About the Student Research Competition
The ACM Student Research Competition (SRC), sponsored by Microsoft, offers a unique forum for undergraduate and graduate students to present their original research before a panel of judges and attendees at well-known ACM-sponsored and co-sponsored conferences.
Recognizing the value of student participation at conferences, ACM started the program in 2003, but it is much more than just a travel funding program. The ACM SRC provides participants a chance to meet other students and to get direct feedback on their work from experts.
This year's competitions took place at 26 participating conferences, sponsored by SIGACCESS, SIGAPP, SIGARCH, SIGCHI, SIGCOMM, SIGCSE, SIGDA,SIGDOC, SIGGRAPH, SIGHPC, SIGMOBILE, SIGMOD, SIGOPS, SIGPLAN, SIGSOFT and SIGSPATIAL and included more than 381 student participants.
The program is administered by Nanette Hernandez at ACM, Dr. Laurie Ann Williams at North Carolina State University, and Dr. Evelyne Viegas at Microsoft, Redmond, WA.
2018 ACM SRC Grand Finals Winners Announced
Meng Li, Jon Gjengset, Daniel George, Tiancheng Sun, Patrick Thier and Ayush Kohli were the 2018 Grand Finals winners of ACM’s Student Research Competition. The SRC Grand Finals are the culmination of a year-long competition that involved more than 381 computer science students presenting research projects at 26 major ACM conferences.
Meng Li, University of Texas, Austin
"A Synergistic Framework for Hardware IP Privacy and Integrity Protection" (ICCAD 2017)
As the technology node scales down to 45nm and beyond, the significant increase in design complexity and cost propels the globalization of the $400-billion semiconductor industry. However, such globalization comes at a cost. Although it has helped to reduce the overall cost by the worldwide distribution of integrated circuit (IC) design, fabrication, and deployment, it also introduces ever-increasing intellectual property (IP) privacy and integrity infringement...... [Read more]
Jon Gjengset, Massachusetts Institute of Technology
"Deep Learning for Time-series Signal Processing for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Real LIGO Data" (SOSP 2017)
Xylem is a new storage backend for read-heavy web applications based on dynamic, partially-stateful dataflow. Xylem provides a web application with significantly improved read performance for commonly-executed queries by pre-computing their results and incrementally maintaining them as writes arrive. The application supplies a relational schema and SQL query definitions, which Xylem compiles into a streaming data-flow. Application writes stream through the data-flow to update stateful caches of the queries’ results, which serve reads efficiently.s.... [Read more]
Daniel George, University of Texas, Austin
"Deep Learning for Time-series Signal Processing for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Real LIGO Data" (SC 2017)
The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of multimessenger astrophysics. To enhance this emergent science, we propose the use of deep learning with a system of 1D convolutional neural networks, that take time-series inputs, for classification and regression with a novel curriculum learning scheme and transfer learning technique. We demonstrate how this method can be applied for rapid detection and parameter estimation of gravitational waves from binary black hole mergers using continuous data streams from multiple LIGO detectors.... [Read more]
Tiancheng Sun, University of California
"Attribute-preserving gamut mapping of measured BRDFs" (SIGGRAPH 2017)
Reproducing the appearance of real-world materials using current printing
technology is problematic. The reduced number of inks available define the
printer’s limited gamut, creating distortions in the printed appearance that
are hard to control. Gamut mapping refers to the process of bringing an outof-
gamut material appearance into the printer’s gamut, while minimizing
such distortions as much as possible... [Read more]
Patrick Thier Sun, Institut fur Computersprachen Technische Universitat Wien
"Fast and Flexible Instruction Selection with Constraints" (CGO 2018)
Instruction selection is an important component of code generation and a variety of techniques have been proposed in the past, ranging from simple macro expansion that selects target instructions based on a single node of the intermediate representation (IR) to global instruction selection methods on the whole IR graph. Simpler methods tend to be faster, but produce slower code.... [Read more]
Ayush Kohli, Southern Illinois University Carbondale
"A Supervised Learning-Based System to Identiy Cloned Android Applications" (ESEC/FSE 2017)
This paper presents the design and evaluation of Decision- Droid, a supervised learning based system to identify cloned
Android app pairs. DecisionDroid combines a set of 13 different features and is highly resilient. We trained DecisionDroid
using a manually verified diverse dataset of 18,562 app pairs. On a hundred ten-fold cross validations, it achieved 96.8% precision, 97.2% recall, and 98.3% accuracy..... [Read more]
Students can gain many tangible and intangible rewards from participating in one of ACM’s Student Research Competitions. With a generous sponsorship of $120,000 per competition year from Microsoft, the ACM Student Research Competition is an internationally recognized venue enabling undergraduate and graduate students to earn:
- Awards: cash prizes, medals, and ACM student memberships
- Prestige: Grand Finalists and their advisors are invited to the Annual ACM Awards Banquet, where they are recognized for their accomplishments
- Visibility: opportunities to meet with researchers in their field of interest and make important connections
- Experience: opportunities to sharpen communication, visual, organizational, and presentation skills in preparation for the SRC experience
The ACM Student Research Competition, sponsored by Microsoft, is an internationally recognized venue enabling undergraduate and graduate students to experience the research world, share research results and exchange ideas, rub shoulders with academic and industry luminaries, understand the practical applications of their research and gain recognition.