Wooi-Chen Khoo | Statistical Models and Inference | Best Researcher Award

Dr. Wooi-Chen Khoo | Statistical Models and Inference | Best Researcher Award

UCSI University | Malaysia

Dr. Wooi-Chen Khoo is a distinguished academician and researcher specializing in actuarial science, business analytics, and applied statistics. With expertise in statistical modeling, time series analysis, survival models, and data analytics, she has built an impressive portfolio of teaching, research, and academic leadership. She has taught across leading institutions such as UCSI University, Sunway University, and the University of Malaya, delivering both undergraduate and postgraduate programs aligned with IFoA and SoA standards. Her research integrates applied probability, statistical inference, and multidisciplinary applications, resulting in impactful publications in high-quality journals. Dr. Wooi-Chen Khoo has successfully supervised PhD and master’s candidates, guiding them toward scholarly and industry-relevant contributions. Beyond academia, she engages with professional bodies such as the Institute and Faculty of Actuaries (IFoA), the Society of Actuaries (SoA), and the Department of Statistics Malaysia (DOSM). Her outreach includes keynote lectures, panel discussions, and workshops for industries, emphasizing data-driven decision-making.

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ORCID 

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Education

Dr. Wooi-Chen Khoo’s academic foundation reflects her strong commitment to mathematics and statistics. She began her journey with a Bachelor’s degree in Mathematical Science at Universiti Sains Malaysia, followed by a Master’s degree in Mathematical Science from the same institution, where she deepened her expertise in applied statistics. She later pursued her doctoral studies at Universiti Malaya, where she completed a PhD in Applied Probability and Statistics. During this period, she refined her focus on statistical modeling of time series and mixture distributions, which became central themes in her scholarly work. Her academic training has equipped her with both theoretical depth and applied skills, enabling her to bridge the gap between pure mathematics and real-world statistical challenges. Complementing her formal education, Dr. Khoo also holds professional qualifications such as HRDF Trainer certification, Google Analytics accreditation, and affiliation with the Society of Actuaries, reflecting her interdisciplinary competence and professional credibility

Experience

Dr. Wooi-Chen Khoo has built a diverse teaching and administrative career across leading Malaysian universities. At UCSI University, she currently serves as Head of the Institute of Actuarial Science and Data Analytics, where she leads programme accreditation, curriculum development, and IFoA alignment. She previously headed the Department of Applied Statistics at Sunway University, driving new programme initiatives and accreditation processes. Earlier, she contributed as a lecturer at Universiti Malaya while pursuing her doctoral studies, strengthening her teaching of probability theory and statistical methods. Her teaching portfolio spans IFoA modules CS1, CS2, and CM1, postgraduate research methodology, and empirical modeling. She has supervised numerous final-year, Master’s, and PhD students, many of whom progressed into impactful research careers. Beyond teaching, Dr. Khoo has held roles as exam coordinator, journal reviewer, invited speaker, and panelist, highlighting her academic leadership. Her consultancy and industry outreach underscore her commitment to data-driven problem solving.

Awards and Honors

Dr. Wooi-Chen Khoo has received recognition for her academic excellence and applied research contributions. She was awarded First Place in an article writing competition organized by the Department of Statistics Malaysia (DOSM) for her work on resilience and economic growth in an ageing society, aligning statistical insights with sustainable development goals. Her research excellence was also acknowledged with a Best Paper Award at the IMT-GT International Conference on Mathematics, Statistics, and Their Applications, recognizing her innovative statistical modeling of bus travel time using the Burr distribution. Additionally, she achieved Second Runner-Up for Best Technical Paper at the Malaysian Road Conference & Exhibition and the International Road Federation Asia-Pacific Regional Congress, showcasing the practical impact of her work in transportation systems. These awards reflect her ability to integrate rigorous statistical methodologies with applied contexts, contributing not only to academia but also to national policy and industry practices.

Research Focus

Dr. Wooi-Chen Khoo’s research lies at the intersection of applied probability, statistics, actuarial science, and data analytics. Her work emphasizes statistical modeling, including mixture autoregressive models, time series of counts, and Burr distributions, with applications spanning infectious disease forecasting, unemployment analysis, insurance pricing, and urban transportation. She has published extensively in reputable international journals, demonstrating both theoretical innovation and practical relevance. In transportation studies, her research has advanced understanding of bus travel time variability and reliability, while her contributions to epidemiological modeling offer insights into disease spread and preventive strategies. She has also explored statistical frameworks for socio-economic issues, such as unemployment and insurance schemes. Her current projects expand into reinforcement learning applications and AI-driven modeling, reflecting her adaptability to emerging methodologies. By supervising postgraduate candidates and collaborating with institutions like DOSM, IFoA, and SoA, Dr. Khoo continues to bridge research, policy, and professional practice

