Query Processing Professors and Supervisors in Singapore

Divesh Aggarwalمشاهده پروفایل

دانشیار

National University of SingaporeSingapore

Divesh Aggarwal is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) and a Principal Investigator at the Centre for Quantum Technologies (CQT). He leads an active research group with multiple PhD students, postdocs, and collaborators focusing on theoretical computer science and cryptography. His research spans two primary themes: (1) fine-grained complexity and exponential algorithms for hard problems, particularly lattice problems, where he works on both finding faster algorithms and proving lower bounds; and (2) randomness extractors and their applications in cryptography, privacy amplification, and tamper-resilient systems. His work intersects cryptography, computational complexity, and quantum computing. Aggarwal's recent publications (2022-2025) demonstrate continued productivity in lattice-based cryptography, with significant contributions to non-malleable codes, quantum security, and hardness assumptions. His work appears consistently in top venues including STOC, FOCS, CRYPTO, and IEEE Transactions. The research shows a strong trend toward quantum-resistant cryptography and exploring the boundaries between classical and quantum computational hardness. He actively mentors students and researchers, with current PhD students including Zeyong Li, Rishav Gupta, Saswata Mukherjee, Aditya Morolia, and Ananta Mukherjee. His alumni have secured positions at institutions including NUS, IIT Delhi, and XJTLU. Aggarwal also organizes a weekly research seminar where his group discusses theoretical computer science topics. His teaching portfolio includes advanced courses such as Computational Complexity, Pseudorandomness, Design and Analysis of Algorithms, and Introduction to Quantum Computing. He serves on program committees for major conferences including CRYPTO, EUROCRYPT, and STOC, and on editorial boards for journals like Information Processing Letters.

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Jithin Vacheryمشاهده پروفایل

مدرس

National University of SingaporeSingapore

Jithin Vachery is a Lecturer at the School of Computing, National University of Singapore (NUS), with a research focus on social network analysis and graph mining. He previously served as a Postdoctoral Research Fellow in the N-CRiPT lab at NUS and completed his PhD at Indian Institute of Technology (IIT) Madras under Prof. Sayan Ranu. PhD in Computer Science (2020), IIT Madras MEng in Computer Science and Engineering (2011), Indian Institute of Science (IISc) B.Tech in Computer Science (2005), Kerala University His research spans data analytics on large networks, including knowledge graphs, social networks, and chemical compound databases. Key areas include graph indexing, optimization, and applications to fake news mitigation and network delay minimization. Recent publications highlight trends in graph query optimization (RAQ), chemical fingerprint search (RISC), and social media interventions (fake news, emotional analysis). Collaborations include work with Prof. Mohan S. Kankanhalli and Prof. Sayan Ranu. IBM Best PhD Thesis Award (2020) Institute Research Award, IIT Madras (2019) Star TA Award (2017) TCS PhD Fellowship (2015–2019) All India Rank 2 in GATE (2009) Jithin teaches courses such as CS2105 (Introduction to Computer Networks) and CG4002 (Computer Engineering Capstone Project). Prior industrial experience includes roles at inspiriSYS and alTRan, focusing on network protocols and routing systems. He collaborates with laboratories including the N-CRiPT lab at NUS and AIDB Lab at IIT-Madras, emphasizing interdisciplinary research in computational social science and database systems.

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WONG Lim Soonمشاهده پروفایل

استاد

National University of SingaporeSingapore

WONG Lim Soon is the KITHCT Chair Professor at the School of Computing , National University of Singapore (NUS). He also served as Deputy Dean of the NUS Graduate School and currently directs the Integrative Sciences and Engineering Programme . His career spans significant contributions to database theory, computational biology, and knowledge discovery technologies. Education: B.Sc. (Engineering) in Computing Science, First Class Honours, Imperial College London Ph.D. in Computer & Information Science, University of Pennsylvania His research interests intersect computational biology , database theory , and knowledge discovery . He focuses on enhancing proteomic profile analysis, addressing confounders in omics data, predicting transcription factor interactions, and rethinking synchronized iteration in programming languages. His work aims to improve biomarker reproducibility in proteomics and design robust statistical methods for omics analysis. His recent publications highlight advancements in genomic data processing , proteomics , and database algorithms . Key themes include non-equijoin efficiency , batch effect normalization , and protein family prediction in low-similarity regimes. Scientific Awards & Honours: Fellow of the ACM, 2013 ICDT 2014 Test of Time Award (with Peter Buneman and Val Tannen) FEER Asian Innovation Gold Award, 2003 (with Allen Yeoh, Huiqing Liu, and Jinyan Li) Singapore Youth Award Medal of Commendation, 2006 Limsoon co-founded Molecular Connections in India and has chaired the company for over a decade, growing it into a 2,000-person organization. His research is supported by grants from Singapore’s National Research Foundation and Ministry of Education Academic Research Fund (Tier-1 and Tier-2). He also develops open-source tools like Synchrony DBModel and GMQL implementations in Scala/Python.

