Gadissa Tokuma Gindaba | Statistical Methods | Best Researcher Award

Mr. Gadissa Tokuma Gindaba | Statistical Methods | Best Researcher Award

Haramaya University | Ethiopia

PUBLICATION PROFILE

Orcid

Mr. Gadissa Tokuma Gindaba

🎓 Chemical Engineering Lecturer & Researcher | Haramaya University

Professional Summary

A dynamic, motivated, and highly productive chemical engineering graduate with advanced research expertise and analytical skills. Mr. Gadissa is passionate about advancing research in various fields, including water and wastewater treatment, green chemistry, alternative energy sources, carbon capture, and biopesticides. With a drive to solve critical societal challenges, he aims to make a positive impact through innovative engineering solutions. His goal is to contribute as a researcher and academician in addressing complex engineering problems.

Education

🎓 M.Sc. in Chemical Engineering (Process Engineering)
Jimma University | Awarded: February 2021
CGPA: 3.89/4
Thesis: Green Synthesis, Characterization, and Application of Metal Oxide Nanoparticles for Mercury Removal from Aqueous Solution
Supervisor: Dr. Eng. Hundessa Dessalegn Demsash

🎓 B.Sc. in Chemical Engineering

Jimma University | Awarded: July 2017
CGPA: 3.65/4
Thesis: Extraction and Characterization of Natural Protein (Keratin) From Waste Chicken Feather
Supervisor: Mr. Samuel Gesesse Filate

Research Interests

💧 Water & Wastewater Treatment
🔬 Emerging Contaminants
⚗️ Advanced Oxidation Processes
🌱 Development of Alternative Energy Sources
🌍 Sustainable Packaging & Construction
🧪 Green Chemistry & Nanotechnology
💡 Catalysis & Reactions
🔬 Process Development for Bio-based Materials
🌱 Carbon Capture & Utilization

Research Experience

🧪 Synthesis & Characterization of Nanomaterials: Developed and characterized metal oxide nanoparticles via green protocols for mercury removal.
🧑‍🔬 Water Treatment Studies: Investigated Fenton-oxidation reactions for pesticide residue removal.
🔬 Material Analysis: Analyzed synthesized nanomaterials using FTIR, SEM, XRD, and TGA techniques.
📊 Statistical Analysis: Optimized parameters for heavy metal removal using Design Expert software (RSM with CCD).
🌱 Alternative Energy: Produced and optimized bioethanol from waste potato and explored renewable energy production from waste biomasses.
🌿 Biopesticides: Developed bioinsecticides from plant extracts like Vernonia amygdalina and Ricinus communis for crop protection.
💉 Chemical Analysis: Used HPLC to investigate and quantify organophosphate pesticide residues.
📝 Grant Writing & Publication: Contributed to grant writing and publishing research in peer-reviewed journals.
♻️ Waste Material Utilization: Extracted and characterized keratin from waste chicken feathers.

Work Experience

👨‍🏫 Chemical Engineering Lecturer
Haramaya University | March 2021 – Present & October 2017 – September 2018

  • Taught and presented courses including Process Dynamics, Control, Reaction Engineering, Thermodynamics, Energy Audit, and more.

  • Supervised and mentored undergraduate and graduate students on thesis projects.

  • Delivered tutorials and practical sessions for Chemical Engineering students.

  • Prepared course materials, graded exams, and evaluated student performance.

Mr. Gadissa’s expertise and passion for research in sustainable technologies and chemical engineering drive his dedication to making meaningful contributions to science and society.

📚 TOP NOTES PUBLICATIONS 

Statistical analysis and optimization of mercury removal from aqueous solution onto green synthesized magnetite nanoparticle using central composite design

Biomass Conversion and Biorefinery
2025-02 | Journal article
Contributors: Gadissa Tokuma Gindaba; Hundessa Dessalegn Demsash

Source:check_circle

Crossref

Optimization of fermentation condition in bioethanol production from waste potato and product characterization

Biomass Conversion and Biorefinery
2024-02 | Journal article
Contributors: Getachew Alemu Tenkolu; Kumsa Delessa Kuffi; Gadissa Tokuma Gindaba

