Lakmal Meegahapola

schoolIdiap Research Institutebar_chart#2390 Global Rank

Total Papers

HCI Rank

#2390

Research Areas

Years Active

Recent Publications

M3BAT: Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training

Meegahapola 等人提出 M3BAT 多分支对抗训练框架，实现多模态移动传感数据在不同域间的无监督自适应迁移，提升了跨域传感器数据的识别准确率。

CHI '242nd AuthorHuman Pose & Activity Recognition +2

Learning About Social Context From Smartphone Data: Generalization Across Countries and Daily Life Moments

Understanding how social situations unfold in people's daily lives is relevant to designing mobile systems that can support users in their personal goals, well-being, and activities. As an alternative to questionnaires, some studies have used passively collected smartphone sensor data to infer social context (i.e., be…

UBICOMP '231st AuthorMental Health Apps & Online Support Communities +1

Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight Countries

Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in mobile health apps. However, even though model generalization issues have been hi…

CHI '231st AuthorHuman Pose & Activity Recognition +1

Quantified Canine: Inferring Dog Personality From Wearables

Being able to assess dog personality can be used to, for example, match shelter dogs with future owners, and personalize dog activities. Such an assessment typically relies on experts or psychological scales administered to dog owners, both of which are costly. To tackle that challenge, we built a device called ``Pat…

CHI '232nd AuthorHuman Pose & Activity Recognition +1

Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK

Smartphones enable understanding human behavior with activity recognition to support people’s daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly conducted in homogeneous populations within a country. However, people are more sedent…

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