School of Computing and Information Systems

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SMU Masters Consultation & Application Day (Jakarta, Indonesia)

Public Events Hourly Sessions: 18 May 2026: 5pm to 8pm 19 May 2026: 10am to 8pm. RSVP: . Reserve a seat: https://postgraduate.smu.edu.sg/acton/fs/blocks/showLandingPage/a/11522/p/p-03d3/t/page/fm/1. Event Details: Join us for a personalised Consultation & Application Day as you prepare for the next step in your professional and personal journey. ​ Receive an application fee waiver, personalised consultation, admission guidance, and on-site admissions interviews (selected programmes only) all within the same day. You ​are ​welcome ​to ​bring ​a ​friend ​with ​you. ​Simply ​forward ​them ​this ​registration ​link: https://postgraduate.smu.edu.sg/acton/fs/blocks/showLandingPage/a/11522/p/p-03d3/t/page/fm/3. Contact: lkcsbpg.admissions@smu.edu.sg. Type: Information Sessions. Subject: Business. Finance & Financial Markets. Innovation & Entrepreneurship. Leadership. Economics. Audience: Prospective Student. Public. Professionals. Monday, May 18, 2026 – Tuesday, May 19, 2026. SMU Indonesia The Energy Building 20th Floor, SCBD Lot 11A, Jl. Jend. Sudirman Kav. 52-53 Jakarta 12190, Indonesia.

Sequential Robustness in Adversarial Reinforcement Learning

This thesis establishes a new foundation for adversarial reinforcement learning, motivated by the comparative structure of regret. Existing approaches to robustness typically rely on adversarial training, which often fails to generalize to novel attacks, or worst-case optimization, which provides lower-bound guarantees but tends to produce overly conservative policies. To address these limitations, I propose a framework guided by three key principles. First, robustness should be evaluated at the trajectory level, ensuring stability over long sequences of decisions rather than individual actions. Second, robust agents must be designed with future adversaries in mind, rather than optimized against a fixed perturbation strategy. Finally, principled descriptions of the underlying problem structure are essential: methods that exploit the true structure of adversarial decision-making remain robust as applications evolve, while purely heuristic approaches often prove brittle. Building on these principles, this diss… Subtitle: PhD Dissertation Defense by BELAIRE Roman Lok-Ming. Contact: scisseminars@smu.edu.sg. Speaker Details: , BELAIRE Roman Lok-Ming PhD Candidate School of Computing and Information Systems Singapore Management University, Roman Belaire is a Ph.D. candidate at Singapore Management University, advised by Pradeep Varakantham and affiliated with the CARE.ai lab. My research concerns adversarial robustness in reinforcement learning, and I also have interests in RL fundamentals, generalization, and AI safety. Recent work has focused on formalizing LLM attacks (prompting LLMs to cause harm) and creating robust… RSVP: . Reserve a seat: https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTejbEKPlArBJhZomj91naG9UN1lHTjdJTE1PN1FINzc1U1ZMWE1INDdCWi4u. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Current Student. Academic Community. Tuesday, May 19, 2026, 10:00 AM – 11:00 AM. Meeting room 5.1, Level 5. SMU SCIS 1, Singapore 178902. For more info visit computing.smu.edu.sg.

Unleashing Vision-Language Semantics for Deepfake Video Detection

Recent Deepfake Video Detection (DFD) studies have demonstrated that pre-trained Vision-Language Models (VLMs) such as CLIP exhibit strong generalization capabilities in detecting artifacts across different identities. However, existing approaches focus on leveraging visual features only, overlooking their most distinctive strength — the rich vision-language semantics embedded in the latent space. We propose VLAForge, a novel DFD framework that unleashes the potential of such cross-modal semantics to enhance model's discriminability in deepfake detection. This work i) enhances the visual perception of VLM through a ForgePerceiver, which acts as an independent learner to capture diverse, subtle forgery cues both granularly and holistically, while preserving the pretrained Vision–Language Alignment (VLA) knowledge, and ii) provides a complementary discriminative cue — Identity-Aware VLA score, derived by coupling cross-modal semantics with the forgery cues learned by ForgePerceiver. Notably, the VLA score is au… Subtitle: Pre-Conference Talk by ZHU Jiawen. Contact: scisseminar@smu.edu.sg. Speaker Details: , ZHU Jiawen PhD Candidate School of Computing and Information Systems Singapore Management University, Jiawen ZHU is a final-year PhD candidate at Singapore Management University under the supervision of Prof. Guansong Pang. She has published multiple papers at top-tier conferences, including CVPR and ICCV. Her research interests include computer vision and open-world learning, with a particular focus on generalist anomaly detection and deepfake artifact detection. RSVP: . Reserve a seat: https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTejbEKPlArBJhZomj91naG9UMVRMSkExQTZaR0hVVEZaTFAxTlE3TEVTMy4u. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Wednesday, May 20, 2026, 3:30 PM – 4:00 PM. Meeting room 4.4, Level 4. School of Computing and Information Systems 1, Singapore Management University, 80 Stamford Road, Singapore 178902. For more info visit computing.smu.edu.sg.