Source:check_circle

Crossref

RSM‐, ANN‐, and GA‐Based Process Optimization for Acid Centrifugation Treatment of Cane Molasses Toward Mitigating Calcium Oxide Fouling in Ethanol Plant Heat Exchanger

International Journal of Chemical Engineering
2024-01 | Journal article
Contributors: Lata Deso Abo; Sintayehu Mekuria Hailegiorgis; Mani Jayakumar; Sundramurthy Venkatesa Prabhu; Gadissa Tokuma Gindaba; Abas Siraj Hamda; B. S. Naveen Prasad; Maksim Mezhericher

Source:check_circle

Crossref

Bioethanol production from agricultural residues as lignocellulosic biomass feedstock’s waste valorization approach: A comprehensive review

Science of The Total Environment
2023-06-25 | Review
Part of ISSN: 0048-9697
Contributors: Mani Jayakumar; Gadissa Tokuma Gindaba; Kaleab Bizuneh Gebeyehu; Selvakumar Periyasamy; Abdisa Jabesa; Gurunathan Baskar; Beula Isabel John; Arivalagan Pugazhendhi

Source:Self-asserted source

Gadissa Tokuma Gindaba

Green synthesis, characterization, and application of metal oxide nanoparticles for mercury removal from aqueous solution

Environmental Monitoring and Assessment
2023-01 | Journal article
Contributors: Gadissa Tokuma Gindaba; Hundessa Dessalegn Demsash; Mani Jayakumar

Fathalla Rihan | Statistical Analysis | Best Scholar Award

Prof. Fathalla Rihan | Statistical Analysis | Best Scholar Award

United Arab Emirates University | United Arab Emirates

Publication Profile

Orcid

Scopus

Google scholar

Professor Fathalla A. Rihan: A Distinguished Expert in Mathematical Sciences 📚✨

Current Position(s) & Employment History 🏫

  • Professor of Mathematics (2017–present)
    Department of Mathematical Sciences, College of Science, UAE University, UAE 🇦🇪
  • Professor of Mathematics (2011–present)
    Department of Mathematics (on leave), Faculty of Science, Helwan University, Egypt 🇪🇬
  • Associate Professor (2012–2017)
    Department of Mathematical Sciences, College of Science, UAE University, UAE
  • Assistant Professor (2008–2012)
    Department of Mathematical Sciences, College of Science, UAE University, UAE
  • Associate Professor of Mathematics (2005–2011)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt
  • Honorary Research Fellow (2000–2010)
    School of Mathematics, University of Manchester, UK 🇬🇧
  • Assistant Professor (2000–2005)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt
    (On leave for Post-Doctoral research in the UK)
  • Senior Research Fellow (2003–2006)
    Salford University, UK, in collaboration with Met Office (Reading University)
  • Research Fellow (2001–2003)
    School of Mathematics, Manchester University, UK
  • Postgraduate Studentship and Lecturer Assistant (1996–2000)
    Department of Mathematics, Manchester University, UK
  • Lecturer (1992–1996)
    Department of Mathematics, Helwan University, Egypt
  • Instructor (1987–1992)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt

Education 🎓

  • Doctor of Science (DSc) in Mathematics (2019)
    National University of Uzbekistan
    Dissertation: “Qualitative and Quantitative Features of Delay Differential Equations and Their Applications”
  • Ph.D. in Mathematics (2000)
    University of Manchester, UK
    Thesis: “Numerical Treatment of Delay Differential Equations in the Biosciences”
  • M.Sc. in Numerical Analysis (1992)
    Helwan University, Egypt
    Thesis: “Spectral and Pseudo-Spectral Method for Solving Partial Differential Equations Using Orthogonal Polynomials”
  • B.Sc. in Mathematics (1985)
    Alexandria University, Egypt, Graduated with Honours

Research Interests  On Statistical Analysis🔬

Prof. Fathalla A. Rihan leads two primary research groups:

  • Numerical Analysis & Mathematical Biology
    • Mathematical modeling of phenomena with time-lags (cell division, population dynamics, infectious diseases, etc.)
    • Numerical treatments for Ordinary, Partial, and Delay Differential Equations (DDEs), as well as Fractional Order Differential Equations
    • Parameter estimation and sensitivity analysis
  • Data Assimilation & Numerical Weather Prediction (NWP)
    • Advanced data assimilation techniques like 3DVar/4D-Var systems
    • Impact of Doppler radial velocities on analysis and forecasting

