Oct 17

A joint Stony Brook-BNL research team has found a way to capture the details of chemistry’s elaborate choreography as it happens.

Anatoly Frenkel (standing) with co-authors (l to r) Deyu Lu, Yuewei Lin, and Janis Timoshenko. (Photo: BNL)

Led by Anatoly Frenkel, a professor in Stony Brook University’s Materials Science and Chemical Engineering Department who has a joint appointment with Brookhaven National Laboratory‘s Chemistry Division, the team relied on computers that have learned to recognize the steps in a complex dance of atoms involved in chemical reactions. The findings should help them improve the performance of catalysts to drive reactions toward desired products faster.

The method—developed by an interdisciplinary team of chemists, computational scientists, and physicists at the U.S. Department of Energy’s Brookhaven Lab and Stony Brook University—is described in a new paper published in the Journal of Physical Chemistry Letters. The paper demonstrates how the team used neural networks and machine learning to teach computers to decode previously inaccessible information from x-ray data, and then used that data to decipher 3D nanoscale structures.

“The main challenge in developing catalysts is knowing how they work—so we can design better ones rationally, not by trial-and-error,” Frenkel said. “The explanation for how catalysts work is at the level of atoms and very precise measurements of distances between them, which can change as they react. Therefore it is not so important to know the catalysts’ architecture when they are made but more important to follow that as they react.”

Trouble is, important reactions—those that create important industrial chemicals such as fertilizers—often take place at high temperatures and under pressure, which complicates measurement techniques. For example, x-rays can reveal some atomic-level structures by causing atoms that absorb their energy to emit electronic waves. As those waves interact with nearby atoms, they reveal their positions in a way that’s similar to how distortions in ripples on the surface of a pond can reveal the presence of rocks. But the ripple pattern gets more complicated and smeared when high heat and pressure introduce disorder into the structure, thus blurring the information the waves can reveal.

So instead of relying on the “ripple pattern” of the x-ray absorption spectrum, Frenkel’s group figured out a way to look into a different part of the spectrum associated with low-energy waves that are less affected by heat and disorder.

“We realized that this part of the x-ray absorption signal contains all the needed information about the environment around the absorbing atoms,” said Janis Timoshenko, a postdoctoral fellow working with Frenkel at Stony Brook and lead author on the paper. “But this information is hidden ‘below the surface’ in the sense that we don’t have an equation to describe it, so it is much harder to interpret. We needed to decode that spectrum but we didn’t have a key.”


A sketch of the new method that enables fast, “on-the-fly” determination of three-dimensional structure of nanocatalysts. The neural network converts the x-ray absorption spectra into geometric information (such as nanoparticle sizes and shapes) and the structural models are obtained for each spectrum.

Fortunately Yuewei Lin and Shinjae Yoo of Brookhaven’s Computational Science Initiative and Deyu Lu of the Center for Functional Nanomaterials (CFN) had significant experience with so-called machine learning methods. They helped the team develop a key by teaching computers to find the connections between hidden features of the absorption spectrum and structural details of the catalysts.

“Janis took these ideas and really ran with them,” Frenkel said.

The team used theoretical modeling to produce simulated spectra of several hundred thousand model structures, and used those to train the computer to recognize the features of the spectrum and how they correlated with the structure.

“Then we built a neural network that was able to convert the spectrum into structures,” Frenkel said.

When they tested to see if the method would work to decipher the shapes and sizes of well-defined platinum nanoparticles (using x-ray absorption spectra previously published by Frenkel and his collaborators) it did.

“This method can now be used on the fly,” Frenkel said. “Once the network is constructed it takes almost no time for the structure to be obtained in any real experiment.”

Oct 18

Professor Shu Jia, in the Department of Biomedical Engineering of the College of Engineering and Applied Sciences and the School of Medicine, received a $1.97M, five year Maximizing Investigators’ Resource Award (MIRA) from the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH). The goal of MIRA is to increase the efficiency of NIGMS funding by providing investigators with stability and flexibility to enhance productivity and foster cutting edge scientific breakthroughs.

Shu Jia with research team

Jia’s research, “Exploring Single-Molecule Biophotonics for Ultrahigh-Resolution Spatiotemporal-Multiplexed Optical Microscopy” focuses on new technological developments to understand the distribution and interactions of molecules in three-dimensionally organized cellular networks that are fundamental to the function of living systems.

