfort, adaptive behavior, and personal comfort models in shared spaces. Her scholarly work has been featured in high-impact journals such as Building and Environment and presented at international conferences including the Building Simulation Conference (2023, Shanghai; 2025, Brisbane) and the UAE Graduate Students Research Conference. With 68 citations and an h-index of 1 (Scopus ID: 57288505500), she continues to advance knowledge at the intersection of architecture, sustainability, and digital simulation tools, contributing to more resilient and human-centered design practices.

Profile: Scopus 

Featured Publication 

Alamirah, H. (2023, September). A bibliometric analysis of immersive virtual environment applications for occupant comfort and behavior research. In Proceedings of the Building Simulation Conference 2023 (p. 1397). Shanghai, China. https://doi.org/10.26868/25222708.2023.1397

Heyu Peng | Engineering | Best Researcher Award

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Mr. Heyu Peng | Engineering | Best Researcher Award

Xi’an Jiaotong University | China

Heyu Peng is an emerging researcher in the field of nuclear science and technology, currently pursuing his doctoral studies at the School of Nuclear Science and Technology, Xi’an Jiaotong University, China, since March . His research primarily focuses on the development and application of advanced computational methods in nuclear engineering, particularly Monte Carlo particle-transport simulations and coupled deterministic–stochastic modeling approaches. He has contributed to significant advancements in the refinement of nuclear simulation tools, demonstrating his expertise in improving accuracy, efficiency, and applicability for nuclear reactor analysis and radiation transport problems. he co-authored a paper published in IEEE Transactions on Nuclear Science that presented a coupled deterministic and Monte Carlo method for modeling and simulating self-powered neutron detectors, a study that addressed critical aspects of detector response modeling and its implications for nuclear instrumentation and monitoring. More recently, a cutting-edge computational tool designed to enhance nuclear reactor physics simulations and broaden its utility in research and practical applications. Through these publications, Peng has established himself as a promising researcher contributing to the advancement of computational nuclear science. His work reflects a strong commitment to bridging theoretical development with real-world applications, offering tools and methodologies that can improve safety, efficiency, and innovation in nuclear energy systems. As a doctoral candidate, Peng continues to expand his research profile, collaborating with experts in the field and contributing to interdisciplinary efforts in nuclear engineering. His growing academic contributions highlight his potential to become a leading researcher in nuclear science, with a focus on computational methods that can shape the future of nuclear technology and its safe, sustainable applications.

Profile: Orcid

Featured Publications

  • He, Q., Zheng, Q., Li, J., Huang, Z., Huang, J., Qin, S., Shu, H., Peng, H., Yang, X., Shen, J., et al. (2024). Overview of the new capabilities in the Monte-Carlo particle-transport code NECP-MCX V2.0. EPJ Nuclear Sciences & Technologies.

  • Zhou, Y., Cao, L., He, Q., Feng, Z., & Peng, H. (2022). A coupled deterministic and Monte-Carlo method for modeling and simulation of self-powered neutron detector. IEEE Transactions on Nuclear Science.

 

Jinzhu Shen | Engineering | Best Researcher Award

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Dr. Jinzhu Shen | Engineering | Best Researcher Award

Donghua University  | China

Jinzhu Shen is a PhD candidate in Fashion Design at Donghua University, specializing in soft robotics, machine vision, and intelligent manufacturing for garment automation. With a strong academic foundation from Jiangnan University, where she completed both her bachelor’s and master’s degrees, she has advanced her expertise in integrating cutting-edge robotics with apparel production. Currently, Jinzhu is also a visiting researcher at Universidad Politécnica de Madrid, further expanding her global research perspective. Her career bridges engineering and design, with hands-on industry experience as an R&D engineer at Rouchu Robotics, where she has contributed to the development of soft-robotic grippers, intelligent sewing systems, and fabric-handling technologies. She has published extensively in leading journals, presented at international conferences such as TIWC, and is an inventor on multiple patents. Jinzhu’s research combines creativity with innovation, aiming to revolutionize garment production processes through automation, precision, and artificial intelligence, making her a rising talent in textile engineering.

Profile

Orcid

Education 

Jinzhu Shen educational background reflects a strong commitment to innovation and interdisciplinary research in fashion technology. She is currently pursuing a PhD in Fashion Design at Donghua University, focusing on robotic automation and AI-driven garment manufacturing systems. During her doctoral studies, she participated in an international visiting research program at Universidad Politécnica de Madrid, where she expanded her expertise in soft robotics and advanced textile engineering. Prior to this, Jinzhu earned both her bachelor’s and master’s degrees in Fashion Design from Jiangnan University, where she gained comprehensive knowledge in garment engineering, textile science, and design technology. Her studies laid a strong foundation in apparel production methods, computational modeling, and product innovation. Throughout her academic journey, Jinzhu has combined engineering principles with design thinking, demonstrating strong analytical and creative skills. Her international exposure and advanced research training have positioned her at the forefront of integrating emerging technologies into the textile and fashion industry.

