Massimo Giannini | Regional Science | Best Researcher Award

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Prof Dr. Massimo Giannini | Regional Science | Best Researcher Award

Professor at University of Rome Tor Vergata, ItalyΒ 

Massimo Giannini is a distinguished Full Professor of Economic Policy at the University of Rome β€œTor Vergata,” where he is affiliated with the Department of Enterprise Engineering. With a prolific career in economic research, he has made significant contributions to the fields of economic policy, endogenous growth, and income distribution. His academic journey includes extensive teaching and research roles, along with notable professional engagements and consultancy in macroeconomic studies and fiscal policy.

Author Profile

ORCID Profile

Education

Massimo Giannini graduated with honors (110/110 cum laude) in Economic Policy from the University of Rome La Sapienza. He pursued post-graduate studies in the Theory of Controlled Systems at the Faculty of Mathematics, University of Rome La Sapienza. He completed his Doctorate in Economic Policy at the same university with a dissertation on Endogenous Growth and Personal Income Distribution, which was awarded as the best dissertation in 1996, developed at Nuffield College, University of Oxford.

Research Focus

Massimo Giannini’s research primarily revolves around economic policy, endogenous growth, personal income distribution, fiscal policy, economics of education, and labor economics. He has a keen interest in applying stochastic calculus and dynamic optimization in economic models, as well as investigating the empirical aspects of fiscal policy in Italy.

Professional Journey

Massimo Giannini’s professional journey includes teaching various undergraduate and postgraduate courses in economic policy, development economics, political economy, and applied econometrics. He has held visiting positions at prestigious institutions such as Nuffield College, Oxford University, NYU, LSE, Carlos III, and Toulouse. His roles also include significant professional activities such as Chief Econometrician for the Osservatorio e Centro di Studi Macroeconomici and consultant for the Italian Ministry of Economics.

Honors & Awards

Throughout his career, Massimo Giannini has received numerous accolades, including the award for the best dissertation in Economic Policy in 1996. He has been involved in several European research projects and has held various esteemed positions, such as Head of the Department in Educational Science and Technology, Head of Scuola IaD (E-learning unit), and Rector Delegate for E-Learning at the University of Rome Tor Vergata.

Publications Noted & Contributions

Massimo Giannini has authored and co-authored numerous publications across various topics in economics. His notable works include studies on stochastic calculus in economics, fiscal policy in Italy, endogenous growth, personal income distribution, the economics of education, and labor economics. Key publications include articles in journals such as the Journal of Economic Dynamics and Control, International Journal of Manpower, Economic Modelling, Bulletin of Economic Research, and Spatial Economic Analysis.

How does firms’ broadband adoption affect regional TFP in Italy?

Title: How does firms’ broadband adoption affect regional TFP in Italy?
Journal: Economia Politica
Date: 2023-10
DOI: 10.1007/s40888-022-00269-5
Contributors: Massimo Giannini, Barbara Martini, Cristiana Fiorelli

This study investigates the impact of firms’ broadband adoption on regional total factor productivity (TFP) in Italy. The research explores how increased broadband access and usage by firms enhance productivity through improved efficiency, innovation, and communication. By leveraging regional data and advanced econometric models, the study provides evidence on the positive correlation between broadband adoption and regional economic performance, emphasizing the importance of digital infrastructure in boosting productivity and economic growth at the regional level.

Ageing in the labour market: a spatial VAR approach

Title: Ageing in the labour market: a spatial VAR approach
Journal: Spatial Economic Analysis
Date: 2022-10-02
DOI: 10.1080/17421772.2022.2036361
Contributors: Massimo Giannini, Cristiana Fiorelli, Barbara Martini

This article examines the implications of an ageing labor market in Italy using a spatial VAR (Vector Autoregression) approach. The research addresses the spatial dynamics and interactions between aging workforce demographics and labor market outcomes, including employment rates, wage levels, and productivity. The findings highlight regional disparities and the spatial dependence of labor market variables, offering insights into policy measures aimed at mitigating the adverse effects of an aging population on regional economies.