“When light comes out of traditional microscopes, it always has a focal spot, and the spot will always have a finite size. That limits how small we can observe in, for example, a biological sample of a cell.” Jia explained. “Our goal is to break this limit.”

To date, a complete understanding of how local molecular mechanisms are integrated over larger scale to support tissue functions, or contribute to disease initiation, is still lacking. The challenges are due to limitations in imaging technology to provide molecular specificity, nanometer-scale resolution, and ultrafast speed across larger volumes of tissue. The proposed research plan investigates the physical and engineering principles underlying optical imaging in complex biological materials, and utilizes these principles to develop new biophotonic tools for next-generation light microscopy.

“This is interdisciplinary research between engineering, biology, and medicine, so in the lab we have researchers from physics, electrical engineering, optics, and computer science,” said Jia. “We’ll develop it and collaborate with biologists to tackle the problem.”

In the long-term, the proposed program is expected to not only provide groundbreaking insights for brain study, but also open up many new pathways to a broad range of biomedical research, and enable discoveries that will address the challenges of human well-being.

“The collaborative and cross-cutting research in Professor Jia’s lab is at the heart of what we strive for here at Stony Brook,” said Fotis Sotiropoulos, Dean of the College of Engineering and Applied Sciences. “We look forward to the many engineering breakthroughs that will come from his lab as a result of this grant over the next five years.”

Previously, Professor Jia also received funding from DARPA and NSF in 2016 to support his next-generation optical imaging research. The Jia Laboratory aims to attain a better understanding of the molecular basis for the functions of tissues and organisms. To achieve the goal, the group investigates the physical and engineering principles underlying single-molecule imaging in complex biological materials, and utilizes these principles to develop new biophotonic methods for super-resolution microscopy. These methods include optical physics, optical wavefront engineering, single-molecule biophysics, adaptive optics, phase microscopy, large-data processing, advanced instrumentation, and nano-fabrication.

First trained as an applied physicist and electrical engineer and later as a bioimaging expert, Professor Jia is passionate about advancing imaging technology with new physical concepts and engineering design. He received his PhD in electrical engineering and PhD minor in physics from Princeton University and was a postdoctoral fellow at Harvard University from 2010-2014. Professor Jia has been an assistant professor in the Department of Biomedical Engineering since 2015.

Oct 18

Penguins are noisy, as any visitor to an aquarium knows. Penguins may be noisy in others ways too, according to a new study published in Nature Communications. Scientists have long used Adélie penguin populations to monitor the health of the Southern Ocean and to understand how major factors such as fishing and climate change impact the oceans and the animals that rely on them. Now an extensive analysis of all known data on Adélie penguin populations over the last 35 years has found that only a small fraction of year-to-year changes in Adélie penguin populations can be attributed to measurable factors such as changes in sea ice.

A new study reveals that it is difficult for scientists to understand fluctuations of Adélie penguin populations in Antarctica from year-to-year.

Instead, most of the short term fluctuations in the number of penguins breeding has no known cause; such ‘noise’ in the system is likely due to a host of marine and terrestrial factors that have not, or cannot, be measured at the majority of sites where penguins breed.

 “In many ways, our study shows that watching Adélie penguin abundance may be like watching the stock market—short term fluctuations may be exceptionally hard to predict and may not signal any change in the fundamental health of the system,” explains senior author Heather Lynch, Associate Professor of Ecology & Evolution at Stony Brook University.

“Therefore, adaptive management of marine resources, whereby we stand ‘at the ready’ to adjust our conservation strategy as new data are collected, may be as difficult, and as risky, as trying to time the stock market. Instead, our results suggest that to the extent Adélie penguins are used as a barometer of ecosystem health, the true dynamics may emerge only very slowly.”

This finding, detailed in the paper “Pan-Antarctic analysis aggregating spatial elements of Adélie penguin abundance reveals robust dynamics despite stochastic noise,” is important because it means that tracking abundance at individual colonies, one of the cornerstones of monitoring the health of the Antarctic ecosystem, may not provide a reliable signal on short time scales.

“By analyzing the data, we found that relatively little of the year-to-year variability in Adélie penguin abundance could be linked to something in the environment we can actually measure,” said lead author Dr. Christian Che-Castaldo, a postdoctoral researcher in the Department of Ecology & Evolution at Stony Brook University. “Precipitation at the site is one factor we know is likely to drive some of this unexplained variation, but like many other potential factors, it’s not one we can easily measure in Antarctica.”

