Computing Research Week 2019

August 5 to 8

The event will be held from 5 to 8 August in NUS, School of Computing (SoC), Seminar Room 1. Similar to the first edition of the research week, our aim is to present excellent research that is being done in SoC, this time. We want to learn about recent research problems and achievements from different groups in SoC. Thus, the program consists of keynote talks by faculty members along with conference style talks by students and poster sessions and panels.


The event is public and free of charge. However, please register by 24th July to help with the organization (catering for coffee and lunch). (The registration was only for catering purposes and is now closed, you can still attend the talks!)

Call for Posters!

We would like to invite all researchers in the school to participate in the poster session and contribute to the Research Week August 2019.
This Call For Posters includes all domains of Computer Science such as Algorithm Theory, Artificial Intelligence, Computational Biology, Database, Media, System and Networking, Programming Languages and Software Engineering, and Security.

Please fill out this form by 20th July 2019!

There are two poster sessions scheduled on Tuesday, 6th Aug, from 14:35 to 15:30 and Thursday, 8th Aug, from 14:35 to 15:30. We will let you know by email on which of the days your poster will be scheduled.


Monday, 5/8/2019

09:00 – 09:20 Welcome coffee

09:20 – 09:30 Opening remarks

Session Chair: Ashraf Abdul

09:30 – 10:15 Automated Program Repair - Abhik Roychoudhury

10:15 – 10:40 Group Fairness and Diversity in the Allocation of Indivisible Goods - Mithun Chakraborty

10:40 – 11:05 Towards Robust ResNet - Jingfeng Zhang

11:05 – 11:15 Break

11:15 – 11:40 IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules - Bishwamittra Ghosh

11:40 – 12:05 Designing Theory-Driven User-Centric Explainable AI - Danding Wang

12.05 – 13:00 Lunch Break

Session Chair: Muoi Tran

13:00 – 13:45 Training-by-Fitting: Self-Supervision for 3D Hand Pose Estimation - Angela Yao

13:45 – 14:10 Learning to Learn from Noisy Labeled Data - Junnan Li

14:10 – 14:35 One Engine To Serve'em All: Inferring Taint Rules Without Architectural Semantics - Zheng Leong Chua

14:35 – 15:00 Coffee break

15:00 – 15:25 Neuro-Symbolic Execution: Augmenting Symbolic Execution with Neural Constraints - Shiqi Shen

15:25 – 15:50 A Semantic Touch Interface for Flying Camera Photography - Lan Ziquan

15:50 – 16:15 Enhancing Stock Movement Prediction with Adversarial Training - Fuli Feng

16:15 – 16:40 Multi agent system verification - Dileepa Fernando

16:40 – 17:00 Break

17:00 – 18:15 Panel 1 - Industry/Academics after PhD: prospects and challenges (Moderator : Aashish Kolluri)
Prateek Saxena
Kuldeep S. Meel
David S. Rosenblum
Jia Yaoqi, Chief Technology Officer & Co-founder at Zilliqa
Jagannadan Varadarajan, Head of Data Science (Machine Learning) at Grab

18:15 – 19:00 Dinner

Tuesday, 6/8/2019

09:00 – 09:30 Welcome coffee

Session Chair: Himeshi De Silva

09:30 – 10:15 Adversarial Machine Learning: Challenges of building trust in AI - Reza Shokri

10:15 – 10:40 Better Care Quality at Lower Cost: Should I Participate in the Online Healthcare Communities - Luo Kai

10:40 – 11:05 Nudge Consumers through the Manipulation of Price Expectation: Evidence from a Field Experiment - Gao Yuting

11:05 – 11:15 Break

11:15 – 11:40 Facilitating mental product interaction: the effects of product orientation and computer interface - Peng Xixian

11:40 – 12:05 The Impact of Peer Influence on Academic Performance: A Three-Stage Co-Evolution Model - Ding Dan

12:05 – 13:00 Lunch Break

Session Chair: Mithun Chakraborty

13:00 – 13:45 Online Investment Advice and Micro-Celebrities: An Empirical Analysis of a Social Investment Platform - Goh Khim Yong