Research Projects 📊

  • 2024–2026: PI, AUA-UAEU Project: “Continuous Runge-Kutta Methods for Pantograph Delay Differential Equations”
  • 2022–2024: PI, ZU-UAEU Project: “Impact of Stochastic Noise on COVID-19 Dynamics in the UAE”
  • 2022: PI, SURE+ 2022 Program: “Mathematical Modeling of COVID-19 in the UAE”
  • 2021–2023: PI, UPAR-UAEU Project: “Quantitative Features of Delay Differential Equations in Biological Systems”
  • 2017–2019: PI, SQU/UAEU Project: “Delay Differential Models of Immune Response with Viral/Bacterial Infections”

Awards & Recognition 🏆

  • Resignation Award for Publications in Top 5% Journals (2023)
  • Member of Mohammed Bin Rashid Academy of Scientists (2021–present)
  • Top 2% World Scientist (Stanford University 2019–2022)
  • University Excellence Merit Allowance (2019–2020)
  • College Excellence Award for Service (2019–2020)
  • Distinguished Research Awards (2017–2019)
  • College Award for Scholarly Research (2014–2015)

Visitor ships 🌍

  • Research Visitor (2000–2001): Manchester University, UK
  • Research Visitor (2001): University of Hertfordshire, UK
  • Research Visitor (2003–2004): NCAR & Oklahoma Weather Center, USA

Publication Top Notes

Optimal control of glucose-insulin dynamics via delay differential model with fractional-order
    • Authors: Fathalla A. Rihan, K. Udhayakumar
    • Journal: Alexandria Engineering Journal
    • Year: 2025-02 🗓️
Modeling Hybrid Crossover Dynamics of Immuno‐Chemotherapy and Gene Therapy: A Numerical Approach
    • Authors: Muner M. Abou Hasan, Seham M. AL‐Mekhlafi, Fathala A. Rihan, Hannah A. Al‐Ali
    • Journal: Mathematical Methods in the Applied Sciences
    • Year: 2025-02-03 🗓️
Stabilization of bilinear systems with distributed delays using the Banach state space decomposition method
    • Authors: Ayoub Cheddour, Abdelhai Elazzouzi, Fathalla A. Rihan
    • Journal: IMA Journal of Mathematical Control and Information
    • Year: 2024-12-19 🗓️
Continuous Runge–Kutta schemes for pantograph type delay differential equations
    • Authors: Fathalla A. Rihan
    • Journal: Partial Differential Equations in Applied Mathematics
    • Year: 2024-09 🗓️
Fractional order delay differential model of a tumor-immune system with vaccine efficacy: Stability, bifurcation and control
    • Authors: Fathalla A. Rihan, K. Udhayakumar
    • Journal: Chaos, Solitons & Fractals
    • Year: 2023-08 🗓️

 

Niansheng Tang | Statistical Methods | Best Researcher Award

Prof Dr. Niansheng Tang | Statistical Methods | Best Researcher Award

Yunan University | China

Publication Profile

Scopus

Orcid

👨‍🏫 Early Academic Pursuits

Prof. Dr. Niansheng Tang is a distinguished scholar affiliated with Yunnan University, China. His academic journey started with a series of significant achievements and certifications, culminating in his specialization in statistical and nonlinear models. His academic foundation includes attending key international training sessions and engaging with vital academic societies that contributed to his development as a respected academic in his field.

💼 Professional Endeavors and Career

Dr. Tang’s career has been characterized by a series of high-level academic positions. From 2000 to 2020, he held various teaching and research roles, including significant appointments at Yunnan University. He has been deeply involved in statistical research, with a focus on nonlinear models, reproductive dispersion, and statistical inference for incomplete data. His roles have also included administrative and leadership positions within academic organizations and societies.