Regional wage and productivity in Italy: a spatio-temporal analysis

Title: Regional wage and productivity in Italy: a spatio-temporal analysis
Journal: Spatial Economic Analysis
Date: 2020-10-01
DOI: 10.1080/17421772.2020.1769169
Contributors: Barbara Martini, Massimo Giannini

This study conducts a spatio-temporal analysis of regional wage and productivity disparities in Italy. By integrating spatial econometric techniques with temporal data, the research explores the relationship between wages and productivity across different Italian regions over time. The results reveal significant regional variations and the influence of spatial dependencies, underscoring the need for tailored regional policies to address productivity and wage inequalities to foster balanced economic development.

Research Timeline

Massimo Giannini’s research timeline highlights his sustained contribution to economic research from the early 1990s to the present. His early work focused on stochastic calculus and dynamic optimization, moving towards empirical studies in fiscal policy and endogenous growth in the late 1990s. In the 2000s, his research expanded into the economics of education and labor economics. From 2012 to 2019, his research activity was paused due to managerial roles at the University of Rome Tor Vergata, but he resumed with significant contributions in regional science and economic policy.

Seyede Masoomeh Hoseini | Emotional Problems | Best Researcher Award

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Ms. Seyede Masoomeh Hoseini | Emotional Problems | Best Researcher Award

Ms at Imam Khomeini International University, Iran

Seyede Masoomeh Hoseini holds a Master’s Degree in General Psychology from Imam Khomeini International University in Iran, focusing on behavioral and emotional problems in children. Her research interests primarily revolve around children’s emotional and behavioral issues, with a notable publication titled “Effectiveness of Filial Therapy on Preschool Children’s Internalization and Externalization Symptoms with an Insecure Attachment Style During Corona Virus Disease 19 in Tehran District.” This research was published in the journal Child & Family Behavior Therapy. Seyede Masoomeh Hoseini has been actively involved in research, particularly in designing research titles, collecting data, and publishing her findings. She aims to contribute significantly to the field of child psychology through her academic pursuits.

Professional Profiles

Education

Seyede Masoomeh Hoseini graduated with a Master’s Degree in General Psychology from Imam Khomeini International University in Iran.

Professional Experience

Currently affiliated with Imam Khomeini International University, Seyede Masoomeh Hoseini focuses on research in the field of children’s emotional and behavioral problems.

Research Interest

Seyede Masoomeh Hoseini, holding a Master’s Degree in General Psychology from Imam Khomeini International University in Iran, focuses her research on behavioral and emotional problems in children. Her work delves into understanding the various challenges children face in their emotional and behavioral development. Specifically, she explores the effectiveness of therapeutic interventions, such as filial therapy, in mitigating internalization and externalization symptoms among preschool children, particularly those with insecure attachment styles. Her research is timely, addressing the impact of environmental factors like the COVID-19 pandemic on children’s psychological well-being. Through her studies, Hoseini aims to contribute meaningful insights into improving the psychological support and interventions available for young children facing emotional difficulties.

Research Skills

Seyede Masoomeh Hoseini, holding a Master’s Degree in General Psychology from Imam Khomeini International University in Iran, has demonstrated a strong commitment to researching behavioral and emotional issues in children. Her academic journey includes significant contributions, notably as the first author of research investigating the effectiveness of Filial Therapy on preschool children’s internalization and externalization symptoms, particularly within the context of insecure attachment styles during the COVID-19 pandemic in Tehran. This work, published in the esteemed journal Child & Family Behavior Therapy, underscores her expertise in child psychology and therapeutic interventions. Seyede’s dedication extends beyond academia; she has actively participated in designing research studies, collecting data, and publishing findings, reflecting her profound engagement in advancing knowledge in child psychology. Her contributions exemplify a rigorous approach to research methodology and a commitment to addressing critical issues affecting children’s mental health, making her a valuable asset in the field of psychology.

 

 

FahadAL Dhabaan | Environmental Science | Best Researcher Award

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FahadAL Dhabaan | Environmental Science | Best Researcher Award

Prof. FahadAL Dhabaan, Shaqra University, Saudi Arabia.

Guda Vanitha | Computer Science | Best Researcher Award

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Dr. Guda Vanitha | Computer Science | Best Researcher Award

Associate Professor, Chaitanya Bharathi Institute of Technology,(A), India

Dr. G. Vanitha is an accomplished educator and Assistant Professor in the Department of Computer Science Engineering at Chaitanya Bharathi Institute of Technology. With 17 years of teaching experience, she holds a Ph.D. in Computer Science Engineering from Jawaharlal Nehru Technological University, Hyderabad. Her research focuses on Natural Language Processing, particularly in event time relation extraction. Dr. Vanitha has authored a textbook, holds multiple patents, and has received numerous awards for her contributions to academia.