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QIAO Dandanمشاهده پروفایل

دانشیار

National University of SingaporeSingapore

QIAO Dandan is an Associate Professor in the Department of Information Systems and Analytics at the National University of Singapore (NUS), School of Computing. She holds a PhD from Tsinghua University and a visiting scholar appointment at the University of Texas at Austin. Her research focuses on digital platforms, computational social science, and the economics of dark web transactions. Notable contributions include analyzing darknet market dynamics, the impact of financial incentives on online reviews, and ride-hailing services' societal effects. Education: Ph.D., Information Systems, Tsinghua University, 2018 Visiting Scholar, University of Texas at Austin, 2015–2017 B.S., Information Systems, Beijing University of Posts and Telecommunications, 2012 Research Interests: Darknet market enforcement and crime suppression Incentive mechanisms in online prosocial behavior Predictive analytics for crowdfunding and e-commerce Platform design and digital transformation strategies Awards: 2024 AIS Early Career Award 2023 ISS Gordon B. Davis Young Scholar Award Multiple grants from Singapore's Ministry of Education and the NET Institute Advising & Grants: Ph.D. coordinator for NUS Department of Information Systems and Analytics Secured MOE Tier-1 and Tier-2 grants Editorial roles at Information Systems Research and MIS Quarterly Labs & Teams: Deputy Director of the Centre for Computational Social Science and Humanities (CSSH) at NUS.

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Yap Rolandمشاهده پروفایل

دانشیار

National University of SingaporeSingapore

Yap Roland is an Associate Professor at the School of Computing, National University of Singapore (NUS), and a member of the Institute of Operations Research and Analytics (IORA). His research focuses on constraint programming and solving, optimization, combinatorial problems, vehicle routing, and big data applications. He actively contributes to advancing methodologies in computational logic, software security, and algorithm design. His work spans theoretical foundations of constraint satisfaction (CSP/SAT) and practical applications in database systems, graph neural networks, and transportation logistics. Notable contributions include benchmarking tools like OSS-Bench for coding LLMs, novel approaches to detecting logic bugs in graph databases, and enhancing security through randomized pointer techniques. His research bridges algorithmic theory and real-world challenges in AI, cybersecurity, and efficient resource allocation. Yap Roland has published extensively in top-tier venues such as the International Conference on Principles and Practice of Constraint Programming (CP) and the International Conference on Theory and Applications of Satisfiability Testing (SAT). His recent work emphasizes scalability, fairness in machine learning, and robustness against memory errors in software systems.

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Ashraf A. Kassimمشاهده پروفایل

استاد

Singapore University of Technology and DesignSingapore

Ashraf A. Kassim is a Professor at the Singapore University of Technology and Design (SUTD) and serves as Associate Provost for the Office of Education and Innovation. He holds a PhD from Carnegie Mellon University and previously held positions including Professor of Electrical & Computer Engineering at the National University of Singapore (NUS), where he also served as Vice-Provost (Research) and Vice-Dean of Engineering. His industry experience includes research at Texas Instruments developing machine vision systems. His research spans computer vision , medical image analysis , machine learning , and deep learning . Key applications include diagnostic radiography, generative adversarial networks (GANs) for image synthesis, facial landmark detection, and attribute-based fashion retrieval systems. His work integrates advanced neural architectures with real-world challenges in healthcare and multimedia. Publications (170+ articles) emphasize deep learning-driven solutions: recent works focus on medical imaging (cell classification, radiograph analysis), generative models (text-to-image synthesis, GANs), and computer vision applications (facial analysis, fashion retrieval). Awards and Honors: Mendaki Foundation’s Anugerah Cemerlang (Academic Excellence Award) Institution of Engineers Singapore Award (2011) Public Administration Medal (Bronze, 2012) National Day Long Service Award (2018) NUS Annual Teaching Excellence Award Administrative service includes board memberships at Singapore Science Centre, Singapore Synchrotron Light Source, and Centre for Maritime Studies. He contributes to academic committees and journal editorial boards internationally.