🔬 Research Focus and Contributions

Dr. Tang’s primary research focuses on statistical modeling, particularly in areas like nonlinear regression, incomplete data inference, and applications in social, economic, and biomedical studies. He has been the principal investigator for multiple funded projects from the Natural Science Foundation of China, Yunnan Province, and the National Social Science Foundation of China. His work has contributed to the understanding of complex data analysis and its application in various fields.

🌍 Impact and Influence

Dr. Tang has made significant contributions to the field of statistics, with his work influencing various sectors including social sciences, economics, and biomedical research. He has been involved with several prominent academic journals and has contributed to the dissemination of knowledge in his field. His research has impacted both theoretical and applied aspects of statistical modeling, and his efforts have been acknowledged globally.

📚 Academic Cites and Recognition

Dr. Tang’s research is widely cited, with his work featured in leading international journals. He has received multiple awards for his contributions to statistical theory and its application in diverse fields. His impact in the statistical community is reflected through various accolades, including recognition as a member of several esteemed academic bodies such as the ISI and the IMS.

💻 Technical Skills and Expertise

With expertise in statistical theory and computational methods, Dr. Tang has advanced the understanding of complex data structures through his work on generalized nonlinear models. His technical proficiency extends to research in incomplete data models and the development of inference methods applicable to small sample sizes, particularly in biomedical studies.

🎓 Teaching Experience

Throughout his career, Dr. Tang has played an important role in mentoring and educating the next generation of statisticians. He has taught various courses at Yunnan University and has supervised numerous graduate students. His teaching style combines theoretical knowledge with practical application, making him a highly regarded educator.

🏛️ Legacy and Future Contributions

Dr. Tang’s legacy in the field of statistics is built on his groundbreaking research, dedication to education, and service to academic societies. Moving forward, he aims to continue influencing the development of statistical methodologies and applying them to emerging areas such as big data analysis and artificial intelligence. His future contributions will likely continue to shape both academic and practical advancements in his field.

🔍 Ongoing Research and Projects

Dr. Tang’s recent and ongoing projects focus on the statistical analysis of reproductive dispersion models, social sciences, and biomedical research. His work continues to garner support from national funding bodies and academic institutions, ensuring the continued impact of his research.

Publication Top Notes

Federated Learning based on Kernel Local Differential Privacy and Low Gradient Sampling
    • Authors: Yi Chen, Dan Chen, Niansheng Tang
    • Journal: IEEE Access 📡
    • Year: 2025 🗓️
The impact of green digital economy on carbon emission efficiency of financial industry: evidence from 284 cities in China
    • Authors: Zhichuan Zhu, Yuxin Wan, Niansheng Tang
    • Journal: Environment, Development and Sustainability 🌍💡
    • Year: 2025 🗓️
Tuning-free sparse clustering via alternating hard-thresholding
    • Authors: Wei Dong, Chen Xu, Jinhan Xie, Niansheng Tang
    • Journal: Journal of Multivariate Analysis 📊
    • Year: 2024 🗓️
Variational Bayesian approach for analyzing interval-censored data under the proportional hazards model
    • Authors: Wenting Liu, Huiqiong Li, Niansheng Tang, Jun Lyu
    • Journal: Computational Statistics and Data Analysis 💻📉
    • Year: 2024 🗓️
Semiparametric Bayesian approach to assess non-inferiority with assay sensitivity in a three-arm trial with normally distributed endpoints
    • Authors: Niansheng Tang, Fan Liang, Depeng Jiang
    • Journal: Computational Statistics 💻📊
    • Year: 2024 🗓️

Håkan Jankensgård | Quantitative Social Science Research | Best Researcher Award

Dr. Håkan Jankensgård | Quantitative Social Science Research | Best Researcher Award

Dr. Håkan Jankensgård at Stockholm University, Sweden

Professional Profile👨‍🎓

Early Academic Pursuits 🎓

Dr. Håkan Jankensgård’s academic journey began with a strong foundation at Lund University, Sweden, where he completed both his MSc in Business Administration (2001) and later his PhD in Business Administration (2011). His dissertation, titled “Essays on Corporate Risk Management,” reflects his early academic focus on risk management, which has become the cornerstone of his research career. His education was further enriched by several specialized courses, including Lärarrollen vid universitet och högskola (2014) and The Good Lecture (2015), honing his teaching and supervisory skills.

