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

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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.

Profile

ORCID 

Googlescholar

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.

Amar Salehi | Reinforcement Learning | Best Researcher Award

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Dr. Amar Salehi | Reinforcement Learning | Best Researcher Award

Dr. Amar Salehi is a postdoctoral researcher at South China University of Technology 🇨🇳, specializing in microrobotics 🤖, AI 🧠, and biosystems engineering 🌱. With a Ph.D. in Mechanical Engineering of Biosystems 🎓 from the University of Tehran 🇮🇷, he developed intelligent and independent control systems for magnetic microrobots. His work integrates machine learning, deep learning, and bio-inspired design for environmental and biomedical applications 🌍🧬. Passionate about innovation, he has contributed to several peer-reviewed journals 📚, international conferences 🌐, and interdisciplinary projects. He also served as a teaching assistant and reviewer and held leadership roles in scientific societies 👨‍🏫. A top-ranked scholar in national entrance exams 🏆, Dr. Salehi actively collaborates across borders for research and development in cutting-edge AI and robotics 🔬.

Profile

Education 🎓

Dr. Salehi earned his Ph.D. in Mechanical Engineering of Biosystems 🎓 from the University of Tehran (2019–2024), focusing on intelligent magnetic microrobot control 🤖. He completed his M.S. at Isfahan University of Technology (2013–2015) 🧪, where he explored fluid heat transfer using CFD methods and mechanical behavior modeling with neural networks. His B.S. was from Razi University (2008–2012) in Biosystems Mechanical Engineering 🔧🌾. A consistent top performer, he ranked 2nd in the Ph.D. entrance exam and 90th in the M.S. exam among thousands 🏅. His academic record features exceptional GPAs and thesis scores 🌟. Dr. Salehi’s interdisciplinary education blends mechanical systems, AI, and biology, building a strong foundation for his current microrobotics and biosensor research 🔬📊.

Experience 👨‍🏫

Experience (150 words): Dr. Salehi is currently a Postdoctoral Fellow at the Shien-Ming Wu School of Intelligent Engineering, South China University of Technology 🇨🇳 (2024–present), working on intelligent agents and microrobotics 🤖. Previously, he was a teaching assistant at the University of Tehran, supporting physics and mechanical engineering courses 👨‍🏫. He also taught part-time at Azad University, Iran (2016–2019) 📘. As a research assistant at the AIAX Lab, he contributed to AI and advanced control systems. He led several interdisciplinary projects, including a joint Iran-Turkey research on microfluidic biochips 🧫. A reviewer for “The Innovation” journal, he is proficient in tools like COMSOL, SolidWorks, Python, and statistical analysis 📊🖥️. He also chaired a student startup “Green Daal Mechanics” and served in university and parliamentary scientific committees 🚀📈.

Awards & Recognitions 🏅

Awards and Honors (150 words): Dr. Salehi received the Best Oral Presentation Award 🥇 at IRAC 2024 for his work on deep learning and microrobots 🤖. Ranked 2nd in the national Ph.D. entrance exam and 90th in the M.S. exam, he also achieved excellent scores in his thesis evaluations (Ph.D.: 19.65/20, M.S.: 19.49/20) 🏆. His academic and research excellence has earned him recognition in national and international forums 📜. He has been an active member of the Scientific Association of Biosystems Engineering and the Interdisciplinary Scientific Student Association at the University of Tehran 🧠. He also served as Editor-in-Chief of the New Green Industry Journal 🌱. With strong leadership in university-industry interaction, he contributes to Iran’s agricultural, food, and energy research panels and policy discussions 🧑‍🔬📢.

Research Interests 🔬

.Research Focus (150 words): Dr. Salehi’s research lies at the intersection of microrobotics 🤖, artificial intelligence 🧠, and biosystems 🌱. His Ph.D. work focused on intelligent, model-free control of magnetic microrobots using deep reinforcement learning in real-world environments 🔍. He explores biosensor optimization using genetic algorithms 🧬, natural language interfaces for microrobot control 🗣️, and micro/nano-systems for biomedical and environmental applications 🌍. He integrates fuzzy logic, ANN, and reinforcement learning in his predictive modeling. Ongoing research includes yield prediction in intercropping systems 🌾 and AI-driven environmental cleanup technologies. Dr. Salehi’s goal is to create autonomous, intelligent microsystems that can navigate, sense, and interact with biological and physical environments, with potential applications in diagnostics, therapy, and sustainability 🧪♻️.

Publications 

 

 

 

Vikas Palekar | Machine Leaning | Best Researcher Award

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Mr. Vikas Palekar | Machine Leaning | Best Researcher Award

 

Profile

Education

He is currently pursuing a Ph.D. in Computer Science and Engineering at Vellore Institute of Technology, Bhopal, Madhya Pradesh, since December 2018. His research focuses on developing an Adaptive Optimized Residual Convolutional Image Annotation Model with a Bionic Feature Selection Strategy. He holds a Master of Engineering (M.E.) in Information Technology from Prof. Ram Meghe College of Engineering Technology and Research, Badnera (SGBAU Amravati), which he completed in December 2012 with an impressive 88.00%, securing the first merit position in the university for the summer 2012 examination. Prior to that, he earned a Bachelor of Engineering (B.E.) in Computer Science and Engineering from Shri Guru Gobind Singhji Institute of Engineering Technology and Research, Nanded (SRTMNU, Nanded), in June 2007, achieving a commendable 74.40%.