Profile

Google Scholar

 

πŸŽ“ Education:

Dr. Vanitha completed her Ph.D. in Computer Science Engineering from Jawaharlal Nehru Technological University, Hyderabad in 2021. She also holds an M.Tech in Computer Science Engineering (2012) and a B.Tech in Computer Science Engineering (2006) from Bharat Institute of Engineering Technology, JNTUH, Hyderabad. Additionally, she pursued a Diploma in Computer Science Engineering and completed her SSC from the Board of Secondary School of Education.

πŸ’Ό Experience:

She has been serving as an Assistant Professor in Computer Science and Engineering at Chaitanya Bharathi Institute of Technology since April 2007. Prior to this, she held an ad-hoc position in the same department from August 2006 to April 2007.

πŸ”¬ Research Interests:

Dr. Vanitha’s research interests include Language Theory, Data Engineering, Machine Learning, and Artificial Intelligence. Her work focuses on developing frameworks for event extraction and representation in natural language texts.

πŸ† Awards:

Dr. Vanitha received the “Pre-eminent Researcher National Award 2022” from Chennai Teacher’s Council (CTC) in recognition of her outstanding contributions to research.

πŸ“š Publications:

Covid19 Patterns Analyzation Using Machine Learning, International Journal of Interdisciplinary Cycle Research (JICR), 2021.

Building Graph for Events and Time in Natural Language Text, International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2020.

Heart Disease Prediction Using Hybrid Technique, Journal of Interdisciplinary Cycle Research (JICR), 2020.

Event Extraction And Classification From English Articles, International Journal of Recent Technology and Engineering (IJRTE), 2019.

Event-Time Relation in Natural Language Text, International Journal of Engineering and Advanced Technology (IJEAT), 2019.

Performance Analysis of Learning Models on Medical Documents, International Journal of Innovative Research in Technology (IJIRT), 2018.

 

Yurou Wang | Motivation | Best Researcher Award

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Assist Prof Dr. Yurou Wang | Motivation | Best Researcher Award

Β Assistant Professor at The University of Alabama, United StatesΒ 

Dr. Yurou Wang is an Assistant Professor of Educational Psychology at the University of Alabama, specializing in motivational theories, educational psychology, and developmental psychology. He holds a Ph.D. in Educational Psychology from the University of Kansas, with research focused on learning beliefs, motivation internalization, and educational contexts across different cultures. Dr. Wang’s expertise includes self-determination theory, emotions in achievement settings, and large-scale educational assessments. He has published extensively in peer-reviewed journals, led research projects on student emotions and educational reforms, and mentored graduate students in educational research. Active in professional service and editorial roles, Dr. Wang contributes significantly to the field through teaching, research, and academic leadership.

Author Profile

Google Scholar Profile

Education

Dr. Yurou Wang earned a Doctor of Philosophy in Educational Psychology from the University of Kansas in 2019, focusing on the roles of learning beliefs and motivation internalization among Western and East Asian students. Prior to this, he completed a Master of Arts in Education at the University of Durham, UK, where he conducted an ethnographic study on Chinese university students serving as short-term volunteer teachers in rural areas. His academic journey began with a Bachelor of Arts in English from Dalian University of Foreign Languages, China, with a minor in International Trade.

Research and Teaching Interests

Dr. Wang’s primary expertise lies in motivational theories like self-determination theory and basic psychological needs, emotions in achievement and cognitive contexts, motivation interventions, and life-span development with a focus on childhood and adolescence. His secondary expertise includes learning persistence, international large-scale assessments (PISA, TIMSS), structural equation modeling, and experimental design.

Professional Experience

Since 2019, Dr. Wang has served as an Assistant Professor at the University of Alabama, teaching courses in developmental, social, and educational psychology. He supervises Graduate Teaching Assistants and contributes to the Master’s program in Educational Psychology. Previously, he was a Graduate Teaching Assistant at the University of Kansas, where he taught sections on Adolescent and Childhood Development and managed course logistics. He also worked as an Associate Researcher at East China Normal University, focusing on large-scale testing evaluation and educational reforms in East Asia.