Professional Endeavors 💼

Dr. Jankensgård’s professional career spans both academia and industry, bringing practical expertise into the classroom. From 2001 to 2003, he served as a Risk Manager at Norsk Hydro in Oslo, Norway, where he gained valuable real-world experience in corporate risk management. His consulting role at Lund, Sweden, from 2004 to 2012, deepened his understanding of corporate finance and risk strategies. This combination of academic excellence and hands-on industry experience makes him a well-rounded academic and consultant.

Contributions and Research Focus 🔍

Dr. Jankensgård’s research is centered on corporate risk management, with an emphasis on understanding how businesses navigate and mitigate financial risks. His work on the role of CEOs in risk management and his long-term study on the effectiveness of corporate risk management have made significant contributions to the field. His research has been supported by prestigious funding bodies like the Jan Wallander and Tom Hedelius Foundations, showcasing his reputation within the academic and professional community. Notably, his studies have questioned the true effectiveness of corporate risk management, offering new insights into the implementation and value of risk strategies in business.

Impact and Influence 🌍

Dr. Jankensgård’s influence extends far beyond his research. He has been actively involved in shaping the discourse on corporate finance, risk, and resilience. He regularly speaks at high-profile events, such as the Svenska Finansanalytikers Förbund and the Rotary Stockholm, and contributes to discussions on risk governance, strategy, and financial forecasting. As a member of various academic and professional committees, including his role on the FFUN committee at Lund University, he has been integral in shaping academic appointments and ensuring the integrity of academic processes.

Academic Citations 📚

Dr. Jankensgård’s research has garnered significant academic attention, with over 820 citations and an H-index of 13 on Google Scholar. His works are widely read, with 5,293 downloads on SSRN, placing him in the top 5% of authors on the platform. These numbers reflect his growing impact in the fields of corporate finance and risk management, as scholars and practitioners continue to engage with his work.

Technical Skills ⚙️

Dr. Jankensgård’s technical expertise is vast, particularly in risk management, corporate finance, and valuation. He has a deep understanding of financial markets, risk governance, and resilience strategies, all of which he integrates into his teaching and research. His ability to apply theoretical knowledge to real-world scenarios, combined with his technical proficiency in financial modeling and corporate strategy, has made him a sought-after consultant and speaker.

Teaching Experience 📚

Dr. Jankensgård’s teaching experience spans over a decade, during which he has developed and led several key courses. As the instructor and course director for courses like Managerial Finance, Corporate Risk Management, and Corporate Valuation at both Lund University and Stockholm University, he has impacted the education of hundreds of students. His courses have been highly ranked, with students consistently praising their relevance to future careers. Beyond course delivery, he is an active doctoral supervisor, guiding 8-15 thesis students annually and contributing to their academic growth.

Legacy and Future Contributions 🚀

Dr. Jankensgård’s legacy lies in his commitment to bridging theory and practice in corporate finance and risk management. As an educator, researcher, and industry expert, he continues to shape the future of the field. His ongoing research projects and speaking engagements suggest that his influence will only grow in the coming years. His contributions to understanding corporate risk, valuation, and resilience will continue to guide future research and industry practices.

YouTube Channel 📹

In addition to his academic work, Dr. Jankensgård has embraced digital media to further educate and engage with a wider audience. His YouTube channel, Jankensgard on Risk, launched in 2021, is dedicated to the theory and practice of risk management. With 250+ subscribers, it serves as an accessible platform for students, professionals, and enthusiasts interested in corporate risk strategies.

Doctoral Supervision 📝

Dr. Jankensgård is deeply involved in the academic development of doctoral students. He has supervised several PhD candidates, including Nick Christie, whose thesis explores financial constraints, risk, and investment. His active participation in doctoral committees, such as the grading of doctoral dissertations, further highlights his commitment to advancing academic knowledge and supporting the next generation of scholars.