13:45 – 14:10 Want to Play DASH? A Game Theoretic Approach for Adaptive Streaming over HTTP - Abdelhak Bentaleb

14:10 – 14:35 A Stealthier Partitioning Attack against Bitcoin Peer-to-Peer Network - Muoi Tran

14:35 – 15:30 Poster Session + Break

15:30 – 15:55 Exploiting the Laws of Order in Smart Contracts - Aashish Kolluri

15:55 – 16:20 Towards Scaling Blockchain Systems via Sharding - Hung Dang

16:20 – 16:45 Introduction to Non-Malleable Codes and Inception Coding - Maciej Obremski

16:45 – 17:30 Break

17:30 – 18:30 Orientation for new graduate students

18:30 – 19:00 Research award presentation

19:00 – 19:30 Program briefing for PhD Students and MComp students

19:30 – 20:30 Dinner

Wednesday, 7/8/2019

09:00 – 09:30 Welcome coffee

Session Chair: Tapas Nayak

09:30 – 10:15 An Optimal Algorithm for Heavy Hitters in Insertion Streams and Related Problems - Arnab Bhattacharyya

10:15 – 10:40 PR3: Power Efficient and Low Latency Baseband Processing for LTE Femtocells - Nishant Budhdev

10:40 – 11:05 SoundUAV: Fingerprinting Acoustic Emanations for Delivery Drone Authentication - Soundarya Ramesh

11:05 – 11:15 Break

11:15 – 11:40 Friot: A Functional Reactive Language for IoT Programs with Dependent Type-and-Effect System - Yahui Song

11:40 – 12:05 Precise Time-synchronization in the Data-Plane using Programmable Switching ASIC - Pravein Govindan Kannan

12:05 – 13:00 Lunch Break

Session Chair: Sangharatna Godboley

13:00 – 13:45 Emptiness doesn't have to mean nothingness; haziness doesn’t have to mean iffiness - Lim Soon Wong

13:45 – 14:10 Crash-avoiding Program Repair - Gao Xiang

14:10 – 14:35 HyCUBE : A CGRA with Reconfigurable Single-cycle Multi-hop Interconnect - Manupa Karunaratne

14:35 – 15:00 Coffee break

15:00 – 15:25 Learning parametric skills for autonomous driving - Gao Wei

15:25 – 15:50 GPU-based Graph Traversal on Compressed Graphs - Sha Mo

15:50 – 16:15 Topological Data Analysis with ε-net Induced Lazy Witness Complex - Naheed Anjum Arafat

16:15 – 16:40 Data-driven methods for knowledge discovery in Regulomics - Stefano Perna

16:40 – 17:00 Break

17:00 – 18:15 Panel 2 - Different aspects of building a smart city (Moderator : Alan Tsang)
Tulika Mitra
Jun Han
Yair Zick
David Hsu
Beng Chin Ooi

18:15 – 19:00 Dinner

Thursday, 8/8/2019

09:00 – 09:30 Welcome coffee

Session Chair: Pravein Govindan Kannan

09:30 – 10:15 How to Video Stream on the Internet like the Pros - Roger Zimmermman

10:15 – 10:40 Knowledge-aware Multimodal Dialogue Systems - Lizi Liao

10:40 – 11:05 Learning to Detect Human-Object Interactions with Knowledge - Bingjie Xu

11:05 – 11:15 Break

11:15 – 11:40 Quantum Log-Approximate-Rank Conjecture is also False - Naresh Boddu

11:40 – 12:05 Weighted fair caching: Occupancy-centric allocation for space-shared resources - Lianjie Shi

12:05 – 13:00 Lunch Break

Session Chair: Vipul Arora

13:00 – 13:45 Deductive Synthesis of Heap-Manipulating Programs: Sound, Expressive, Fast - Ilya Sergey

13:45 – 14:10 Sublinear Time Nearest Neighbor Search over Generalized Weighted Space - Lei Yifan

