The prestigious MICRO Test of Time (ToT) Award is an annual feature at the IEEE/ACM International Symposium on Microarchitecture. This year was the 51st edition of the conference, held between October 20 and 24 in Fukuoka City, Japan. In the course of the conference, the Awards Committee named Thomas Ball and James R. Larus as the winners of the fifth MICRO Test of Time Award. That is an honor for EPFL as well; Professor Larus is Dean of the School of Computer and Communication Sciences (IC).
Machine learning has become ubiquitous today with applications ranging from accurate diagnosis of skin cancers and cardiac arrhythmia to recommendations on streaming channels and gaming. However, in the distributed machine learning scheme, what if one ‘worker’ or ‘peer’ is compromised? How can the aggregation system be resilient to the presence of such an adversary?
Martin Jaggi, Tenure Track Assistant Professor at EPFL’s School of Computer and Communication Sciences, has won the Google Focused Research Award for 2018 in the area of Machine Learning. The award-winning investigation was on “Large-Scale Optimization: Beyond Convexity,” completed jointly with Alexandre d’Aspremont and Francis Bach.
In about two months’ time, participants will assemble in Seattle for the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018). Apart from the academic discourses that will take place at the four-day conference (November 6-9), the event is also of particular interest for EPFL because two of its outstanding researchers will be awarded the Best Paper Award for their contribution to the previous edition of the annual event.
The Dimitris N. Chorafas Foundation recognizes outstanding scientific work in selected fields in engineering sciences, medicine, and natural sciences. The winners are chosen each year from among the select list of graduating doctorate students submitted by the Foundation’s partner universities in Europe, North America, and Asia. One of this year’s awardees is Manos Karpathiotakis, who completed his PhD at EPFL’s Data-Intensive Applications and Systems (DIAS) Laboratory in 2017 and is currently a scientist at the laboratory.
In a press release last month, the Takis & Louki Nemitsas Foundation announced the selection of Anastasia Ailamaki, Professor and Director at EPFL’s Data-Intensive Applications and Systems Laboratory, as the Laureate of the NEMITSAS Prize 2018 in Computer Science.
The 48th International Conference on Dependable Systems and Networks (DSN-2018) was held in Luxembourg City. The four-day event (June 25-28) saw thematic workshops and a series of more than 60 presentations by scholars in the realms of dependability and security research, fields that have been the raison d’être of DSN conferences over the years.
Houston hosted this year’s annual conference of the ACM Special Interest Group on Management of Data (SIGMOND). During the five-day event (June 10-15), several awards were presented to a select group of participants. One of the most coveted of these awards is the Best Demonstration Award, won this year by Professor Anastasia Ailamaki and her student Eleni Tzirita Zacharatou. Both are attached to EPFL’s Data-Intensive Applications and Systems Laboratory. Prof. Ailamaki is Lab Director and Ms Zacharatou is pursuing her doctoral program in computer and communication sciences.
The ACM Multimedia Systems Conference (MMSys 2018) was held between June 12 and 15 in Amsterdam. More than 30 papers were presented at the event under the “research track,” but there was only one winner for the Best Paper Award: a research conducted by Xavier Corbillon, Francesca De Simone, Gwendal Simon, and Pascal Frossard on “Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos.”
Each year, the Design Automation Conference (DAC) announces five winners of the Under-40 Innovators Award. This year, one of the winners of the coveted honor is David Atienza, Associate Professor of Electrical and Computer Engineering at EPFL’s Embedded Systems Laboratory.
The ISSS awards only two researches out of the scores of nominations received for consideration from across all Swiss institutes. That emphasizes the novelty of the study by Hamza Harkous.
The 39th IEEE Symposium on Security and Privacy concluded at San Francisco on May 23. It is considered to be one of the most prestigious events in the academic calendar each year as far as computer security and privacy issues are concerned.
Last month, Google announced the winners of its PhD Fellowship award for 2018. They include 39 researchers from North America, Europe, and the Middle East. Among them is Lana Josipović, a doctoral student in the Processor Architecture Laboratory led by Professor Paolo Ienne. She has been awarded for her outstanding research in the Systems and Networking domain.
The annual mega event at EcoCloud is just around the corner. In little over a fortnight, the Lausanne Palace Hotel will be a buzz of activity as it hosts the two-day EcoCloud annual event, slated for June 18–19. The venue’s prime location, which offers panoramic views of the city, Lake Geneva, and the magnificent Alps, will be an apt setting for industry experts to share insights on budding data and cloud computing platforms.
EcoCloud, the EPFL research center that drives today’s cloud computing technologies, warmly welcomes four new professors to its fold. They are Pascal Frossard, Carmela Troncoso, Robert West, and Paolo Ienne.
Each year, the IEEE Technical Committee on Cyber-Physical Systems (TCCPS) recognizes outstanding scientific contributions under various categories, including the Early- and Mid-Career awards. The winners for 2018 have just been announced by the Committee. Among the awardees is David Atienza, associate professor of electrical engineering and director of the Embedded Systems Laboratory (ESL) at EPFL. He has won the Mid-Career Award for “sustained contributions to thermal processor design and medical wearables.’’
