Events are an integral part of the UPH experience. Check out some of the latest news!
These are some of faculty members. For a complete list, see next page
Profile
Associate Professor of Information Systems Management within the Department of Information Systems. He earned his undergraduate degree in Informatics Engineering from Universitas Pelita Harapan, followed by both an M.B.A. and a Ph.D. from the Institute of International Management at National Cheng Kung University, Taiwan, specializing in Information Technology, Operations, and Decisions.
Dr. Widjaja’s pedagogical expertise spans a diverse range of subjects, including Management Information Systems, Digital Marketing, Consumer Behavior, and Information Systems Research Methodology. His scholarly endeavors focus on Behavioral Information Systems, Cyber-Psychology, and E-Commerce, with a contemporary emphasis on Artificial Intelligence and its human-centric implications. An accomplished researcher, his work is featured in prestigious, peer-reviewed journals such as Decision Support Systems, Computers in Human Behavior, and the International Journal of Human-Computer Interaction.
Education
Research Interest
Behavioral Information Systems, Cyber-Psychology, and E-Commerce, Artificial Intelligence and its human-centric implications
Research Pages
Profile
Distinguished Professor at Zhejiang University. He received both his Bachelor’s degree and Ph.D. degree from the College of Biomedical Engineering & Instrument Science, Zhejiang University. His research focuses on computer vision, machine learning, and 3D vision, with broad interests spanning knowledge graph embedding, multimodal learning, medical image analysis, video understanding, 3D reconstruction, and generative models. He has published in leading venues and
journals including IEEE TKDE, CVPR, NeurIPS, ECCV, SIGIR, AAAI, IEEE TBME, and
Nature-related interdisciplinary research. His work reflects a strong interdisciplinary trajectory,bridging biomedical engineering, visual computing, artificial intelligence, and large-scale intelligent systems.
Education
Research Interest
Computer Vision, Machine Learning, 3D Vision, Multimodal Learning, Generative Models, Medical Image Analysis
Research Pages
Profile
Associate Professor, earned his PhD from the School of Computer Science, the University of Birmingham, UK in 2016. His research interest lie primarily in the area of software engineering for/in Cloud and virtualised environment, software automation using AI, software product line engineering and applied AI in biomedic and business improvement. Currently working on generative AI for biomedic and software product line engineering for energy aware. His current position as program chair of Master of Informatics.
Profile
Lecturer in Computer Science with research expertise in Natural Language Processing for Indonesian and low-resource local languages, particularly Batak Toba. Academic work focuses on sentiment analysis, semantic search, extractive summarization, and deployment of Transformer-based NLP systems in educational and theological domains. Early contributions include BESKlus, a BERT-based extractive summarization model with K-Means Clustering, and applied NLP studies in semantic search for theological texts and sentiment analysis across Indonesian digital platforms.
Current research centers on bias analysis in Indonesian QA datasets and the development of a multidomain Batak Toba language corpus. Secured two internal research grants as principal investigator: one for investigating bias and fairness in Indonesian QA datasets using Transformer-based baselines, and another for building a digitized Batak Toba–Indonesian parallel corpus. Actively mentoring undergraduate research on Transformer-based text classification, question answering, and aspect-based sentiment analysis, bridging NLP research and real-world applications for underrepresented languages.
Education
Research Interest
Low-Resource Natural Language Processing, Sentiment Analysis, Dataset Curation and Bias Analysis, Natural Language Processing for Education and Theology.
Research Pages
Profile
Department Chair of Information Systems at Universitas Pelita Harapan. She is actively involved in academic leadership, teaching, curriculum development, and student project supervision in the field of information systems. Her academic interests include information systems development, human-cantered technology, UI/UX, machine learning, data analytics, and digital innovation.
She is currently pursuing doctoral studies in Technology, with a research focus on Human–AI Interaction, particularly trust calibration in agentic AI for higher education. Her work explores how agentic AI systems can support meaningful, responsible, and user-cantered learning experiences. In addition to her academic role, she is also engaged in interdisciplinary initiatives that connect technology, creativity, and industry relevance, especially in preparing students for future digital careers.
Education
Research Interest
Human–AI Interaction, Agentic AI, Trust Calibration, Higher Education Technology, Information Systems Development, UI/UX, Machine Learning, Data Analytics, Digital Innovation.
Research Pages
Profile
Associate Professor in Computer Science specializing in medical informatics, intelligent systems, and digital health technologies. His academic work focuses on developing scalable and practical healthcare solutions through the integration of IoT, artificial intelligence, and smart health systems. Early contributions include the development of hospital information systems and enterprise-scale applications across industry sectors in Indonesia and Japan.