Experience 

Jinzhu Shen has developed a unique blend of academic and industry experience, contributing significantly to textile automation and robotics innovation. She currently serves as an R&D engineer at Suzhou Rouchu Robotics, where she has worked on advanced soft robotic fingers, intelligent sewing systems, and machine vision algorithms for fabric handling. Her research and engineering efforts focus on designing robotic solutions to improve garment manufacturing efficiency, precision, and sustainability. Jinzhu’s contributions include simulation of robotic gripping forces, development of autonomous sewing strategies, and integration of AI-based vision systems. She has also led and contributed to multiple funded projects, collaborating with academic institutions and industry partners. In addition to her engineering role, her doctoral and visiting researcher positions have enabled her to publish in top-tier journals, present at prestigious conferences, and secure patents. Her experience demonstrates a deep understanding of fashion design, robotics, and automation, positioning her as an innovative leader in textile engineering.

Awards and Honors 

Jinzhu Shen has received multiple awards and scholarships in recognition of her academic excellence, research innovation, and contributions to textile technology. She was awarded the prestigious Taicang YIDAO Clothing Scholarship for two consecutive years, highlighting her leadership in garment automation research. Earlier, she earned the Outstanding Poster Award at the Apparel Science and Technology Academic Exchange Conference, showcasing her impactful contributions to apparel robotics. Throughout her studies at Jiangnan University, Jinzhu consistently demonstrated excellence, earning several academic scholarships, including second- and third-class honors. She was also recognized as a merit student, reflecting her strong academic performance and leadership. Her achievements extend beyond academics, with multiple patents credited to her name, underscoring her role as an innovator in robotic garment handling systems. These honors collectively illustrate her dedication to pushing boundaries in apparel engineering, her growing influence in textile research, and her commitment to advancing the intersection of robotics, AI, and fashion design.

Research Focus 

Jinzhu Shen research focuses on revolutionizing garment production through soft robotics, machine vision, and intelligent manufacturing systems. Her work integrates engineering precision and design innovation, aiming to fully automate the fabric handling and sewing process. She has developed robotic grippers and AI-driven vision systems capable of manipulating delicate textiles, addressing long-standing challenges in apparel manufacturing. Her doctoral studies emphasize the synergy between robotics and textiles, with a focus on fabric alignment, smoothness evaluation, and deep-learning-based automation strategies. She also investigates sustainable approaches to garment production by optimizing industrial workflows through robotics. Jinzhu’s contributions include numerous peer-reviewed publications, patents, and presentations at international conferences, demonstrating her ability to translate theoretical research into practical applications. Her interdisciplinary expertise spans computational modeling, product innovation, and industrial collaboration, positioning her as a pioneer in transforming the traditional fashion supply chain into a technology-driven ecosystem. Her research bridges design, engineering, and AI to shape the future of apparel manufacturing.

Publications

Title: Intelligent and Precise Textile Drop-Off: A New Strategy for Integrating Soft Fingers and Machine Vision Technology
Year: 2025

Title: A study on the formulation of process parameters for soft finger-assisted fabric stitching
Year: 2024

Title: A novel evaluation method of Chinese female lower body shapes based on machine learning
Year: 2024

Title: Research progress of automatic grasping methods for garment fabrics
Year: 2023

Conclusion

Jinzhu Shen exceptional research achievements, spanning academic and industrial innovation, make her a strong contender for the Best Researcher Award. Her pioneering work in soft robotics and automated garment manufacturing demonstrates a rare blend of creativity, technical depth, and practical application. With continued global engagement and leadership development, she is poised to become a transformative figure in intelligent manufacturing and fashion technology research.