Perspectives on Interpretability of Neural Models for Representing Text

In this dissertation, we investigate interpretability in the three elements of learning neural text representations: inputs, models, and outputs. We emphasise perspective as we present alternative novel methods to mine and organise meaning in this work. Firstly, examining models, we propose an alternate angle of interpreting Neural Topic Models word-topic distribution, producing better topic representations for interpretation. Next, we apply our previous findings to mine interpretations from the weights of transformer-based Large Language Models. Second, for outputs, as observations is critical to interpretability evaluations, we examine text representations from the human mental model. We propose and formulate a large-scale correlation analysis and accompanying user studies to examine automated coherence metrics and human evaluations. Finally, the model and its corresponding outputs learn from the pre-defined boundaries of the input space. For neural text representations, that would be the token space consis… Subtitle: PhD Dissertation Defense by LIM Jia Peng. Contact: scisseminars@smu.edu.sg. Speaker Details: , LIM Jia Peng PhD Candidate School of Computing and Information Systems Singapore Management University, Jia Peng joined SMU in 2017 as an undergraduate studying Information Systems. After graduating in 2021, he continued to pursue a Ph.D. in Computer Science, under supervision of Prof. Hady W. Lauw, working on Natural Language Processing research. Over the course of his Ph.D. he published in ACL, EMNLP, COLING, NeurIPS. He was also awarded with AISG Ph.D. Fellowship and Singapore Data Science… RSVP: . Reserve a seat: https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTejbEKPlArBJhZomj91naG9UMVhCTFVJWDBKM1lCSzdPUDRTNlZCM01UNi4u. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Current Student. Academic Community. Thursday, May 21, 2026, 9:00 AM – 10:00 AM. Meeting room 5.1, Level 5. SMU SCIS 1, Singapore 178902. For more info visit computing.smu.edu.sg.

Artificial Intelligence for Music, from Audio to Video, from Cyber to Physical

This seminar explores how AI-embedded tools can enhance individual practice and performance for string professionals and students. We discuss requisite technologies such as audio input analysis, error detection, dynamic and tempo estimation, posture and instrument advising. These capabilities enable AI to provide measurable benefits to musicians and generate genre-specific visual content, addressing two key research questions: (1) When can AI technology improve professional practice and performance? (2) What factors influence musicians’ acceptance of AI?  AI has made impressive progress in forms of images, audio, video, and text. AI's future challenges lie in moving from cyberspace to physical space. The second part of this seminar presents a novel MIDI-to-motion conversion for robotic cello performance. This method converts musical input into bowing trajectories without expensive motion capture. Our approach achieves human-like sound and contributes labeled robotic performance data to the research community… Contact: scisseminars@smu.edu.sg. Speaker Details: , Kristen Yeon-Ji Yun Clinical Associate Professor Rueff School of Design, Art and Performance, Purdue University, Kristen Yeon-Ji Yun is a clinical associate professor in the Department of Music in the Patti and Rusty Rueff School of Design, Art, and Performance at Purdue University. She is the principal investigator of a research grant IIS-2326198 from the National Science Foundation on the topic "Artificial Intelligence Technology for Future Music Performers". She is active as a soloist, chamber… RSVP: . Reserve a seat: https://forms.office.com/pages/responsepage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTbOXO7ktpRtBsn62WuekYtpUQVlUVEJMV1VINDRWSDBLRk9NTVdIT0hMMy4u&route=shorturl. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Current Student. Academic Community. Thursday, May 21, 2026, 2:30 PM – 3:30 PM. Seminar Room 2-3, Level 2. SMU SCIS 2, Singapore 178903. For more info visit computing.smu.edu.sg.