Publications Top Noted

Dr. Wang has published extensively in peer-reviewed journals on topics such as educational psychology, self-determination theory, learning motivation, and academic performance under different educational contexts, including the impact of COVID-19. His research contributions include articles in journals like Learning and Motivation, Current Psychology, and Behavior Research Methods. He has also authored book chapters and presented his work at numerous conferences, contributing significantly to the field of educational psychology.

Academic performance under COVID-19: The role of online learning readiness and emotional competence

Journal: Current Psychology

Cited By: 73

Year: 2023

Side effects of large-scale assessments in education

Journal: ECNU Review of Education

Cited By: 61

Year: 2019

Psychometric evaluation of a new internalization of learning motivation (ILM) scale

Journal: Current Psychology

Cited By: 12

Year: 2022

Using Mokken scaling techniques to explore carelessness in survey research

Journal: Behavior Research Methods

Cited By: 6

Year: 2023

Guarding the Past or Inventing the Future: Education Reforms in East Asia

Book Chapter: Imagining the Future of Global Education

Cited By: 6

Year: 2017

Research and Grants

As a Principal Investigator, Dr. Wang leads the Micro-Facial Expression Tracking (MET) Lab, focusing on understanding students’ emotions during problem-solving tasks. He has secured research grants such as the University of Alabama Internal ORED Small Grant for a professional development program and has been involved as a Co-PI in projects aiming to promote college students’ attitudes toward disabilities and analyze large-scale assessment data.

Teaching and Mentoring

Dr. Wang has developed and taught courses at both the University of Alabama and the University of Kansas, covering topics in personality and social development, educational psychology, and motivation. He has mentored several graduate students in their thesis projects and capstone studies, focusing on diverse topics related to educational experiences and academic performance.

Hadi Zayyani | signal processing| Excellence in Research

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Dr.Hadi Zayyani | signal processing| Excellence in Research

Chaohe Zheng is an Assistant Professor at the School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, China. He earned his Ph.D. in Energy and Power Engineering from the same institution, following his Bachelor’s degree in the field. His research primarily focuses on computational dynamics, molecular dynamics, quantum dynamics, carbon capture and utilization, and chemical looping technologies.

Profiles

scopus

 

πŸŽ“Β EducationΒ 

PhD: Sharif University of Technology, Tehran, Iran, 2005-2010 (GPA=18.01/20).Β Abroad Research Duration: INRIA-Rennes, France, March 2008-Dec 2008.Β MSc: Sharif University of Technology, Tehran, Iran, 2001-2002 (GPA: 16.22/20).Β BSc: Sharif University of Technology, Tehran, Iran, 1996-2000 (GPA: 17.13/20).Β Diploma: Tohid High School, Shiraz, Iran, 1992-1996 (GPA: 19.50/20).

πŸ†Β Honors

Ranked 1st in High School among nearly 100 students, Shiraz, 1996. Ranked 5th in National BSc University Entrance Exam among nearly 1 million students, 1996. Ranked 13th in National MSc University Exam (Electrical Engineering), 2001. Selected as a national talent by Iran National Talent Organization. Winner of research grant for abroad PhD duration from Iran Telecommunication Research Center, 2008. Winner of Dr. Ashtiani’s grant for young assistant professors, Iran National Talent Organization, 2012. Winner researcher of Qom province in Engineering, 2020. Selected as top 1% reviewers in Publons, 2018-2019. Selected as top 2% scientist in the world in 2021 and 2022 by researchers of Stanford University.

πŸ“šΒ Teaching Experience

Estimation Theory, Adaptive Filters, Random Processes, Signal and Systems, Communication I, Communication II, Advanced Communications, DSP, Circuit Theory II

πŸ‘¨β€πŸ«Β Supervision

2 PhD theses as principal supervisor., 1 PhD thesis as co-principal supervisor., 18 MSc theses as principal supervisor., 12 MSc theses as co-supervisor., Nearly 60 BSc projects as principal supervisor.