Work experience

He is currently working as an Assistant Professor in the Department of Computer Engineering at Bajaj Institute of Technology, Wardha, since July 31, 2023. In addition to his teaching responsibilities, he serves as the Academic Coordinator of the department and has worked as a Senior Supervisor for the DBATY Winter-23 Exam at Government College of Engineering, Yavatmal.

Previously, he worked as an Assistant Professor (UGC Approved, RTMNU, Nagpur) in the Department of Computer Science and Engineering at Datta Meghe Institute of Engineering, Technology & Research, Wardha, from June 14, 2011, to June 30, 2023. During this tenure, he held the position of Head of the Department from April 21, 2016, to June 30, 2023. He taught various subjects, including Distributed Operating Systems, TCP/IP, System Programming, Data Warehousing and Mining, Artificial Intelligence, and Computer Architecture and Organization. Additionally, he contributed to university examinations as the Chief Supervisor in the Winter-2015 Examination and a committee member for the Summer-2013, Summer-2015, and Summer-2018 Examinations. He also played a key role in institutional development as a member of the Admission Committee, NBA & NAAC core committees at the department level, and as the convener of the National Level Technical Symposium “POCKET 16” organized by the CSE Department on March 16, 2016.

Earlier in his career, he served as an Assistant Professor in the Department of Computer Engineering at Bapurao Deshmukh College of Engineering, Wardha, from November 26, 2008, to April 30, 2011. He taught subjects such as Unix and Shell Programming, Object-Oriented Programming, and Operating Systems while also serving as a Department Exam Committee Member.

Achievement

He was the first university topper (merit) in M.Tech (Information Technology) and received the Best Paper Award at the 2021 International Conference on Computational Performance Evaluation (ComPE), organized by the Department of Biomedical Engineering, North Eastern Hill University (NEHU), Shillong, Meghalaya, India, from December 1st to 3rd, 2023. He has actively participated in various conferences, including presenting the paper “Label Dependency Classifier using Multi-Feature Graph Convolution Networks for Automatic Image Annotation” at ComPE 2021 in Shillong, India. He also presented his research on “Visual-Based Page Segmentation for Deep Web Data Extraction” at the International Conference on Soft Computing for Problem Solving (SocProS 2011) held from December 20-22, 2011. Additionally, he contributed to the Computer Science & Engineering Department at Sardar Vallabhbhai National Institute of Technology, Surat, by presenting “A Critical Analysis of Learning Approaches for Image Annotation Based on Semantic Correlation” from December 13-15, 2022. His work on “A Survey on Assisting Document Annotation” was featured at the 19th International Conference on Hybrid Intelligent Systems (HIS) at VIT Bhopal University, India, from December 10-12, 2022. Furthermore, he co-authored a study titled “Review on Improving Lifetime of Network Using Energy and Density Control Cluster Algorithm,” which was presented at the 2018 IEEE International Students’ Conference on Electrical, Electronics, and Computer Science (SCEECS) in Bhopal, India.

 

Publication

Mahmoud Alimoradi | Machine Learning | Best Researcher Award

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Mr. Mahmoud Alimoradi | Machine Learning | Best Researcher Award

Lahijan Azad ,Iran

He understands the growing need for Machine Learning and has a keen interest in the field, which he considers a blessing. Recognizing the importance of managing large and complex computations to control various aspects of the human environment has led him into this vast world. He is particularly fascinated by machine learning, especially reinforcement learning, supervised learning, semi-supervised learning, outliers, and basic data challenges. Furthermore, optimization, an area of artificial intelligence that requires fundamental studies and a change in approach, is another of his key research interests.

Profile

Education

He holds a Master’s degree in Artificial Intelligence Engineering from the University of Shafagh, completed in 2020. His thesis was titled “Trees Social Relations Optimization Algorithm: A New Swarm-Based Metaheuristic Technique to Solve Continuous and Discrete Optimization Problems.” He also earned a Bachelor’s degree in Software Engineering from Azad Lahijan University, which he attended from 2007 to 2011.

Research Interests

Theory: Reinforcement Learning (high-dimensional problems, regularized algorithms, model
learning,
representation learning and deep RL, learning from demonstration, inverse optimal control, deep
Reinforcement Learning); Machine Learning (statistical learning theory, nonparametric
algorithms, time series. processes, manifold learning, online learning); Large-scale Optimization;
Evolutionary Computation, Metaheuristic Algorithm, Deep Learning, Healthcare Machine
learning, Big Data, Data Problems (Imbalanced), Signal Analysis
Applications: Automated control, space affairs, robotic control, medicine and health, asymmetric
data, data science, scheduling, proposing systems, self-enhancing systems

Work Experience

He is a freelance programmer with expertise in various operating systems, including Microsoft Windows and Linux (Arch, Ubuntu, Fedora). He is proficient in software tools such as Microsoft Office, Anaconda, Jupyter, PyCharm, Visual Studio, Tableau, RapidMiner, MATLAB, and Visual Studio. His programming skills include Matlab, Python, C++, Scala, Java, and Julia, with a focus on data mining, data science, computer vision, and machine learning. He is experienced with Python libraries like Pandas, Numpy, Matplotlib, Seaborn, PyCV, TensorFlow, Time Series Analysis, Spark, Hadoop, and Cassandra. Additionally, he is skilled in using Github, Docker, and MySQL. His expertise spans machine learning, deep learning, imbalanced data, missing data, semi-supervised learning, healthcare machine learning, algorithm design, and metaheuristic algorithms. He is fluent in English and Persian.

Publications