 

Top Noted Publications 📖

Semen Gunjo | Statistics | Editorial Board member

Mr. Semen Gunjo | Statistics | Editorial Board member

Mr. Semen Gunjo at DMISS(Data management and Information Support Service), Ethiopia

👨‍🎓 Profile

SEMEN BEKELE GUNJO

EARLY ACADEMIC PURSUITS

Semen Bekele Gunjo’s academic journey began with a solid foundation in STATISTICS and ACCOUNTING. He earned his BSc in Statistics from Addis Ababa University (1998-2001) and a Master’s Degree in Statistics (2006-2008). He also completed a BA in Accounting at Rift Valley University (2016-2018) and a Master’s Degree in Economics (2013-2015).

PROFESSIONAL ENDEAVORS

With over 20 YEARS of experience, Semen has specialized in DATA QUALITY ANALYSIS and PROJECT MANAGEMENT across sectors such as EDUCATION, HEALTH, WATER, and AGRICULTURE. He has successfully led consultancy projects and served as a TEAM LEADER for various assignments, focusing on management information systems and statistical frameworks.

CONTRIBUTIONS AND RESEARCH FOCUS

Semen’s contributions include developing frameworks for effective DATA MANAGEMENT and ANALYSIS. His involvement in KEY INDICATOR VERIFICATION and DATA QUALITY ASSESSMENTS has significantly enhanced monitoring and evaluation practices. Currently, he is pursuing a PhD in DEVELOPMENTAL STUDIES with a focus on DEVELOPMENT AND ENVIRONMENT.

IMPACT AND INFLUENCE

Semen’s work has improved DATA QUALITY and management systems within Ethiopian sectors, leading to better decision-making processes. His leadership in consultancy roles has influenced POLICIES related to accountability and data integrity in governmental operations.

ACADEMIC CITATIONS

His academic contributions include various WORKING PAPERS and presentations, such as the seminar on GLASS CONTAINER PRODUCTION in Ethiopia (2023), highlighting his engagement in ACADEMIC DISCOURSE.

LEGACY AND FUTURE CONTRIBUTIONS

Semen aims to leave a legacy of enhanced DATA INTEGRITY and robust analytical frameworks. His ongoing research is set to provide insights into the relationship between DEVELOPMENT and ENVIRONMENTAL SUSTAINABILITY. He is committed to mentoring future professionals in data management and policy analysis.

📖  Top Noted Publications
Modeling the Economic Cost of Congestion in Addis Ababa City, Ethiopia
  • Authors: Gunjo, S.B., Guta, D.D., Damene, S.
    Journal: Environmental Systems Research
    Year: 2024
The Perception of Drivers and Passengers on the Socio-Economic Impacts of Traffic Congestion in Addis Ababa, Ethiopia
  • Authors: Gunjo, S.B., Guta, D.D., Damene, S.
    Journal: Urban, Planning and Transport Research
    Year: 2024

Tijani Mohammed | Statistical Methods | Best Researcher Award

Dr. Hamdi Jaballah | Statistical Methods | Best Researcher Award

Doctorate at Institut de chimie et des matériaux Paris Est, CNRS, France

Profiles

Scopus Profile
Orcid Profile
Research gate

🌟Academic Background

Hamdi Jaballah is an accomplished engineer in materials science with a Ph.D. in Physics and a Master’s in Condensed Matter Physics. With four years of experience in research and development, he specializes in cutting-edge materials for energy applications, including hydrogen storage, permanent magnets, and magnetocaloric materials for solid-state refrigeration. Proficient in Python for data analysis, Hamdi is recognized for his excellent communication, writing, and teamwork skills. Driven by innovation, he is committed to contributing to the energy, automotive, mobility, and renewable energy sectors.

🎓 Education

Hamdi earned his Doctorate in Physics and Materials Science from Université Paris Est Créteil, where he focused on synthesizing and studying new composite materials for solid-state refrigeration. He also holds a Master’s degree in Condensed Matter Physics and a Bachelor’s degree in Physics and Chemistry from Faculté des Sciences de Tunis El-Manar. His academic background laid the foundation for his expertise in materials engineering.

💼 Professional Experience

Currently a Research Engineer at the Institut de Chimie et des Matériaux Paris-Est, CNRS, Hamdi is engaged in developing innovative materials for energy applications. His work includes the fabrication of intermetallic alloys, nanomaterials for permanent magnets, and hydrogen storage materials. Previously, he volunteered as an R&D Engineer at Capgemini Engineering, where he developed prototypes for magnetic cooling. His earlier roles include being an Intern Researcher in numerical physics and materials science, where he modeled magnetic materials using DFT.

