Research Students' Symposium 2021/2022
The 2022 Computer Science PhD Symposium will be held from Wednesday
29th June to Friday 1st July.
The symposium exists to give all
PhD. students in Computer Science at Manchester the chance to present
their work to the Department. Second-year students and above will give
short talks; first-year students will present posters.
It is a
great opportunity---for both staff and students---to learn about some
of the fascinating research being carried out in the Department,
across all areas of the subject.
Location details
All talk sessions: Kilburn 1.4
Poster session: Kilburn Atlas 1/Staff and PG Common Room (Floor 1)
Timetable
Day 1: Third(+) year talks
- 9:45--10:00 Welcome and prize announcements (Ian Pratt-Hartmann)
- 10:00--11:00 Contributed talks
- Kamil Erdayandi: Towards Privacy Preserving Local Energy Markets
- Mohammed Alhamadi: Modelling User Strategies on Interactive Information Dashboards
- 11:00--11:30 Coffee
- 11:30--13:00 Contributed talks
- Jiarun Cao: Information Extraction in the Cancer Literature
- Ruoyu Sun: Reinforcement Learning based Motion Planning with Boltzmann Distribution Policy
- Ruben Enrique Padilla Robles: Efficient data collection in UAV assisted WSN in large areas
- 13:00--14:00 Lunch break
- 14:00--15:30 Contributed talks
- Igor Wodiany: Dynamic Binary Lifting and Acceleration
- Minmin Jinag: Mitigating EM Side-Channel Attacks with Dynamic Delay Insertion and Data Bus Inversion
- Khlood Jastaniah: Efficient Privacy-Friendly and Flexible Wearable IoT Data Processing with User-Centric Access Control
Day 2: Poster session and Second year talks
- Jake Vasilakes: Contextualizing Information Extraction
- Shengzhong Mao: Time Series Forecasting Based on Visibility Graph Networks
- Chengdong Shi: Machine Learning-Based Approach to Nonlinear Functional
- Data Analysis for Photovoltaic Power Forecasting
- 20 minute break
- Shaden Alismail: Memory subsystem in Multi-tenant FPGAs
- Wei Zhao: Remaining Useful life prediction based on functional data analysis
- Erick Mendez Guzman: Explainable Text Classification Framework for Detecting Indicators of Forced Labour
Day 3: Second year talks
- Yuping Wu: EDU-level Extractive Summarization with Flexible Summary Length
- Bowen Xu: Trust-based Secure Routing in Hierarchical WSN with QoS Support
- Bardia Babaei: Precise characterizing of FPGAs in production systems
- Yujie Tian: Component based approach for program synthesis
- Lisheng Wu: Augmented Goal-Expansion via Pre-trained Skills for Sparse-Reward Long-Horizon Reinforcement Learning
- Yifan Xu: Explanations through Dialogue for Rule-based Reasoning Systems
- Maram Alalwan: Data discovery in data marketplaces
- Tianlin Zhang: Mental illness detection from text using deep learning
- Boyang Liu: Argument Mining from Biomedical Literature
- Biyun Yang: General Terminology Induction: Implementation and Improvement
- Ching-Hsun Tseng: Perturbed Gradients Updating within Unit Space for Deep Learning