Sujata Basyal | Control System | Best Researcher Award

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Ms. Sujata Basyal | Control System | Best Researcher Award

Research Assistant at Auburn University, United States

Sujata Basyal is a passionate mechanical engineer and researcher from Nepal, currently pursuing her Ph.D. at Auburn University. With a strong foundation in nonlinear control and robotics, she works at the CARE Lab developing robust, adaptive, and intelligent control strategies. Sujata’s journey spans from mechanical design roles in Nepal to cutting-edge research in the U.S. She has co-authored numerous journal and conference papers on exoskeletons, deep neural networks, and control systems. Beyond academia, she’s a community leader, active volunteer, and a dedicated advocate for women in engineering and STEM education. 🌍🤖📚

Publication Profile

Google Scholar

Academic Background

Sujata holds a Ph.D. (in progress) and an M.S. in Mechanical Engineering from Auburn University, where she’s a Graduate Research Assistant in the CARE Lab. She earned her Bachelor’s degree in Automobile Engineering from Tribhuvan University, Nepal. Her academic path is marked by merit scholarships, fellowships, and an impressive research portfolio. Through her studies, she has gained deep expertise in nonlinear systems, control theory, and rehabilitation robotics. Her educational journey reflects a blend of academic rigor and hands-on innovation, both in Nepal and the United States. 🎓🇳🇵

Professional Background

Sujata’s experience ranges from research-intensive roles in the U.S. to industry-level engineering in Nepal. At Auburn, she designs robust control systems for rehabilitation robotics. Before that, she worked as a Warranty Executive at Agni Group and as a Mechanical Design Engineer and Project Supervisor at multiple firms in Kathmandu. Her roles included product design, team leadership, and service engineering. She has also interned at Go Ford, gaining hands-on experience with vehicle diagnostics and maintenance. Her career blends practical skills, technical depth, and global exposure. 🔧🌐📈

Awards and Honors

Sujata has been recognized with prestigious honors like the Presidential Graduate Research Fellowship and EPSCoR Graduate Scholars Program at Auburn University. She received the 100+ Women Strong Travel Fellowship and multiple merit scholarships throughout her undergrad. In Nepal, she secured a national RDI grant and won robotics competitions, including at IIT Bombay and Robotics Association of Nepal. These awards reflect her excellence in academics, leadership, innovation, and her commitment to advancing women and technology in engineering. 🥇🎖️👩‍🏫

Research Focus

Sujata’s research focuses on developing robust and adaptive control strategies using Lyapunov theory, deep neural networks, and concurrent learning. Her work addresses challenges in uncertain, nonlinear, and switched dynamic systems with applications in rehabilitation robotics, such as exoskeleton control, and networked control systems. She integrates artificial intelligence and control theory to build systems that are intelligent, responsive, and resilient. Her innovative research aims to enhance human-robot interaction, particularly for medical and assistive technologies. 🤖📊🧠

Publication Top Notes

📘 Robust Control of a Nonsmooth or Switched Control Affine Uncertain Nonlinear System Using a Novel RISE-Inspired Approach
 Year: 2023 | Cited by: 4

🦿 Deep Neural Network Based Saturated Adaptive Control of Muscles in a Lower-Limb Hybrid Exoskeleton
 Year: 2023 | Cited by: 2

🧠 Neuromuscular Model-free Epistemic Risk Guided Exploration (NeuroMERGE) for Safe Autonomy in Human-Robot Interaction
 Year: 2024 | Cited by: 1

⚙️ RISE-Like Saturated Control for Non-Smooth and Switched Non-Linear Systems
 Year: 2023 | Cited by: 1

Conclusion

Sujata Basyal is an outstanding emerging researcher whose academic journey, innovative contributions, and community engagement collectively mark her as a highly deserving candidate for the Best Researcher Award. With a strong academic foundation through her ongoing Ph.D. and prior M.S. in Mechanical Engineering from Auburn University, her work focuses on nonlinear control, rehabilitation robotics, and neural networks—fields at the forefront of engineering innovation. She has authored 3 journal papers and 18+ conference publications in top-tier venues like ACC, CDC, ICORR, and IMECE, showcasing both depth and breadth of research. Her work on adaptive and Lyapunov-based control strategies not only advances theory but also translates into impactful real-world applications such as hybrid exoskeleton systems. Recognized through prestigious fellowships like the Presidential Graduate Research Fellowship and the EPSCoR GRSP, Sujata has also demonstrated excellence through national and international robotics awards. Her leadership roles, mentoring, and active membership in organizations like ASME and SWE underscore a commitment to academic, professional, and community development. In every dimension—scholarship, innovation, leadership, and impact—Sujata Basyal exemplifies the caliber of a Best Researcher Award recipient.