🌐 Research Projects

Distributed Adaptive System Identification in Networks, Qom University of Technology, 2016-2017. One Bit Compressed Sensing, Qom University of Technology, 2017-2018. Direction of Arrival Estimation in Linear Arrays in Special Cases (noncoherent, one bit data,…), Qom University of Technology, 2017-2018. One Bit Compressed Sensing in Wireless Sensor Networks (WSN), Iran National Science Foundation (INSF), 2018-2019. Graph Signal Recovery and its Applications, Iran National Science Foundation (INSF), 2019-2021. Adaptive Graph Signal Recovery and Learning, INSF, 2022-Now. Linearization Techniques of Radio Communication Systems, 2023-Now.

🏭 Industrial Projects

Digital Radio, Baseband Signal Processing (in FPGA), Micromodje Industry, 2000-2004. Digital Radio, Modem Design (in FPGA), Micromodje Industry, 2000-2004. Pulse Analyzer, Faramoj Pajouh, 2003-2004. Sharif University Satellite Corporation, Designing Communication Links, 2008-2009. Phased Array Radar, Electronic Research Center, Sharif University of Technology, 2001-2011. Modulation Classification, Zaeim Corporation, 2011-2011. Bounded Component Analysis (BCA) and Separation of Communicational Signals, Imenpardaz Corporation, 2021-2022. RSS Localization Using Hack-RFs, Advanced Lab of Communication and Signal Processing, Qom University of Technology, 2023-Now.

πŸ“– Books

“Distributed Estimation in Wireless Sensor Network,” In Persian, Publications of Qom University of Technology, 2024. “Estimation Theory,” In Preparation, In Persian, Publications of Qom University of Technology, 2024.

 

Publications

Diffusion LMS algorithm in the presence of second order nonlinearities with theoretical bounds

Authors: H. Zayyani, M. Korki

Journal: Digital Signal Processing: A Review Journal, 2024

A new practical physical layer secret key generation in the presence of an untrusted relay

Authors: M. Keshavarzi, H. Zayyani, A. Kuhestani, H. Ahmadi

Journal: Physical Communication, 2024

Graph signal recovery using variational Bayes in Fourier pairs with CramΓ©r–Rao bounds

Authors: R. Torkamani, A. Amini, H. Zayyani, M. Korki

Journal: Signal Processing, 2024

IRS-Aided Received Signal Strength Localization Using a Wireless Sensor Network

Authors: S. Motie, H. Zayyani, M. Korki

Journal: IEEE Communications Letters, 2024

Forensic discrimination between traditional and compressive imaging by blurring kernel investigation

Authors: A. Taimori, H. Zayyani, F. Marvasti

Journal: Multimedia Tools and Applications, 2024

A Robust Stable Laplace Continuous Mixed Norm Adaptive Filter Algorithm

Authors: H. Zayyani, M. Korki, A. Taghavi

Journal: IEEE Sensors Letters, 2024

A Robust Markovian Block Sparse Adaptive Algorithm With Its Convergence Analysis

Authors: Z. Habibi, H. Zayyani, M. Korki

Journal: IEEE Transactions on Circuits and Systems II: Express Briefs, 2024

Double-Proportionate Uncertainty-Aware Diffusion Algorithm for Distributed Estimation

Authors: H. Zayyani, M. Korki

Journal: IEEE Transactions on Circuits and Systems II: Express Briefs, 2024

Hidden Markov Model Decorrelated Diffusion Leaky LMS With Optimized Leaky Factor

Authors: H. Zayyani, M. Salman, M. Korki, A.A.F. Youssef

Journal: IEEE Access, 2024

A Robust Proportionate Graph Recursive Least Squares Algorithm for Adaptive Graph Signal Recovery

Authors: A.N. Sadigh, H. Zayyani, M. Korki

Journal: IEEE Transactions on Circuits and Systems II: Express Briefs, 2024 (Article in Press)

 

Marian Mitroiu| Biostatistics | Best Researcher Award

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Β Dr. Marian Mitroiu| Biostatistics | Best Researcher Award

Β Dr. Marian Mitroiu,Biogen,Switzerland

Dr. Marian Mitroiu is an esteemed professional in the field of biotechnology, currently affiliated with Biogen in Switzerland. With a robust background in (mention specific areas if known, e.g., neurology, immunology), Dr. Mitroiu brings extensive expertise to his role, contributing significantly to advancements in (mention specific areas of research or focus, e.g., neuroscience, rare diseases). His work is characterized by a commitment to innovation and a passion for improving healthcare outcomes through pioneering research and development efforts.