His research emphasizes smart health environments, including IoT-based patient monitoring, Personal Health Records (PHR), and assistive technologies for individuals with disabilities. Recent work explores data-driven healthcare systems, environmental health monitoring, and computer vision applications in medical procedures. He has secured multiple research grants and intellectual property rights, demonstrating strong translational impact from research to real-world implementation. He actively leads and contributes to interdisciplinary projects bridging technology and healthcare innovation in Indonesia.
Education
Research Interest
Medical Informatics, Smart Health Systems (IoT-based), Personal Health Records (PHR), Artificial Intelligence in Healthcare, Computer Vision for Medical Applications, Assistive Technologies.
Reaserch Pages
Profile
Associate Professor in Computer Science with a strong background in electronics and control engineering, specializing in system identification, signal processing, and dynamic systems. Research focuses on integrating deep learning and physics-informed approaches to model, analyze, and control complex temporal and signal-based systems. Early work on adaptive vibration control of flexible structures established a foundation in control theory and dynamic modeling, later extended to signal processing, computer vision, and applied machine learning across healthcare, finance, and education domains. Research also explores machine learning and deep learning techniques—including reinforcement learning and transformer-based models—for natural language processing, financial analytics, and data-driven system modeling. Current work emphasizes data-driven and physics-informed system identification for vibration systems, leveraging deep learning, hybrid modeling, and digital twin technologies to develop intelligent, interpretable, and adaptive monitoring and control systems.
Education
Research Interest
System Identification, Control Systems, Signal Processing, Physics-Informed Neural Networks (PINN), Time-Series Deep Learning, Intelligent Monitoring Systems, Digital Twin, Adaptive and Intelligent Systems
Research Pages
Profile
Associate Professor in Informatics with solid educational background on software engineering and distributed system. His research expertise centers on artificial intelligence and machine learning, particularly in predictive modeling, anomaly detection, and generative AI, applied to optimize digital infrastructure such as distributed systems, learning management platforms, and real-world computing environments. He also specializes in blockchain and intelligent system integration, combining AI with areas such as education, IoT, and financial systems to develop scalable, secure, and practical solutions for complex socio-technical challenges. His publications include journal articles, conference proceedings, and applied research addressing both theoretical and practical challenges in computing systems, with a growing citation footprint and an h-index indicating consistent academic impact.
Education
Research Interest
Distributed Systems, Cloud Computing, Edge Computing, Machine Learning Systems, Data Engineering.
Research Pages
Profile
Lecturer in Computer Science with research expertise in Machine Learning, sound processing, and data analytics. Academic work focuses on developing robust and scalable machine learning models for a wide range of artificial intelligence applications, particularly those involving real-world data. Early research contributions include the optimization of sound classification methods and the development of supporting analytical frameworks. This foundation has been extended to sound-based applications such as engine failure detection and music classification, as well as monitoring crowd behavior. Research integrates signal processing techniques with data-driven approaches to produce accurate and efficient solutions. Interest lies in interdisciplinary applications of artificial intelligence that bridge engineering and real-world deployment contexts. Consistently demonstrates a commitment to advancing applied AI research with practical relevance and measurable impact, while actively contributing to teaching and mentoring in advanced data science topics.
Education
Research Interest
Machine Learning, Sound Processing, Data Analytics.
Research Pages
Profile
Lecturer in Bachelor degree of Informatics, specializing in teaching classes related to game development, multimedia, technopreneurship and user experience. Experienced with game development for 10+ years under the banner of Eterna Palace Games. Knowledgeable in using numerous game engines including Ren’Py, Tyranobuilder, RPG Maker, Unity, and Roblox Studio. Current research centers on game design, gamification, educational games, and user experience.
Education
Research Interest
Game Design, Gamification, Educational Games, User Experience
Research Pages
Profile
Lecturer in Mathematics, Algorithms and Data Structures, Computer Vision, and Machine Learning, with research expertise in facial recognition systems, neural network architectures, and automated attendance management. Academic work focuses on developing deep learning-based solutions for real-world applications, including convolutional neural networks, SSD-ResNet architectures, and hybrid transform-RBFNN methods for facial image recognition. Co-authored alongside the lead researcher, the flagship study on facial recognition-based classroom attendance has reached 242 citations, marking it as a highly cited contribution in educational technology.
Current research extends to sign language recognition using CNN, predictive modeling of stock prices with the Prophet algorithm, and sarcasm detection in Indonesian-language YouTube comments. Research interests encompass computer vision, deep learning, AI algorithms, and NLP. Active in developing intelligent attendance solutions, including masked face recognition for post-2020 scenarios. Additional contributions include library book search systems using Levenshtein distance and inventory information systems for industry partners.
Education
Research Interest
Computer Vision, Face Recognition, Machine Learning, Deep Learning (CNN, RBFNN, SSD, ResNet), Automated Attendance Systems, Indonesian Language NLP.
Research Pages
Profile
Lecturer in Informatics which research expertise is in high-performance computing, parallel algorithms, and GPU acceleration using CUDA. Academic work focuses on optimizing computationally intensive problems through efficient algorithm design and scalable parallel implementations. Early research contributions include GPU-based optimization for multistatic radar systems, which was awarded Best Paper Award in 2020. Followed by studies in security-oriented computing such as parallel pattern matching for SQL injection detection using automata-based approaches. Additional academic involvement includes coaching teams in competitive
programming, achieving an Honorable Mentions at the ACM-ICPC Regional.
Current research centers on DNA data storage systems, with emphasis on system-level optimization across both encoding and decoding pipelines. Secured research grant on CUDA-based computing for bioinformatics that includes GPU-accelerated motif generation, constraint-aware encoding strategies, and scalable reconstruction methods based on edit distance and iterative trace reconstruction. Leading DSS Research Group, their research direction aims to develop efficient end-to-end computational frameworks that integrate theoretical models with practical high-performance implementations for DNA Storage System.
Education
Research Interest
GPU Computing, Parallel Computing, CUDA Programming, DNA Data Storage System, Bioinformatics.
Reaserch Pages
Profile
Lecturer with a background in Computer Engineering, currently teaching courses in calculus, programming and Internet of Things (IoT). My academic focus combines computational thinking with real-world applications, helping students develop both analytical and practical skills. My primary research interest lies in IoT and smart city development, particularly in designing intelligent systems that enhance urban efficiency, sustainability, and quality of life. I am interested in how connected devices, data integration, and automation can support smarter infrastructure and public services.Through my teaching and research, I aim to contribute to the development of innovative, data-driven solutions that address modern urban challenges while preparing students to engage with emerging technologies.
Education
Research Interest
Internet of Things
Research Pages
Profile
Arnold joined UPH in 2002 as a lecturer in the Faculty of Computer Science, with expertise in discrete mathematics, artificial intelligence systems, management information systems, and database systems. His dedication is reflected in his nine years as Head of the Computer Systems Department and six consecutive years as Head of the Information Systems Department. His commitment to UPH is evidenced by an award recognizing ten consecutive years as a tenured lecturer. His contributions to teaching, research, and community service were recognized when he was a finalist for the Outstanding Faculty Awards in 2010.
From 2002 to 2019, he conducted extensive research in artificial intelligence, including automated reasoning, genetic algorithms, and logic puzzle solvers. Since 2020, his research has focused on information systems, particularly behavioral analysis and modeling the use of generative AI to enhance learning outcomes, mitigate negative impacts, and improve learning productivity, a shift from his prior AI research.
Education
Research Interest
Artificial Intelligence, Management Information Systems, Behavior Analysis in Information System.
Research Pages
Profile
Kusno Prasetya, Ph.D. is a lecturer in the Information Systems study program at Universitas Pelita Harapan (UPH). He earned his Bachelor’s Degree in Computer Science from Sekolah Tinggi Teknik Surabaya, followed by a Master of Information Technology (Hons) and a Doctor of Philosophy in Information Technology from Bond University, Australia. His doctoral research on massively multiplayer online games produced an influential contribution in applying artificial neural networks to bot detection which has been cited in systematic reviews on cheating detection in MMORPGs and patent by Electronic Arts Inc.
His current research interests span over the field of information systems, Internet of Things, artificial intelligence, data analytics, business intelligence, and extended reality, with recent IEEE conference publications on collaborative VR for short-range combat training and on gesture interaction validity in educational VR. He also integrates AI in education through community service activities and holds a BSI-issued ISO auditing certification alongside a professional XR development credential.
Education
Research Interest
Data science, Artificial Intelligence, Information Systems, Business Intelligence, Data Analytics, Extended Reality (XR).
Research Pages
Profile
Lecturer in Information Systems with expertise in machine learning, intelligent systems, and IT governance. Academic work focuses on developing data-driven solutions to support decision-making processes across various domains, including health and education. Recent research emphasizes the application of machine learning approaches for analyzing complex data patterns and improving the effectiveness of intelligent decision support systems.
In addition, research contributions extend to IT governance and evaluation, particularly through the application of COBIT frameworks to assess and enhance the capability and performance of information systems. Professional experience integrates academic and practical perspectives through roles in IT, marketing, and student affairs, strengthening interdisciplinary problem-solving and system implementation skills.
Current interests center on applied machine learning, digital business systems, and IT governance, with a focus on scalable, impactful, and real-world solutions within information systems.
Education
Research Interest
Machine Learning, Data Mining & Classification, Digital Business & Information Systems, IT Governance, Decision Support Systems.
Research Pages
Profile
Lecturer and IT professional in Information Systems with a specialization in Data Science and applied machine learning. Academic and professional work focuses on leveraging data analytics and artificial intelligence to support decision-making processes in educational and enterprise environments.
Research contributions include the development of predictive models for evaluating student competency using ensemble learning methods such as Random Forest, combined with visual interpretability approaches like Pythagorean Tree. Experienced in data processing, analysis, and visualization using tools such as SQL, Orange Data Mining, and Power BI.
Current interests center on AI-driven student tracking systems, personalized learning models, and intelligent decision support systems. Actively engaged in bridging practical enterprise system experience—particularly in Oracle PeopleSoft, ERP, and HRIS—with academic research to deliver scalable and impactful data-driven solutions.
Education
Research Interest
Educational Data Mining, Machine Learning, Artificial Intelligence in Education, Data Analytics, Decision Support Systems, Enterprise Information Systems.
Research Pages
Profile
Hantang Liu received his Ph.D degree from College of Computer Science and Technology, Zhejiang University, with deep expertise in deep learning and computer vision. Published at top-tier venus including Siggraph, NeurIPS, IJCAI, AAAI, and IEEE TMM. Proven track record bridging cutting-edge research and large-scale production systems——from million-scale AI video pipelines at Alibaba to leading AI study program at different entities. Experienced practitioner of AI agents and modern AI toolchains.
Education
Research Interest
Computer Graphics, Computer Vision, Generative Models, AI Agents.
Profile
Dr. Hongwei Zhang is currently a Postdoctoral Fellow at the Chinese University of Hong Kong, specializing in statistical machine learning, graph algorithms, and AI-driven biomedical data analysis. His research expertise spans stochastic processes, optimization, and generative models, with a current focus on leveraging AI to decode disease mechanisms and develop clinical diagnostic tools through multi-modal data integration. His notable contributions include developing efficient network automatic relevance determination and interpretable hypergraph neural networks. He has also engineered high-performance predictive models for siRNA silencing efficiency, achieving top-tier rankings (2/2249) in life science track of the 2nd World AI4S Prize. He has published research in several international conferences and journals, including ICML, NeurIPS, ICLR, IJCAI, and Neural Networks, and also serves as a reviewer for top-tier conferences and journals in machine learning and AI.
Education
Research Interest
Statistical Machine Learning, AI for Biomedicine & Multi-omics, Generative Models, Graph Algorithms.
Profile
PhD candidate in Statistics and Machine Learning at Fudan University with research expertise in causal inference, robust learning, and their applications in medical imaging and machine learning. Academic work focuses on designing reliable and interpretable AI systems for healthcare, particularly in disease progression modeling, survival analysis, and uncertainty-aware segmentation. Early research contributions include forecasting irreversible diseases via progression learning (CVPR 2021) and conformalized survival counterfactual prediction (ICLR 2026). Currently exploring latent causal invariant diffusion models and auto-prompting SAM with uncertainty rectification for medical image segmentation. Actively involved in reviewing for top-tier conferences including ICML, ICLR, CVPR, and MICCAI, and served as teaching assistant for advanced statistics courses at Fudan University.
Education
Research Interest
Causal Inference, Robust Learning, Medical Imaging, Survival Analysis, Uncertainty Estimation, Diffusion Models, Auto-Prompting in Segmentation, Machine Learning Systems.
Hear what our accomplished alumni have to say about their experience with us!
Read More
“If I could turn back time, I would definitely choose SI UPH again to pursue my Bachelor's degree. All faculty members were very helpful and dedicated in preparing students to face the professional world.”
“Learning information systems enables a comprehensive understanding of people, process, and technology in managing and leveraging various information technologies across industries.”
“Since entering the work life, I've really come to understand just how useful the knowledge I gained from the Information Systems program at UPH has been. Thank you to all the IS lecturers who helped me reach the point where I am today.”
“In Information Systems, I learn to bridge the gap between business and technology. I also learn to understand how technology can be leveraged to solve business problems, improve processes, and drive innovation.”