14:10 – 14:35 Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures - Wenqiang Lei

14:35 – 15:30 Poster Session + Break

15:30 – 15:55 Scaling Data Stream Processing on Shared-Memory Multicore Architectures - Shuhao Zhang

15:55 – 16:20 Monitoring the Evolving Congestion Control Landscape of the Internet - Ayush Mishra

16:20 – 16:45 Improving Join Reorderability with Compensation Operators - Wang Taining

16:45 – 17:00 Music and Wearable Computing for Health and Learning - Wang Ye

17:00 – 17:05 Closing remarks

17:05 – 19:00 Dinner

19:00 – 20:00 Concert by Sound and Music Computing Lab

Poster Presentations

Git for Data: Collaboration-oriented Data Management with Ease and Efficiency – Lin Qian

Cronus: Robust Collaborative Machine Learning through Knowledge Transfer of Black-box Models – Chang Hongyan

Towards Robust ResNet: A Small Step but A Giant Leap – Zhang Jingfeng

Who, Where, and What to Wear? Extracting Fashion Knowledge from Social Media – Ma Yunshan

FLEX: Faithful Linguistic Explanations for Neural Net based Model Decisions – Sandareka Wickramanayake

Particle Filter Recurrent Neural Networks – Xiao Ma

Phase transition behavior of conjunction of cardinality and XOR constraints – Yash Pote

Harmony: An approach for Geo-distributed Processing of Big-Data Applications – Zhang Han

ApproxSymate: path sensitive program approximation using symbolic execution – Himeshi De Silva

Rainfall Estimation from Traffic Cameras – Remmy Zen

A Distributed Approach for Bitrate Selection in HTTP Adaptive Streaming – Abdelhak Bentaleb

Certifying Graph-Manipulating C Programs via Localizations within Data Structures – Anshuman Mohan

Bypassing Backdoor Detection Algorithms in Deep Learning – Lester Tan

SurFi: Detecting Surveillance Camera Looping Attacks with Wi-Fi Channel State Information – Nitya Lakshmanan

Quantitative Verification of Neural Networks And its Security Applications – Teodora Baluta

CGPredict: Embedded GPU Performance Estimation from Single-Threaded Applications – Wang Siqi

CASCADE: High Throughput Data Streaming via Decoupled Access-Execute CGRA – Dhananjaya Wijerathne

SPECTRUM: A Software Defined Predictable Many-core Architecture for LTE Baseband Processing – Vanchinathan Venkataramani

What Your Gait Reveals about You! – Sanjay Saha

Program Details

Monday, 5/8/2019, 09:30 – 10:15 Automated Program Repair – Abhik Roychoudhury

Automated program repair is an emerging and exciting field of research, which allows for automated rectification of errors and vulnerabilities. The use of automated program repair can be myriad, such as (a) improving programmer productivity (b) automated fixing of security vulnerabilities as they are detected, (c) self-healing software for autonomous devices such as drones, as well as (d) use of repair in introductory programming education by grading and providing hints for programming assignments. One of the key technical challenges in achieving automated program repair, is the lack of formal specifications of intended program behavior. In this talk, we will conceptualize the use of symbolic execution approaches and tools for extracting such specifications. This is done by analyzing a buggy program against selected tests, or against reference implementations. Such specification inference capability can be combined with program synthesis techniques to automatically repair programs. The capability of specification inference also serves a novel use of symbolic execution beyond verification and navigation of large search spaces. Automated program repair via symbolic execution goes beyond search-based approaches which attempt to lift patches from elsewhere in the program. Such an approach can construct “imaginative” patches, serves as a test-bed for the grand- challenge of automated programming, and contributes to the vision of trustworthy self-healing software.