Author Profile

Scopus

Education

PhD, Biostatistics,Utrecht University, 2017 – 2022,Master of Science (MS), Epidemiology – Medical Statistics track,Utrecht University, 2017 – 2021,MSc, Biostatistics,Universitatea din BucureΘ™ti, 2014 – 2016,Master of Science (MSc), Pharmacovigilance (Drug Safety Monitoring),University of Medicine and Pharmacy “Iuliu HaΕ£ieganu”, Cluj-Napoca, 2013 – 2014,Resident Pharmacist, Clinical, Hospital, and Managed Care Pharmacy,University of Medicine and Pharmacy “Carol Davila”, Bucharest, 2013 – 2015

Experience:

cBiogen,Associate Director Biostatistics, Baar, Zug, Switzerland,December 2022 – Present (1 year 7 months),Senior Principal Biostatistician, Baar, Zug, Switzerland,August 2021 – November 2022 (1 year 4 months),College ter Beoordeling van Geneesmiddelen,Methodology Assessor, Utrecht, Netherlands,March 2018 – June 2021 (3 years 4 months),UMC Utrecht,PhD Candidate, Utrecht Area, Netherlands,January 2017 – June 2021 (4 years 6 months),European Medicines Agency,Trainee Biostatistics and Methodology, London, United Kingdom,November 2015 – October 2016 (1 year)

Skills:

  • Biostatistics
  • Clinical Trial Methodology
  • Estimands
  • ICH E9(R1) Guidelines
  • Epidemiology
  • Pharmacovigilance

Research Focus:

Marian Mitroiu’s research likely focuses on:,Advanced biostatistical methodologies in clinical trials,Epidemiological studies related to medical statistics,Pharmacovigilance and drug safety monitoring

Publications:

  • Simoneau, G., Mitroiu, M., Debray, T.P., Pellegrini, F., Moor, C.
    • Title: Visualizing the target estimand in comparative effectiveness studies with multiple treatments
    • Journal: Journal of Comparative Effectiveness Research, 2024, 13(2), pp. e230089
  • Leng, X., LeszczyΕ„ski, P., Jeka, S., Addison, J., Zeng, X.
    • Title: Comparing tocilizumab biosimilar BAT1806/BIIB800 with reference tocilizumab in patients with moderate-to-severe rheumatoid arthritis with an inadequate response to methotrexate: a phase 3, randomised, multicentre, double-blind, active-controlled clinical trial
    • Journal: The Lancet Rheumatology, 2024, 6(1), pp. e40–e50
  • Kersten, R.F.M.R., Γ–ner, F.C., Arts, M.P., de Gast, A., van Gaalen, S.M.
    • Title: The SNAP Trial: 2-Year Results of a Double-Blind Multicenter Randomized Controlled Trial of a Silicon Nitride Versus a PEEK Cage in Patients After Lumbar Fusion Surgery
    • Journal: Global Spine Journal, 2022, 12(8), pp. 1687–1695
  • Mitroiu, M., Teerenstra, S., Oude Rengerink, K., PΓ©tavy, F., Roes, K.C.B.
    • Title: Estimation of treatment effects in short-term depression studies. An evaluation based on the ICH E9(R1) estimands framework
    • Journal: Pharmaceutical Statistics, 2022
  • Oude Rengerink, K., Mitroiu, M., Teerenstra, S., PΓ©tavy, F., Roes, K.C.B.
    • Title: Rethinking the intention-to-treat principle: one size does not fit all
    • Journal: Journal of Clinical Epidemiology, 2020, 125, pp. 198–200
  • Mitroiu, M., Oude Rengerink, K., Teerenstra, S., PΓ©tavy, F., Roes, K.C.B.
    • Title: A narrative review of estimands in drug development and regulatory evaluation: Old wine in new barrels?
    • Journal: Trials, 2020, 21(1), 671
  • Mitroiu, M., Rengerink, K.O., Pontes, C., Van Der Lee, J.H., Roes, K.C.B.
    • Title: Applicability and added value of novel methods to improve drug development in rare diseases
    • Journal: Orphanet Journal of Rare Diseases, 2018, 13(1), 200
  • Brakenhoff, T.B., Mitroiu, M., Keogh, R.H., Groenwold, R.H.H., van Smeden, M.
    • Title: Measurement error is often neglected in medical literature: a systematic review
    • Journal: Journal of Clinical Epidemiology, 2018, 98, pp. 89–97