Pedro Pitrez | Engineering | Best Researcher Award

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Assist. Prof. Dr. Pedro Pitrez | Engineering | Best Researcher Award

Assist. Prof. Dr. Pedro Pitrez  at Assistente Convidado – FEUP , Portugal

Pedro Pitrez is a Mechanical Engineer specializing in thermal energy and internal combustion engine systems. He holds a Master’s degree and is currently completing his Ph.D. at FEUP, focusing on energy systems and mechanical engineering. Pitrez has extensive experience in both academia and industry, with a passion for research, development, and teaching. He has worked as a lecturer at UTAD and FEUP, teaching subjects such as Applied Thermodynamics and Mechanics. His professional journey includes working at INEGI, where he developed a machine for cork painting, and at EDP Geração, managing operations for hydroelectric power plants. Known for his technical expertise, Pitrez combines his engineering knowledge with a drive for innovation, contributing to various research projects, academic articles, and conferences.

Publication Profile

Scopus

🎓 Education

Pedro Pitrez’s educational background includes a Bachelor’s degree in Mechanical Engineering from UTAD, followed by a Master’s degree in Mechanical Engineering from FEUP. His Ph.D. work at FEUP focuses on the areas of energy systems and combustion. Pitrez has excelled in his academic career, achieving strong results with a Master’s thesis on preparing a Porsche 911 internal combustion engine for competition. His academic training also includes specialized research in thermal energy, reflected in his current work and studies. Furthermore, he has contributed significantly to educational platforms, having taught courses such as Applied Thermodynamics II and Mechanics III. His current research at FEUP and INEGI is an embodiment of his continuous pursuit of knowledge and advancement in the field of mechanical and energy engineering.

💼 Experience

Pedro Pitrez has an extensive professional background in both academia and industry. From March 2020 to August 2022, he worked as a researcher at INEGI, where he was involved in the development of industrial machines, including a machine for cork painting. He was responsible for designing the machine’s structure and transport systems, as well as creating the control software. Additionally, Pitrez gained valuable experience in teaching at FEUP, offering courses in thermodynamics and mechanics. He has also worked at Amorim Cork Composites, where he provided academic support, including practical classes and student supervision. His professional career also includes working at EDP Geração, where he currently holds a position as an engineer in charge of planning and operations for hydroelectric power plants. Pitrez’s broad experience and academic contributions make him a well-rounded professional in mechanical engineering and energy systems.

🏆 Awards & Honors

Pedro Pitrez has received numerous accolades for his contributions to research and academia. Notably, he won the Best Paper Award at the International Conference on Technologies and Materials for Renewable Energy, Environment, and Sustainability (TMREES23) in 2023. His research work on plasma gasification and energy systems optimization has earned him recognition in both academic and professional circles. Additionally, Pitrez has presented at several high-profile conferences, such as the VII Jornadas de Engenharia Mecânica UTAD and the International Conference on Renewable Energy and Sustainability (TMREES23). His academic journey has been marked by consistent excellence, having also contributed to published articles in reputable journals such as Energy Reports and ENCIT 2020. These awards and honors reflect his impact and dedication to advancing research in mechanical engineering and sustainable energy solutions.

🔍 Research Focus

Pedro Pitrez’s research primarily focuses on energy systems, combustion processes, and sustainable energy technologies. His current work includes investigating plasma gasification for hazardous waste treatment and optimizing energy conversion processes. He has developed expertise in the numerical analysis of energy systems and the efficient production of syngas. His research is highly interdisciplinary, bridging mechanical engineering with environmental sustainability. Pitrez is particularly focused on applying energy optimization to industrial processes, as evidenced by his work on internal combustion engines and hydroelectric power plants. Additionally, his ongoing Ph.D. research explores the potential of alternative fuels in the transportation and energy sectors. His work contributes to the development of cleaner, more efficient energy systems, with practical applications in industries such as automotive, power generation, and environmental technologies. Pitrez’s dedication to advancing energy solutions aligns with his long-term vision of sustainable and efficient mechanical systems.

Publication Top Notes

  • Energy Recovery from Infectious Hospital Waste and Its Safe Neutralization

    • Authors: P. Pitrez, Pedro; E.L.M. Monteiro, Eliseu L.M.; A.I. Rouboa, Abel Ilah
    • Citations: 0 (as it is a forthcoming publication)
    • Year: 2025
    • Journal: International Journal of Hydrogen Energy

  • Numerical Analysis of Plasma Gasification of Hazardous Waste Using Aspen Plus

    • Authors: Not provided in the reference.
    • Citations: 0
    • Year: 2023
    • Journal: Energy Reports
    • Volume: 9, Pages 418-426

  • Optimization of Plasma Gasification System for Treatment of COVID-19 Hazardous Waste for Valorization of LHV and H2 Composition

    • Authors: Not provided in the reference.
    • Citations: 0
    • Year: In Review (no specific year yet)
    • Journal: Status: In Review