Monday, 5/8/2019, 13:00 – 13:45 Training-by-Fitting: Self-Supervision for 3D Hand Pose Estimation - Angela Yao

Learning based hand pose estimation methods, especially deep learning based methods, requires large amount of accurate annotations on real-world data to achieve high accuracy. However, acquiring such accurate annotated samples can be extremely difficult and expensive. To mitigate the dependency on large amounts of annotation, we propose to leverage unlabeled samples instead. We propose a method that bridges model-based optimization and discriminative learning by using model-fitting errors to train deep neural networks. We demonstrate the ability of our method to generalize on two different models, one from a set of spheres and one from triangular meshes. Our proposed method makes highly accurate pose estimates comparable to current supervised methods and advances state-of-the-art in unsupervised learning for hand pose estimation.

Tuesday, 6/8/2019, 09:30 – 10:15 Adversarial Machine Learning: Challenges of building trust in AI - Reza Shokri Machine learning algorithms have shown an unprecedented predictive power for many complex learning tasks. As they are increasingly being deployed in large scale critical applications for processing various types of data, new questions related to their trustworthiness would arise. Can machine learning algorithms be trusted to have access to individuals' sensitive data? Can they be robust against noisy or adversarially perturbed data? Can we reliably interpret their learning process, and explain their predictions? In this talk, I will go over the challenges of building trustworthy machine learning algorithms in centralized and distributed (federated) settings, and will briefly discuss the inter-relation between privacy, robustness, and interpretability.

Tuesday, 6/8/2019, 13:00 – 13:45 Online Investment Advice and Micro-Celebrities: An Empirical Analysis of a Social Investment Platform - Goh Khim Yong

Retail investors are increasingly seeking online investment advice from social media. In this study, we conduct an empirical analysis of a social investment platform (SIP), which relies on social media advisors (SMAs) to contribute online investment commentaries and advice to retail investors. We then simultaneously quantify the impact of both SMAs’ informational factors and micro-celebrity tactics on their remuneration performance. This enables us to derive the relative economic significance of these factors and infer the information preferences of retail investors. Utilizing a dataset from a Chinese SIP, our study performs an in-depth content analysis to measure the informational factors of online investment advice and micro-celebrity tactics of SMAs. We then propose a hierarchical Bayesian modelling framework that accounts for various empirical issues: SMA heterogeneity, self-selection of paid content generation, omitted variable bias and measurement errors. Our findings demonstrate that SMAs achieve higher remuneration performance in terms of subscription revenue if their investment advice has more diverse sectors (diversity), more popular stocks (popularity), fewer negative sentiments (negativity), higher short-term predictive accuracy (accuracy), and more efforts in monitoring stocks across periods (sustenance). Specifically, sentiment negativity has the strongest relative effect. A one standard deviation increase in negativity leads to RMB 43.29 change in the remuneration performance, followed by diversity (2.81), sustenance (2.43), and popularity (1.84). In addition, an affiliation-based micro-celebrity tactic is more effective than an intimacy-based one. These two tactics also negatively moderate the effects of informational factors such as diversity and intensity. Our findings provide implications for academic research and practice.

Wednesday, 7/8/2019, 09:30 – 10:15 An Optimal Algorithm for Heavy Hitters in Insertion Streams and Related Problems - Arnab Bhattacharyya

We give the first optimal bounds for returning the heavy hitters in a data stream of insertions, together with their approximate frequencies, closing a long line of work on this problem. We show a randomized algorithm whose space complexity improves upon Misra and Gries' classic algorithm and is furthermore optimal upto constants. A modification of our algorithm can be used to estimate the maximum frequency up to an additive error. We also introduce several variants of the heavy hitters and maximum frequency problems, inspired by rank aggregation and voting schemes, and show how our techniques can be applied in such settings. Unlike the traditional heavy hitters problem, some of these variants look at comparisons between items rather than numerical values to determine the frequency of an item. Joint work with Palash Dey (IIT Kharagpur) and David Woodruff (IBM Almaden)

Wednesday, 7/8/2019, 13:00 – 13:45 Emptiness doesn't have to mean nothingness; haziness doesn’t have to mean iffiness - Lim Soon Wong

Biological and clinical omics data are full of data holes, obfuscating batch effects, confounding dependencies, etc. These issues present interesting pervasive challenges in analyzing biological and clinical omics data. I will present some instances of these challenges, as well as our solutions to them. I will highlight the interplay of logic, statistics, and biological/physical principles in the development of these solutions.