🔬 Research Interests

Hamdi is passionate about advancing materials science for sustainable energy solutions. His research focuses on hydrogen storage, aiming to develop efficient solid-state solutions for transportation decarbonization. He is also dedicated to exploring magnetocaloric and electrocaloric materials for eco-friendly refrigeration. Additionally, Hamdi is interested in creating multifunctional energy materials to enhance the performance of sustainable energy systems.

🌐 Skills and Expertise

Hamdi’s technical skills include proficiency in Python (pandas, NumPy, SciPy, Matplotlib), Mathematica, MATLAB, and various materials analysis tools. He has extensive experience in data analysis, project management, and problem-solving. Fluent in French, English, and Arabic, Hamdi excels in cross-functional communication and collaboration.

📖 Publication

Sm Substitution Effect on the Critical Behaviour of Laves Phase Gd1−xSmxCo2 Intermetallic Nearby the Ferromagnetic-Paramagnetic Phase Transition
    • Authors: S. Bellafkih, H. Jaballah, L. Bessais
    • Journal: Solid State Sciences
    • Year: 2024
Influence of Iron Substitution on Structural, Magnetic, and Magnetocaloric Properties of Tb2Fe17−xAlx Compounds Synthesized by Arc Melting
    • Authors: S. Charfeddine, I. Souid, H. Jaballah, L. Bessais, A. Korchef
    • Journal: Inorganic Chemistry Communications
    • Year: 2024
Crystal Structure Change in Magnetocaloric Compounds (Er,Nd)2Fe17
    • Authors: S. Louhichi, H. Jaballah, L. Bessais, M. Jemmali
    • Journal: Inorganic Chemistry Communications
    • Year: 2024
Structural, Magnetic and Magnetocaloric Properties of the Gd2Fe17-xCrx (x = 0, 0.5, 1 and 1.5) Compounds
    • Authors: M. Saidi, H. Jaballah, L. Bessais, M. Jemmali
    • Journal: Journal of Physics and Chemistry of Solids
    • Year: 2023
Exploring Crystal Structure, Hyperfine Parameters, and Magnetocaloric Effect in Iron-Rich Intermetallic Alloy with ThMn12-Type Structure: A Comprehensive Investigation Using Experimental and DFT Calculation
    • Authors: J. Horcheni, H. Jaballah, E. Dhahri, L. Bessais
    • Journal: Magnetochemistry
    • Year: 2023

Jinlu Liu | Bayesian Analysis | Best Researcher Award

Mr. Jinlu Liu, Bayesian Analysis, Best Researcher Award

Mr. Jinlu Liu at University of Edinburgh, United Kingdom

Professional Profile

Orcid Profile
Scopus Profile

Summary

Jinlu Liu is an accomplished statistician and researcher specializing in Bayesian nonparametric mixture models and their applications in single-cell sequencing data. With a PhD in Statistics and Artificial Intelligence from the University of Edinburgh, Jinlu has developed innovative methods for cell subtype detection and neuronal connectivity modeling. His expertise spans advanced statistical modeling, data analysis, and computational techniques, and he has made significant contributions through publications, poster presentations, and awards.

Education

  • PhD in Statistics and Artificial Intelligence, University of Edinburgh (Sep 2019 – Feb 2024)
    Research focused on constructing Bayesian nonparametric mixture models for single-cell sequencing data, with applications in detecting cell subtypes and genetic markers.
  • MSc in Data Science (Distinction), University of Edinburgh (Sep 2018 – Sep 2019)
    Specialized in Biomedical Data Science, Incomplete Data Analysis, Bayesian Theory, and Natural Language Processing.
  • BSc in Mathematics with Statistical Science (First), University College London (Sep 2015 – Aug 2018)
    Studied Mathematical Methods, Real Analysis, Bayesian Statistics, and Optimization Algorithms.