The IBM PhD Fellowship Award, instituted in 1950 to recognize outstanding PhD students who drive innovation, is one of the most sought-after distinctions worldwide. Each year, only a chosen few make it to the elite group. Among the awardees for 2018 is Lefteris Kokoris-Kogias from EPFL’s Laboratory of Decentralized and Distributed Systems. His achievement is all the more creditable because he figured among the awardees for 2017 as well.
In March 2016, EPFL and the International Committee of the Red Cross (ICRC) signed a seminal agreement to establish the Humanitarian Tech Hub. The four-year program has opened many avenues of collaboration between the scientific and humanitarian fields. To further cement that relationship, ICRC has just announced the appointment of EPFL’s Edouard Bugnion to the ICRC Assembly.
Web browsing has become almost second nature to us. Each day, we plunge into tens of websites and unwittingly accept their long-winded privacy policies without bothering to peruse their stipulations. This is undoubtedly because those documents are shrouded in legalese too dense and cumbersome to read and digest. Yet, it is a well-known fact that many websites collect, store, and even use the private data that we inadvertently leave behind during our browsing sessions. Disturbingly, such practices are usually protected by the legal jargon contained in their privacy policies. So how do we ascertain the nature of data collected by a website? Is it possible to know how our data will be used by a website even before we start browsing that site?
Geo-replication is gaining ground for distributed services because it brings the services closer to the end users, reduces the page-load time, and increases user engagement. It also enables data platforms, such as that of Facebook, to survive data center failures. However, recent work has proven that no distributed data system can assure the best of desirable properties like low-latency access, partition tolerance, and strong consistency.
Training of large-scale machine-learning models is extremely challenging because the training data is much more than the memory capacity. However, scientists at IBM and EPFL have collaborated to develop a novel scheme that enables the use of accelerators such as GPUs and FPGAs to speed up the training of machine learning models. They presented their findings at the 31st Annual Conference on Neural Information Processing Systems (NIPS) in Long Beach, California.
Machine learning and artificial intelligence (AI) are finding new applications across industries. Many tasks that were performed by humans are now being handled by machines, adding efficiency to the output. But what would happen if AI crosses the threshold of human control and makes unilateral decisions? It is a frightening, but highly probable, scenario. In 2014, it prompted Google to consider the idea of a “big red button” to stop dangerous AI in an emergency. However, the challenge is not in being able to stop or interrupt an AI process but in preventing AI from biased learning due to such frequent interruptions. The biased learning can be extremely dangerous in multi-agent systems, where several machines are involved in an AI task.
The program in French can be found here.
Anastasia Ailamaki, Professor and Lab Director at the Data-Intensive Applications and Systems Laboratory (School of Computer and Communication Sciences), has just added another feather to the cap of EPFL’s research excellence. IEEE has included her as IEEE Fellow in the Class of 2018.
The Association for Computing Machinery (ACM) has named EPFL Professor Edouard Bugnion as ACM Fellow for 2017. This is ACM’s most prestigious member grade where only the crème de la crème of the computing research fraternity find admittance.
The research will ultimately contribute to the next generation of financial services and likely even more innovative applications of the technology not only here in Switzerland but globally.
The digital revolution is now all-pervasive, charting breakthroughs in computing and information technology. Driving that change is a group of leading innovators across the world. Among them is David Atienza, associate professor of Electrical and Computer Engineering and director of the Embedded Systems Laboratory at the School of Engineering, EPFL. In recognition of his outstanding scientific contributions to computing, the Association for Computing Machinery (ACM) has acknowledged him as a “pioneering innovator” and a “2017 Distinguished Member.”
The widespread availability of video streaming services and the proliferation of smartphones have enabled users to do away with the need to download heavy content and thus save storage space on their devices. But the service provider—be it YouTube, Netflix, or any other—has to face serious challenges in offering a seamless experience to users. Two of the major concerns are storage space on their servers, and the resultant power consumption. Conversely, the user is confronted with challenges like bandwidth issues, unstable streaming flow, and video encoding issues. However, a solution is in the making to enhance the user experience and simultaneously minimize the worries of the service provider.
Providers of payment systems and password-protected applications use advanced computation to ensure security of their services. It is generally accepted that if large numbers are used in developing a code, it becomes extremely difficult to solve the math and break the code. In this process, computation of discrete logarithms plays a crucial part. Until recently, the record for computing a discrete logarithm was in the multiplicative group of a 596-bit prime field. However that has now been surpassed in a collaborative research between EPFL and the University of Leipzig. The team has cracked an extremely lengthy code by using complex mathematical calculations.
In April this year, researchers at EPFL’s School of Computer and Communication Sciences (IC) gained recognition for exemplary work in computer science. While Vasileios Trigonakis was awarded the 2017 Eurosys Roger Needham Doctoral Dissertation Award, Immanuel Trummer bagged Honorable Mention for the 2017 SIGMOD Jim Gray Doctoral Dissertation Award.