 

Publications

 

Title: Modeling time series of counts with a new class of INAR (1) model
Year: 2017
Citation count: 36

Title: Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities
Year: 2012
Citation count: 28

Title: Quantifying bus travel time variability and identifying spatial and temporal factors using Burr distribution model
Year: 2022
Citation count: 19

Title: Coherent forecasting for a mixed integer-valued time series model
Year: 2022
Citation count: 7

Title: On the prediction of intermediate-to-long term bus section travel time with the Burr mixture autoregressive model
Year: 2024
Citation count: 6

Conclusion

Dr. Wooi-Chen Khoo is a passionate educator, accomplished researcher, and strategic academic leader whose contributions in applied probability, actuarial science, and data analytics have advanced knowledge, supported industry practices, and shaped future generations of statisticians.

Farshad Sadeghpour | Data prediction | Best Researcher Award

Dr. Farshad Sadeghpour | Data prediction | Best Researcher Award

Farshad Sadeghpour (b. 1996) 🇮🇷 is a Petroleum Engineer and Data Scientist 💻🛢️ with expertise in reservoir engineering, petrophysics, and AI applications in the energy sector. Based in Tehran, Iran 📍, he holds a Master’s and Bachelor’s in Petroleum Exploration. With extensive experience in EOR, SCAL/RCAL analysis, and machine learning, Farshad has contributed to both academic and industrial R&D at RIPI, NISOC, and PVP. He has published multiple research articles 📚, won international awards 🏆, and participated in key petroleum projects. He served in the military 🪖 and actively collaborates with academia and industry on AI-driven energy solutions.

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Education 🎓

🧑‍🎓 Master’s in Petroleum Engineering (Petroleum Exploration), Petroleum University of Technology, Abadan 🇮🇷 (2019–2022) | GPA: 18.82/20
🎓 Bachelor’s in Petroleum Engineering, Islamic Azad University (Science & Research Branch), Tehran 🇮🇷 (2015–2019) | GPA: 19.14/20
📚 Courses covered include reservoir engineering, geomechanics, well-logging, and advanced data analytics.
🛠️ Projects include CO₂ storage modeling, permeability prediction via AI, and LWD-based mud loss forecasting.
📊 Developed key industry collaborations with NISOC, RIPI, and OEID through thesis, internships, and military service projects.
💡 Honed computational and simulation skills using MATLAB, Python, COMSOL, Petrel, and ECLIPSE.
🏛️ Academic mentors: Dr. Seyed Reza Shadizadeh, Dr. Bijan Biranvand, Dr. Majid Akbari.

Experience 👨‍🏫


🔬 Computer Aided Process Engineering (CAPE) – Petroleum Reservoir Engineer (Nov 2024–Present)
🛢️ Petro Vision Pasargad – Reservoir Engineer & Lab Operator (Sep 2023–May 2024)
🧠 Research Institute of Petroleum Industry (RIPI) – Petroleum Engineer, Data Scientist (Mar 2023–Apr 2024)
🏭 National Iranian South Oil Company (NISOC) – Petroleum Engineer, Petrophysicist (Mar 2021–Nov 2024)
🧪 Internships: NIOC – Exploration Management, Oil & Energy Industries Development (OEID)
📊 Key contributions include EOR analysis, SCAL/RCAL lab testing, permeability modeling, machine learning pipelines, and field data analysis.
🧾 Delivered reports, simulations, and AI models supporting production optimization and reservoir characterization.

Awards & Recognitions 🏅

🥉 3rd Prize Winner – EAGE Laurie Dake Challenge 2022 (Madrid, Spain) 🌍
🎖️ Recognized for thesis excellence in AI-driven mud loss prediction with NISOC collaboration
📌 Acknowledged during military service project with RIPI for developing ANN-based well log models
🏅 Published in high-impact journals such as Energy, Geoenergy Science and Engineering, and JRMGE
✍️ Co-author of multiple peer-reviewed papers and under-review articles across petroleum engineering disciplines
🔬 Worked alongside top researchers including Dr. Ostadhassan, Dr. Gao, and Dr. Hemmati-Sarapardeh
🛠️ Actively participated in multidisciplinary teams combining AI, geomechanics, and petrophysics
📢 Regular presenter and contributor at petroleum conferences and AI-in-energy seminars.