Stance-Linked Provenance: How Voter Identity Disclosure Reshapes Voting and Suggestion Incorporation on Crowdsourcing Platforms

Digital knowledge production on collaborative platforms is governed by the interplay between crowd evaluation and feedback, especially in the generative AI era, when ideas and suggestions can be produced at far greater speed and scale. This study examines how evaluator identity disclosure shapes users’ evaluation and ideators’ incorporation of crowd feedback. Leveraging a design change on TVTropes that shifted voting from anonymous to attributable, we find that identity disclosure reduces both positive and negative evaluations, suggesting lower evaluative participation. We also find that the incorporation of detractor feedback is reduced with identity disclosure, indicating that ideators are less receptive to opposing input when feedback is tied to revealed evaluative stance. These findings reveal a governance trade-off: while identity disclosure enhances accountability and transparency, it simultaneously reduces participation and limits learning from dissent.  This is a Pre-Conference talk for Twenty-second… Subtitle: Pre-Conference Talk by LIAW Shao Yi. Contact: scisseminar@smu.edu.sg. Speaker Details: , LIAW Shao Yi PhD Candidate School of Computing and Information Systems Singapore Management University, LIAW Shao Yi is a Ph.D. candidate in Information Systems, supervised by Prof. TANG Qian. Her general research interests are in product and human innovation with an emphasis on how individuals generate, evaluate, and refine ideas on digital platforms. RSVP: . Reserve a seat: https://forms.cloud.microsoft/Pages/ResponsePage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTejbEKPlArBJhZomj91naG9UM09YNlY1V0k4M0dENjdNQ1UwT1VMU0dXTy4u. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Thursday, May 28, 2026, 2:00 PM – 2:30 PM. Meeting room 4.4, Level 4. School of Computing and Information Systems 1, Singapore Management University, 80 Stamford Road, Singapore 178902. For more info visit computing.smu.edu.sg.

Aligned Multi-View Scripts for Universal Chart-to-Code Generation

Chart-to-code generation converts a chart image into an executable plotting script, enabling faithful reproduction and editable visualizations. Existing methods are largely Python-centric, limiting practical use and overlooking a critical source of supervision: the same chart can be expressed by semantically equivalent scripts in different plotting languages. To fill this gap, we introduce Chart2NCode, a dataset of 176K charts paired with aligned scripts in Python, R, and LaTeX that render visually equivalent outputs, constructed via a metadata-to-template pipeline with rendering verification and human quality checks. Building on a LLaVA-style architecture, we further propose CharLuMA, a parameter-efficient adaptation module that augments the multimodal projector with a language-conditioned mixture of low-rank subspaces, allowing the model to share core chart understanding while specializing code generation to the target language through lightweight routing. Extensive experiments show consistent gains in exec… Subtitle: Pre-Conference Talk by ZHANG Zhihan. Contact: scisseminar@smu.edu.sg. Speaker Details: , ZHANG Zhihan PhD Candidate School of Computing and Information Systems Singapore Management University, ZHANG Zhihan is a Ph.D. student in Computer Science at the SMU School of Computing and Information Systems, supervised by Prof. LIAO Lizi. Her research focuses on cross-modal reasoning. RSVP: . Reserve a seat: https://forms.office.com/Pages/ResponsePage.aspx?id=ynmKyZpakUeiQ_Bq_WdGTacjffrphqhDrJfv1DjxSmNUNjVaMlVEM1Y5WDNOTFBNUVc0MkpQN1c5Ni4u. Type: Seminars & Workshops. Subject: Information Technology & Systems. Audience: Public. Thursday, May 28, 2026, 4:30 PM – 5:00 PM. Meeting room 4.4, Level 4. School of Computing and Information Systems 1, Singapore Management University, 80 Stamford Road, Singapore 178902. For more info visit computing.smu.edu.sg.

DBA(Tech) Information Session - Tech-Ready Leadership in the Age of AI

Infosessions . Term Week: Week. Subject: Careers. Type: Information Sessions. Seminars & Workshops. Audience: Current Student. Reserve a seat: https://smu.sg/DBA_Tech_event. RSVP: . Thursday, May 28, 2026, 6:30 PM – 9:00 PM. Hybrid (details will be shared base on registration). For more info visit smu.sg.

DBA(Tech) Information Session: Tech-Ready Leadership in the Age of AI

Infosessions RSVP: . Reserve a seat: https://scispg.smu.edu.sg/acton/media/44865/dbatmcis0526. Type: Information Sessions. Subject: Information Technology & Systems. Leadership. Audience: Professionals. Public. Thursday, May 28, 2026, 6:30 PM – 9:00 PM. Hybrid (details will be shared base on registration).