Thursday, 8/8/2019, 09:30 – 10:15 How to Video Stream on the Internet like the Pros - Roger Zimmermman

Globally, video streaming currently accounts for about 70% of all traffic on the internet and it is expected to reach 82% by 2021. Thus, managing video traffic efficiently is of high importance for many organizations. Furthermore, video communication is becoming an important and integral part of many applications, for example, for staff training or customer support calls. In recent years HTTP (Hypertext Transfer Protocol) adaptive streaming (HAS) is being adopted with increasing frequency and has become the de-facto standard for video streaming. Thus, HAS technology has seen rapid and significant developments recently. With the large-scale deployments of HAS, new and interesting challenges have emerged. For example, the client-driven, on-off adaptation behavior of HAS results in uneven bandwidth competition and a decrease in end-user quality of experience (QoE). Also, the long latency of HAS is problematic in live streaming. In this talk I will present some of our proposals and recent work which aim to alleviate these scalability issues.

Thursday, 8/8/2019, 13:00 – 13:45 Deductive Synthesis of Heap-Manipulating Programs: Sound, Expressive, Fast - Ilya Sergey

In my talk, I will describe a deductive approach for synthesising imperative programs with pointers from declarative specifications expressed in Separation Logic. The approach treats logical program specifications, given in the form or pre- and postconditions with a pure and a spatial part, as proof goals, and provides an algorithm for rule-directed program construction based on the shape of the symbolic heap footprint a desired program manipulates. The program synthesis algorithm rests on the novel framework of Synthetic Separation Logic (SSL). The produced executable programs are correct by construction, in the sense that they satisfy the ascribed specifications, and are accompanied by complete proof derivations (i.e., certificates), which can be checked independently by a third-party verifier. The approach has been implemented as a proof search engine for SSL in a form a program synthesiser. For efficiency, the engine exploits properties of SSL specifications, aggressively relying on a version of the Frame Rule and commutativity of separating conjunction to prune the search space. I will explain and showcase the use of SSL on characteristic examples, describe the design of out tool, and report on the experience of using it to synthesise a series of benchmark programs manipulating with heap-based linked data structures. I will also tell about some recent advances of using SSL-based synthesis, enhanced with immutability annotations, as well as its applications for program repair.

Thursday, 8/8/2019, 17:00 – 17:45 Music and Wearable Computing for Health and Learning - Wang Ye

Music is more than just a source of entertainment. Parents sing nursery rhymes to their young children to help them learn their first language; music therapists use music to help patients recover. I will present our recent research work in creating music computing technology specifically geared towards health and learning applications. In particular, I will introduce our Singing and Listening to Improve Our Natural Speaking (SLIONS) Karaoke smartphone app, which is designed to promote joyful learning of a second language. Wearable sensors are applied in many different domains. I will present our wearable sensor systems specially designed for quantifying patients’ gaits, as well as for facilitating physical exercise via dancing and music making. Towards this end, I will highlight our Mobility Analysis (MANA) smart-sensor system which is designed to quantify gaits of people with Parkinson’s disease, as well as Motion Initiated Music Ensemble with Sensors (MIMES) system which is designed to convert human movements to musical sounds for neurologic music therapy.


Program Committee Chairs
Teodora Baluta
Nitya Lakshmanan
Program Committee
Ashraf Abdul
Vipul Arora
Mithun Chakraborty (poster committee)
Himeshi De Silva
Bishwamittra Ghosh
Sangharatna Godboley (poster committee)
Pravein Govindan Kannan
Wentain Guo
Ruidan He
Minh Ho
Chang Hongyan
Manupa Karunaratne
Aashish Kolluri
Cheryl Lee
Xie Luyu
Rasool Maghareh
Tapas Nayak
Cai Panpan
Sunimal Rathnayake (poster committee)
Reza Shokri
Muoi Tran
Alan Tsang
Xie Yaqi
Shuhao Zhang