Research Interests 🔬

📌 AI & ML applications in petroleum engineering 🧠🛢️ – including ANN, genetic algorithms, and deep learning
📊 Mud loss zone prediction, formation permeability modeling, CO₂ storage feasibility using ML
🧪 Experimental rock mechanics: nanoindentation, geomechanical upscaling, SCAL/RCAL testing
📈 Petrophysical property estimation in carbonate and unconventional reservoirs
🌍 Reservoir simulation, LWD analysis, and smart data integration using Python, Petrel, COMSOL
📖 Notable studies include: elastic modulus upscaling, kerogen behavior under pyrolysis, RQI/FZI modeling
🔬 Interdisciplinary projects bridging data science with geoscience and reservoir engineering
🤝 Collaboration with academic and industry leaders to develop practical, AI-driven solutions for energy challenges.

Publications 
  • Elastic Properties of Anisotropic Rocks Using an Stepwise Loading Framework in a True Triaxial Testing Apparatus

    Geoenergy Science and Engineering
    2025-04 | Journal article
    CONTRIBUTORS: Farshad Sadeghpour; Hem Bahadur Motra; Chinmay Sethi; Sandra Wind; Bodhisatwa Hazra; Ghasem Aghli; Mehdi Ostadhassan
  • Storage Efficiency Prediction for Feasibility Assessment of Underground CO2 Storage: Novel Machine Learning Approaches

    Energy
    2025-04 | Journal article
    CONTRIBUTORS: Farshad Sadeghpour
  • A new petrophysical-mathematical approach to estimate RQI and FZI parameters in carbonate reservoirs

    Journal of Petroleum Exploration and Production Technology
    2025-03 | Journal article
    CONTRIBUTORS: Farshad Sadeghpour; Kamran Jahangiri; Javad Honarmand
  • Effect of stress on fracture development in the Asmari reservoir in the Zagros Thrust Belt

    Journal of Rock Mechanics and Geotechnical Engineering
    2024-11 | Journal article
    CONTRIBUTORS: Ghasem Aghli; Babak Aminshahidy; Hem Bahadur Motra; Ardavan Darkhal; Farshad Sadeghpour; Mehdi Ostadhassan
  • Comparison of geomechanical upscaling methods for prediction of elastic modulus of heterogeneous media

    Geoenergy Science and Engineering
    2024-08 | Journal article
    CONTRIBUTORS: Farshad Sadeghpour; Ardavan Darkhal; Yifei Gao; Hem B. Motra; Ghasem Aghli; Mehdi Ostadhassan

Nuo Yu | Radiomics | Best Researcher Award

Ms. Nuo Yu | Radiomics | Best Researcher Award

Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College ,China

Nuo Yu is a Ph.D. candidate at the Cancer Institute and Hospital of the Chinese Academy of Medical Sciences, specializing in radiation oncology with a focus on esophageal squamous cell carcinoma (ESCC). His research primarily explores innovative chemoradiotherapy regimens to improve treatment outcomes for patients with locally advanced ESCC.

Yu has contributed to several peer-reviewed publications in SCI-indexed journals. Notably, he co-authored a study titled “Conversion Chemoradiotherapy Combined with Nab-Paclitaxel Plus Cisplatin in Patients with Locally Advanced Borderline-Resectable or Unresectable Esophageal Squamous Cell Carcinoma: A Phase I/II Prospective Cohort Study,” published in Strahlentherapie und Onkologie in August 2024. This research evaluated the efficacy and safety of a novel chemoradiotherapy regimen, demonstrating promising results in locoregional control and overall survival rates.

In March 2023, Yu co-authored another significant study, “Efficacy and Safety of Concurrent Chemoradiotherapy Combined with Nimotuzumab in Elderly Patients with Esophageal Squamous Cell Carcinoma: A Prospective Real-world Pragmatic Study,” published in Current Cancer Drug Targets. This research focused on treatment strategies for elderly patients with ESCC, highlighting the potential benefits of combining chemoradiotherapy with nimotuzumab.

Yu’s work has been recognized at international conferences, including presentations at the American Society for Radiation Oncology (ASTRO), the Federation of Asian Organizations for Radiation Oncology (FARO), and the Korean Society for Radiation Oncology (KOSRO). These engagements underscore his active participation in the global radiation oncology community and his commitment to advancing cancer treatment research.

While still in the early stages of his career, Yu’s focused research on ESCC and his contributions to the field of radiation oncology position him as a promising candidate for the Best Researcher Award. Continued efforts to expand his research scope, increase publication impact, and assume leadership roles in larger-scale studies will further strengthen his candidacy.

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Scientific Publications