Professional Experience

  • Postdoctoral Researcher, Centre for Discovery Brain Sciences, University of Edinburgh (Feb 2024 – Present)
    Modeling neuronal connectivity using MAPseq data and Bayesian mixture models.
  • Mathematics Tutor, University of Edinburgh (Sep 2019 – Feb 2024)
    Tutored various courses, including Multivariate Analysis, Nonparametric Regression Models, and Statistical Computing.
  • Information Analyst, Public Health Scotland, National Health Service (Jan 2022 – Jul 2022)
    Developed time series algorithms and optimized R code for patient waiting times.

Research Interests

Jinlu Liu’s research interests include Bayesian nonparametric methods, statistical modeling of biological data, and computational algorithms for data analysis. He is particularly focused on applications in single-cell sequencing, neuronal connectivity, and healthcare data analysis. His work aims to develop efficient and reliable statistical methods to advance understanding in these fields.

Key Skills

  • Advanced proficiency in R, LaTeX, OpenBUGS, JAGS, and Stan
  • Intermediate skills in Python, SQL, and SAS
  • Expertise in Bayesian modeling, statistical computing, and data analysis
  • Proficient in using Slack, Zoom, and Microsoft Teams

📖 Publication Top Noted

Dr. Marta Campi | Statistical Methods | Best Researcher Award

Dr. Marta Campi, Statistical Methods, Best Researcher Award 

Doctareat at Institut Pasteur, France

Professional Profile:

Scopus Profile 
Google Scholar Profile
Orcid Profile

Summary:

Dr. Marta Campi is a Postdoctoral Researcher at Institut Pasteur with expertise in Statistical Signal Processing and Machine Learning. She specializes in developing computational optimal speech enhancement techniques for real-time application in hearing aids, particularly tailored for individuals with auditory neuropathies. Her research integrates personalized cues into model calibration for improved efficacy. With a background in financial computing and econometrics, Marta brings a diverse skill set to her research endeavors.

Education:

  • PhD in Statistical Science and Signal Processing, University College London, UK
  • MPhil in Statistics, University College London, UK
  • MRes in Financial Computing, University College London, UK
  • MSc in Financial Econometrics, University of Essex, UK
  • BSc in Mathematical Statistics and Data Management, Universita degli studi di Genova, Italy

Professional Experience:

Dr. Marta Campi has amassed a diverse and extensive professional background, spanning various research, academic, and industry roles across multiple countries. As a Postdoctoral Researcher at Institut Pasteur in Paris, France, she focuses on advancing signal processing techniques for auditory applications, particularly in the development of computational optimal speech enhancement methods for hearing aids. Marta’s expertise extends to her role as a Research Engineer at Telecom Paris, where she contributed to implementing machine learning geolocation methods for wireless device networks.

Her dedication to education is evident through her tenure as a Teaching Assistant at University College London, where she tutored courses in probability, statistics, and programming methods. Marta has also lent her expertise as a Research Assistant at Heriot-Watt University in Edinburgh, Scotland, and City University of London, enriching projects in green finance and copula functions within insurance applications, respectively.

She broadened her research horizons through international collaborations, serving as a Visiting Research Fellow at the Institute of Statistical Mathematics in Tokyo, Japan, and a Visiting Research Student at Universite Clermont Auvergne in Clermont-Ferrand, France. Marta’s industry experience includes roles as a Senior Analyst at Fortlake Asset Management in Sydney, Australia, and as a Consultant at InRobin in Edinburgh, UK, where she contributed to predictive modeling and asset maintenance monitoring.

Her earlier experience as a Junior Analyst at COSTA CROCIERE S.P.A in Genova, Italy, further enriched her analytical skills and understanding of demand forecasting and price optimization. Throughout her career, Marta has demonstrated a commitment to interdisciplinary research and innovation, bridging the gap between academia and industry to address complex challenges in statistical signal processing and machine learning.

Research Interest :

Dr. Campi’s research interests span statistical signal processing, machine learning, and auditory neuroscience, with a focus on developing innovative solutions for speech enhancement in hearing aids. She is particularly interested in leveraging personalized cues and novel signal processing techniques to address auditory neuropathies and improve the quality of life for individuals with hearing impairments. Marta’s interdisciplinary approach combines her expertise in statistical science with real-world applications, aiming to bridge the gap between cutting-edge research and clinical practice in audiology.

Publication Top Noted: