About us

AISIA Research Lab

+6 years of experiences
+20 partners and clients
+120 publications
+10 collaborators

Our Collaborators

Our collaborators consist of exceptionally talented professors with a rich diversity of skills and expertise, each handpicked from the finest institutes across Southeast Asia, guaranteeing the highest caliber of knowledge and innovation in our work.

Cathal Gurrin
Professor from Dublin City University (DCU) (Ireland)

Dr Cathal Gurrin (@cathal) is an Associate Professor at the School of Computing, at Dublin City University, deputy head of the School of Computing, and head of the Adapt centre at DCU. His research interest is personal analytics and lifelogging (a search engine for the self). He has personally gathered a digital memory since 2006 (incl. over 18 million wearable camera images) and billions of other data points; probably the largest lifelog in the world. His research develops new types of assistive technology for healthcare, human memory and productivity enhancement. He jointly founded the international NTCIR-Lifelog, ImageCLEF-lifelog and Lifelog Search Challenge collaborative evaluation campaigns, and he is a co-organiser of the Dublin Quantified-Self meetup.

Profile Citations

Nitesh Chawla
Frank M. Freimann Professor of Computer Science and Engineering from University of Notre Dame (USA)

Nitesh V. Chawla is the Frank M. Freimann Professor of Computer Science and Engineering at the University of Notre Dame. He is an expert in artificial intelligence, data science, and network science, and is motivated by the question of how technology can advance the common good through interdisciplinary research. Chawla's research expertise lies in machine learning, data science, and network science. He is also the co-founder of Aunalytics, a data science software and cloud computing company. Chawla is a fellow of the Association for Computing Machinery (ACM) and a Fellow of the Institute of Electrical and Electronics Engineers (IEEE). One of Chawla's most recognized publications, with a citation count of over 24,000, is the research paper titled "SMOTE: Synthetic Minority Over-sampling Technique."

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Dang Nguyen Duc Tien
Associate Professor from University of Bergen (Norway)

Dr. Duc Tien Dang Nguyen is an Associate Professor of Information Science. His area of expertise is on multimedia forensics, lifelogging and multimedia retrieval. Duc Tien is the author and co-author of more than a hundred peer-reviewed research papers that have been cited over a thousand times. He has been PC member at a number of conferences, co-organizer of both the Multimedia Verification, the NTCIR Lifelog Task and the ImageClef Lifelog tasks, and co-organizer of over ten other MediaEval tasks. He is also to be the incoming General Chair of MMM 2023.

Profile Citations

Dam Khanh Hoa
Professor from University of Wollongong (Australia)

Hoa Khanh Dam is Professor, Deputy Head of School (Research) & Head of Postgraduate Studies in the School of Computing and Information Technology, University of Wollongong (UOW) in Australia. He is Co-Director for the Decision System Lab at UOW, heading its Software Analytics research program. His research interests lie primarily in the intersection of Software Engineering and Artificial Intelligence (AI), inventing and developing AI solutions for project managers, software engineers, QA teams and security analysts to improve software quality and cybersecurity, accelerate productivity and increase project success rates. His research also focuses on methodologies and techniques for developing IoT applications and autonomous AI systems.

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Ho Si Tung Lam
Associate Professor from Dalhousie University (Canada)

Dr. Lam Ho is a postdoctoral researcher working with Prof. Marc Suchard at the University of California, Los Angeles. He graduated from the University of Science, Ho Chi Minh City in 2008. He received his M.Sc. in Applied Mathematics from University of Orleans, France in 2009, and his Ph.D. in Statistics from the University of Wisconsin-Madison in 2014. He is interested in statistical methods and applications for stochastic processes. His thesis focuses on the Ornstein-Uhlenbeck diffusion process on a phylogenetic tree, which has been used extensively to model the evolution of continuous phenotypes. Currently, he is working on statistical inference for partially observed multivariate birth-death processes with applications in infectious diseases and observational health data.

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Cuong Nguyen
Assistant Professor from Florida International University (USA)

Cuong Nguyen is an Assistant Professor of the Knight Foundation School of Computing and Information Sciences, Florida International University. Before joining FIU, he was an Applied Scientist at Amazon Web Services (AWS) from 2018-2021, working on machine learning with applications to computer vision and natural language processing. His research interests include probabilistic machine learning and artificial intelligence, with applications to real-world problems in computer vision and natural language processing. He has regularly published at top conferences and journals in machine learning and artificial intelligence, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the AAAI Conference on Artificial Intelligence (AAAI), and the Journal of Machine Learning Research.

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Dao Minh Son
Senior Researcher from National Institute of Information and Communications Technology (NICT) (Japan)

He is a senior researcher of the National Institute of Information and Communications Technology (NICT), Japan. He received his Ph.D. from the University of Trento, Italy. He was a senior assistant professor (Universiti Teknologi Brunei), researcher (Trento University, Italy), and JSPS postdoc (Osaka University, Japan). His main interests include multimedia retrieval, event detection, video surveillance, data science, computer vision, and pattern recognition. He has led several national and international projects under the Society 5.0 framework. He is a PC member, (co)-chair, (co)organizer, and (co)editor in several international conferences/workshops and journals. He is a member of the MediaEval Community Council (2021), a well-known multimedia benchmarking challenge event.

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Vu Dinh
Associate Professor from University of Delaware (USA)

Vu Dinh is an associate professor in the Department of Mathematical Sciences, University of Delaware. His research focuses on applied probability/statistics and phylogenetics, with an emphasis on the development of next-generation Markov chain Monte Carlo (MCMC) methods for phylogenetic inference. He is also interested in theoretical foundations and applications of machine learning frameworks in applied sciences. From 2015-2017, he was a post-doctoral research fellow at Fred Hutchinson Cancer Research Center (Seattle, WA). He received his PhD in 2014 from Purdue University, working on computational methods for experimental design and control of biological systems. He earned his bachelor degree in 2008 from the University of Science (Ho Chi Minh City, Vietnam).

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Michael Riegler
Chief Research Scientist/Research Professor from SimulaMet (Norway)

Michael Riegler is a chief research scientist at SimulaMet. His research interests are medical data analysis and understanding, image processing, image retrieval, parallel processing, crowdsourcing, social computing and user intent. He is involved in several initiatives like the MediaEval Benchmarking initiative for Multimedia Evaluation, which runs a task on data analysis for medicine since several years.

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Pål Halvorsen
Chief Research Scientist/Research Professor from SimulaMet (Norway)

Pål Halvorsen received the Ph.D. degree from the University of Oslo, Norway, in 2001. He is currently the Chief Research Scientist with SimulaMet, Norway, a Professor with Oslo Metropolitan University, Norway, and a Professor II with the University of Oslo. At SimulaMet, he is currently leading the Department of Holistic Systems Research, which investigates the challenges of complete end-to-end pipelines with a particular focus on sports and medical applications. His current research interests include several areas in distributed (multimedia) systems and content analysis from a performance and efficiency point of view.

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Sameer Alam
Associate Professor from Nanyang Technological University - NTU (Singapore)

Sameer Alam is an Associate Professor at the School of Mechanical and Aerospace Engineering. He is the Deputy Director of Air Traffic Management Research Institute leading research on AI & Data Analytics applied to Air Transportation. He is also the Co-Director of Saab-NTU Joint Lab leading research on Machine Learning for Digital and Remote Tower. He is leading a research team of 20 scientist and 6 PhD students to create the next generation of AI-Human Hybrid ATM system. Sameer obtained PhD in Computer Sc. (2008) specializing in Artificial Intelligence from University of New South Wales (UNSW), Australia and Master's. in Computer Sc. (1999) from BIT, Mesra, India.

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Graham Healy
Assistant Professor from Dublin City University (Ireland)

Graham Healy received the B.Sc. degree (Hons.) in computer applications, in 2008, and the Ph.D. degree in brain–computer interfaces, in 2012. He worked as a Postdoctoral Researcher with The University of British Columbia, from 2012 to 2013, and The Insight Centre for Data Analytics, Dublin City University, in 2013, where he later became a Research Fellow, in 2017, and then became an Assistant Professor in computing, in 2019. He is currently an Assistant Professor with the School of Computing, Dublin City University. His research interests include the ways computerized systems can automatically detect things from people using signals, i.e., bioelectric, social, and collaborative, then do something useful with that information, and mix of basic-research with a practical focus on developing real-world applications.

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Daniel Sonntag
Professor from German Research Center for Artificial Intelligence (DFKI) (Germany)

His research interests include intelligent user interfaces, natural language processing, information retrieval and mining, dialogue systems, common-sense modelling, and semantic (explainable) machine learning methods for cognitive computing and improved usability. This includes multimodal multisensor interfaces for medical and health systems and Industry 4.0 in particular, common-sense and (interactive) machine learning methods for human computer interfaces, knowledge discovery, information extraction, and cognitive modelling with ontologies. He has published over 150 scientific articles, and has been recipient of the German High Tech Champion Award in 2011. As a principal investigator he leads both national and European projects from the Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, the Federal Ministry of Health, and Horizon 2020. His recent application of multimodal multisensor interfaces is now having industrial impact, for example SmartWeb's multimodal interaction design and technical infrastructure by Apple (Siri).

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DENIS GREBENKOV
Professor from Ecole Polytechnique (France)

Denis GREBENKOV has graduated from Saint Petersburg State University (Russia) and Ecole Polytechnique (France) after defending two PhD theses, one in statistical and the other in theoretical physics. Since 2006, Denis GREBENKOV is a permanent CNRS researcher at Laboratory of Condensed Matter Physics of Ecole Polytechnique. He is interested in understanding and modeling transport phenomena in complex systems. He developed various models, theoretical approaches and numerical tools for studying Laplacian transport towards irregular interfaces, anomalous diffusions in living cells, first passage times of intermittent surface-mediated processes in porous media, diffusion magnetic resonance imaging of lungs and brain, convective and diffusive transport in the placenta …

Profile Citations