Gustavo Carnivali | Bioinformatic | Best Researcher Award

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Dr. Gustavo Carnivali | Bioinformatic | Best Researcher Award

Researcher at UFMG, Brazil

Gustavo SimΓ΅es Carnivali is a dedicated researcher specializing in bioinformatics, computer graphics, and computational mathematics. His work focuses on gene networks, drug repurposing for COVID-19, and data visualization techniques. With a background in computer science and multiple master’s degrees, Gustavo is currently pursuing a Ph.D. in Bioinformatics while actively contributing to research at EMBRAPA and other institutions. He has a strong publication record and has presented his work at prestigious conferences. Gustavo’s interdisciplinary expertise and innovative research contributions highlight his commitment to advancing computational sciences and bioinformatics.

Professional Profiles

Education

Gustavo SimΓ΅es Carnivali has pursued a diverse and rigorous academic path, reflecting his commitment to multidisciplinary studies. He is currently undertaking a Ph.D. in Education at Integraliza in Brazil under the guidance of Luiz Carlos Santos, alongside his ongoing Ph.D. studies in Bioinformatics at the Federal University of Minas Gerais (UFMG), supervised by Tiago Antonio de Oliveira Mendes and supported by a grant from Fundação de Amparo Γ  Pesquisa do Estado de Minas Gerais (FAPEMIG). Prior to his doctoral pursuits, Gustavo earned a Master’s degree in Computer Science at the Federal University of Juiz de Fora (UFJF), where he worked under Marcelo Bernardes Vieira’s mentorship. He also holds a Master’s degree in Education Sciences from Universidad Martin Lutero in the United States, completed in 2022 with guidance from Samuel de Oliveira Nicolau. Additionally, Gustavo achieved a Master’s degree in Computational Modeling at the National Scientific Computing Laboratory (LNCC) in Brazil, supported by a grant from Conselho Nacional de Desenvolvimento CientΓ­fico e TecnolΓ³gico (CNPq) and supervised by Artur Ziviani. His academic journey exemplifies his dedication to advancing knowledge across computer science, education, and bioinformatics fields.

Professional Experience

Gustavo SimΓ΅es Carnivali has accumulated valuable professional experience across prestigious institutions and research environments. Currently, he serves as a researcher at the Empresa Brasileira de Pesquisa AgropecuΓ‘ria (EMBRAPA), contributing to cutting-edge projects in his field. Previously, he held positions at the Universidade Federal de Minas Gerais (UFMG) and Universidade Federal de Juiz de Fora (UFJF) as a grantee, where he engaged in various research and academic activities. His roles have encompassed a range of responsibilities, from conducting research in bioinformatics and computer science to collaborating on multidisciplinary projects. Gustavo’s professional journey underscores his expertise in scientific research and his commitment to advancing knowledge in his specialized areas.

Research Interest

Gustavo SimΓ΅es Carnivali’s research interests span several key areas within bioinformatics, computer graphics, and computational mathematics. He focuses on leveraging bioinformatics tools to study genetic interactions related to diseases like Covid-19. His work extends to exploring machine learning methods for disease differentiation and developing computational models for efficient community detection in complex networks. Additionally, he engages in research aimed at understanding genetic variations and their implications in human health, showcasing a multidisciplinary approach that integrates computer science with biological sciences to address contemporary challenges in healthcare and beyond.

Award and Honors

Gustavo SimΓ΅es Carnivali has garnered significant recognition for his contributions in computational sciences and bioinformatics. He received an Honorable Mention from the Brazilian Computer Society (SBC) in 2018 for his work on efficient community detection in large-scale complex networks. Additionally, he achieved First Place at Startup Weekend JF in 2015 for his project “New Dream.” These awards underscore his expertise and innovative approach in the fields of computer science, bioinformatics, and computational mathematics.

Research Skills

Gustavo SimΓ΅es Carnivali is highly skilled in the fields of computer science, bioinformatics, and computational mathematics. His research expertise spans bioinformatics, focusing on gene networks and drug repurposing, as well as computer graphics for data visualization and computational mathematics for algorithmic development. With a background in machine learning, he applies these techniques to analyze complex datasets and model intricate networks. Gustavo is also proficient in scientific writing, having authored numerous peer-reviewed articles and presented his research at various international conferences. His interdisciplinary approach and innovative contributions underscore his commitment to advancing computational sciences and bioinformatics.

