The Doctoral Colloquium of SenSys 2018 seeks to provide a friendly, supportive, and constructive environment where PhD students can present their research in progress for an open discussion guided by a panel of experienced researchers. The Doctoral Colloquium will be structured as a series of short presentations by the students followed by individual discussions, feedback, and advice. Students with the most inspiring topics will also be invited to present a poster during the main conference to leverage further interaction with SenSys attendees.
Current PhD students in the early stages of their career are encouraged to submit a 2-pages research summary describing the work in progress and including a 100-word abstract. Things to consider for inclusion in the research summary might be: the expected contribution to the field; the original idea or thesis statement; the problem domain and the specific problem addressed; a brief overview of related work; the methodological approach; research carried out and results so far. The abstract shall also include a one-paragraph biography of the student, including the names and affiliations of the research advisor(s), and expected date of dissertation submission. The student should be the sole author, although contributions of the advisor and others should be acknowledged.
The Doctoral Colloquium committee will review submissions to ensure quality, relevance, and potential benefit from attendance. Authors of accepted submissions are expected to participate in person to the Doctoral Colloquium. There will be no separate registration fee for the Doctoral Colloquium.
Sunday, November 4, 2018
- 15:00 - On the Challenges in Energy-Constrained Outdoor Wireless Sensor Networks: Trade off between Efficiency and Robustness
- 15:20 - A Cascading Bandit Approach to Efficient Mobility Management in Ultra-Dense Networks
- 15:40 - Device Pairing based on deep learning in Body Area Networks
- 16:00 - Exploiting Spatial Diversity for Energy Efficient LPWANs Decoding
- 16:20 - Identification Of Primary-Space-Use Outliers Based On Temporal Energy Consumption Features Using Machine Learning
The Doctoral Colloquium will be held in Room 307, the 3rd floor of Teaching Building I, Southern University of Science and Technology (SUSTech) and co-located with ACM Sensys 2018 Workshops.
We encourage Ph.D. students to prepare and present their posters on Nov. 7th jointly with the Poster & Demos session of ACM Sensys 2018.
Research summaries will be reviewed by the chairs and panel members. If the work is accepted, a student may be expected to make clarifications and improvements to the research summary by the camera-ready deadline. Submissions must be received no later than October 6th via web submission form.
Submissions must be in PDF format, be written in English, of no more than two pages in length (all inclusive), and adhere to the Sensys formatting styles found here.
The abstract should include the author’s name, affiliation, and email address.
The camera-ready paper must be submitted by the 26th of November 2018 (AOE). You should use the acmart.cls. Please note that ACM uses 9-pt fonts in all conference proceedings, and the style (both LaTeX and Word) implicitly define the font size to be 9-pt. The maximum number of pages for poster and demos is 2, including the references. Please refer to publication chair's Note as well as the User Guide of the new class.
To submit a Doctoral Colloquium abstract, please add " PhD Forum Abstract:" at the beginning of the manuscript's title.
- Submission Deadline: October 6, 2018 AOE
- Notification of Acceptance: October 13, 2018 AOE
- Camera-Ready: October 26, 2018 AOE
- Colloquium: November 4, 2018
- Doctoral Colloquium Panelists:
Marco Zimmerling (TU Dresden)
Rasit Eskicioglu (University of Manitoba)
Xiaohui Lin (Shenzhen University)
Lu Su (State University of New York Buffalo)
Program Committee: Polly Huang (National Taiwan University) Yuhan Dong (Tsinghua University) Xiang Chen (Sun Yat-Sen University) Simon Pun (The Chinese University of Hong Kong, Shenzhen) Rong Yu (Guangdong University of Technology)