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LI Yuchenمشاهده پروفایل

دانشیار

Singapore Management UniversitySingapore

Yuchen Li is an Associate Professor at the School of Computing and Information System (SCIS) at Singapore Management University (SMU), where he also holds the Lee Kong Chian Fellowship for Research Excellence. He earned his Ph.D. in Computer Science from the National University of Singapore (NUS) in 2017. His research focuses on social analytics, high-performance graph mining, and fintech applications leveraging large language models (LLMs). He has led significant projects funded by MoE, including 'Next-Gen Competitive Intelligence' and 'CONQUEROR' for concurrent graph query processing. His academic contributions span influential publications in top-tier conferences like SIGMOD, KDD, and ICML, with notable works on graph algorithms, fraud detection, and knowledge graph robustness. He advises Ph.D. students and has supervised over a dozen researchers, including current students Xiao Hanhua, Wang Sha, and Ye Chang. His awards include the Lee Kong Chian Fellowship and the Best Demo Paper Award at CIKM 2021. Li’s research bridges theoretical foundations and practical applications, addressing challenges in graph processing, social media analysis, and fintech. His team develops systems like 'Dupin' for fraud detection and 'ThunderRW' for in-memory graph processing, showcasing expertise in GPU acceleration and scalable algorithms.

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Wawan Solihinمشاهده پروفایل

مدرس

National University of SingaporeSingapore

Dr. Wawan Solihin is an adjunct lecturer in the Civil Engineering Department at the National University of Singapore (NUS), specializing in Building Information Modelling (BIM) and spatial data management. With over 30 years of professional experience, his research focuses on automated code compliance, BIM interoperability, and applying AI to enhance building data interrogation. He earned his PhD from Georgia Institute of Technology in 2016 under Prof. Chuck Eastman, pioneering solutions for BIM-based compliance checks. Education: PhD (Design Computing), Georgia Institute of Technology, USA (2016) Research Interests: AI-driven BIM data quality and automation Automated code compliance for buildings Integration of spatial data and BIM OpenBIM and data interoperability standards Key Projects & Contributions: Core contributor to Singapore’s BIM initiatives (e.g., PUB’s BIM Checker, URA’s GFA Autochecker) Co-developer of Fornaxcloud for cloud-based BIM validation Active in standardization via buildingSMART International and Singapore Technical Committees Advising & Grants: Co-supervises PhD and final-year students on AI-BIM integration Leads industry-funded projects in compliance automation Labs & Teams: Member of buildingSMART’s Regulatory Domain Steering Committee Technical coordinator for Singapore’s BIM standardization efforts

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ZHANG Jiahengمشاهده پروفایل

استادیار

National University of SingaporeSingapore

ZHANG Jiaheng is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His work bridges cryptography, artificial intelligence, and system security, with a focus on scalable and privacy-preserving technologies. He teaches CS3235 – Computer Security and leads research in zero-knowledge proofs, LLM safety, and trustworthy AI. Research Interests: His research spans Cryptography , Security , Machine Learning & AI , Privacy , and Algorithms & Theory . He specializes in making zero-knowledge proofs practical at scale and securing large language models against jailbreaking, backdoors, and privacy leaks. His recent projects include zkGPT, BatchZK, and Guardreasoner, highlighting his dual focus on theoretical foundations and real-world applications. The recent publications show a strong trend toward scalable zero-knowledge systems and AI security , particularly in verifying and protecting LLMs. These works integrate cryptographic rigor with modern AI challenges, reflecting a cohesive research vision at the frontier of trustworthy computing. Scientific Contributions: Developed scalable collaborative zk-SNARKs for efficient proof generation. Pioneered techniques for secure LLM inference and jailbreak detection. Advanced GPU-accelerated and distributed zero-knowledge proof systems. Advising & Grants: While specific students and grants are not listed, his active publication record in top-tier venues suggests ongoing research supervision and external funding in cybersecurity and AI. He is likely involved in advising PhD and Master’s students in cryptography and AI security. Labs & Teams: He is part of the NUS School of Computing research ecosystem, potentially affiliated with cybersecurity or AI labs, contributing to Singapore’s leadership in privacy-preserving technologies.

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