Publications

  1. Thermal Management of the Li‐Ion Batteries to Improve the Performance of the Electric Vehicles Applications
    • Authors: Vrije Universiteit Brussel
    • Year: 2022
  2. Understanding Voltage Behavior of Lithium-Ion Batteries in Electric Vehicles Applications
    • Authors: Not specified
    • Year: 2022
  3. Multi-objective particle swarm optimization and training of datasheet-based load dependent lithium-ion voltage models
    • Authors: Not specified
    • Year: 2021
  4. Reliability Evaluation of Lithium-Ion Batteries for E-Mobility Applications from Practical and Technical Perspectives: A Case Study
    • Authors: Not specified
    • Year: 2021
  5. Smart Grid in China, EU, and the US: State of Implementation
    • Authors: Not specified
    • Year: 2021
  6. Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm
    • Authors: Not specified
    • Year: 2021
  7. Novel thermal management methods to improve the performance of the Li-ion batteries in high discharge current applications
    • Authors: Not specified
    • Year: 2021
  8. PCM assisted heat pipe cooling system for the thermal management of an LTO cell for high-current profiles
    • Authors: Not specified
    • Year: 2021
  9. Battery Modelling and Energy Management of the Electric Vehicles and Renewable Energy Resources
    • Authors: Vrije Universiteit Brussel
    • Year: 2021
  10. Aluminum Heat Sink Assisted Air-Cooling Thermal Management System for High Current Applications in Electric Vehicles
    • Authors: Vrije Universiteit Brussel
    • Year: 2020

 

 

Ayesheh Enayati | neurosciences | Excellence in Research

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Dr. Ayesheh Enayati | neurosciences | Excellence in Research

assistant professor, Golestan University of Medical Sciences, Iran

Ayesheh Enayati holds a Ph.D. in Pharmacognosy from Tehran University of Medical Sciences and specializes in cardiovascular research, phytochemistry, and biotechnology. Currently based at Golestan University of Medical Sciences, she conducts research on natural products and their applications in cardiovascular health and tissue engineering.

Profile

Google Scholar

 

πŸŽ“ Education:

Ayesheh Enayati completed her Doctor of Pharmacognosy at Tehran University of Medical Sciences, Tehran, Iran. She also holds a Master of Science in Phytochemistry and a Bachelor of Science in Chemistry.

πŸ”¬ Experience:

With extensive research experience, Ayesheh conducted her doctoral thesis research at both Tehran University of Medical Sciences and Golestan University of Medical Sciences, focusing on pharmacognosy and pharmacological experiments using the Langendorff perfusion system. She serves as Director and Secretary of the STE-MI Registry Committee at the Ischemic Disorders Research Center.

πŸ” Research Interests:

Her research interests span phytochemistry, natural products, cardiovascular research, biotechnology, and heart tissue engineering.

 

πŸ“š Publications:

Roselle (Hibiscus sabdariffa L.) extract as an adjunct to valsartan in patients with mild chronic kidney disease: A double-blind randomized controlled clinical trial (2024, Avicenna Journal of Phytomedicine)

Potential antiplatelet agents with grape seed–backbone polyphenols: computational studies (2024, Natural Product Research)

Effect of Pistacia genus on gastrointestinal tract disorders: A systematic and comprehensive review (2024, Fitoterapia)

LC–MS/MS phytochemical profiling, antioxidant activity, and enzyme inhibitory of Potentilla reptans L. root: Computational studies and experimental validation (2024, Process Biochemistry)

A comprehensive review of scientific evidence of Daucus carota L. plant from the viewpoints of Persian Medicine and Current Medicine: A review study (2023, Journal of Islamic and Iranian Traditional Medicine)

Neuroprotective effect of Potentilla reptans L. root in the rat brain global ischemia/reperfusion model (Year not specified, Journal not specified)

Mahloro HopeSerepa-Dlamini | Biotechnology | Best Researcher Award

Published on by Academic Achievements

Mahloro HopeSerepa-Dlamini | Biotechnology | Best Researcher Award

Prof. Mahloro HopeSerepa-Dlamini, University of Johannebsurg, South Africa.