Heather Lynch

“This doesn’t mean that monitoring isn’t important, only that we may have to adopt an even more conservative strategy for conserving marine resources. In the face of so much uncertainty, we may not detect a real decline until it’s already too late,” Dr. Lynch explained.

Adélie penguins are one of four species of penguins with significant breeding populations in the Antarctic. Adélie penguins are the most well studied of all penguin species and, being distributed around the entire coastline of the Antarctic continent, are often considered the “canaries in the coal mine” for anthropogenic threats like fishing and climate change.

In this study, the authors analyzed data from all 267 Adélie penguin populations in Antarctica stretching back to 1979, using data collated from the scientific literature under the auspices of a NASA-funded tool called the Mapping Application for Penguin Populations and Predicted Dynamics (MAPPPD).

They used a statistical technique known as hierarchical Bayesian modelling to accommodate the fact that most Adélie penguin breeding locations are surveyed only rarely. Finding a statistically-rigorous way to ‘fill in’ missing data was key to the effort, since it allowed the research team to look at the population dynamics of penguins at larger spatial scales than has been possible in the past.

Dr. Lynch emphasized that not only did the research uncover more details about the increase in Adélie penguin populations over the last three decades, but it suggests that monitoring more breeding colonies sporadically, rather than fewer sites consistently, may provide more timely and more reliable information for policymakers, despite short term fluctuations common in Adélie colonies.

The study also illustrates a new method of tracking Adélie penguin populations throughout the entire continent rather than at selected study sites where the majority of the data are actually collected. They hope to study other penguin species in Antarctica using the same method.

“The findings, overall, provide clear guidance on how to extract the most information from our monitoring efforts, and highlight the benefits of working across disciplines for effective conservation,” added co-author Dr. Jenouvrier at WHOI.

Co-investigators of the research included scientists from the Woods Hole Oceanographic Institution in Woods Hole, Ma.; the National Center for Atmospheric Research in Boulder, Co.; the Department of Natural Resource and Environmental Science in Reno, Nv.; the University of South Florida in St. Petersburg, Fla.; and the Centre d’Edudes Biologiques de Chize in France.

This work was funded by the National Aeronautics and Space Administration (NASA) Ecosystem Forecasting program and by the National Science Foundation’s Office of Polar Programs.

Oct 18

For decades, statistical agencies such as the United Nations, the U.S. Census Bureau and Eurostat have provided data and analyses of population aging, assuming that the only characteristic that was relevant to the study of population aging was chronological age. But this is not the case.

Sixty-five-year-olds today have longer remaining life expectancies and score higher on tests of cognitive functioning than 65-year-olds in the past. Data on population aging that ignore the changing characteristics of people produce a distorted picture of the extent of population aging in the future.

Warren Sanderson, a professor in the Department of Economics at Stony Brook University, and Sergei Scherbov, from the International Institute for Applied Systems Analysis in Laxenburg, Austria, have produced new measures of population aging that take the changing characteristics of people into account.

Some of their measures appeared in the Highlights to the UN’s ReportWorld Population Ageing, 2017. For the first time, people now have a choice between two types of population aging measures from the United Nations — measures that take the changing characteristics of people into account and those that do not.

This is the first time that research from a Stony Brook professor has been tabulated in an official UN demographic report.

Sep 07

Despite centuries of studying the atom and the particles within it, the mysteries of matter continue to elude scientists. What are we really made of?

An Electron-Ion Collider would probe the inner microcosm of protons to help scientists understand how interactions among quarks (colored spheres) and glue-like gluons (yellow) generate the proton’s essential properties and the large-scale structure of the visible matter in the universe today.
To solve such an enigma and better understand the building blocks of our universe, Stony Brook University and the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory (BNL) have partnered to establish the Center for Frontiers of Nuclear Science, bolstered by a new $5 million grant from the Simons Foundation.

“The Center for Frontiers in Nuclear Science will bring us closer to understanding our universe in ways in which it has never before been possible,” said Samuel L. Stanley Jr., MD, President of Stony Brook University. “Thanks to the vision of the Simons Foundation, scientists from Stony Brook, Brookhaven Laboratory and many other institutions are now empowered to pursue the big ideas that will lead to new knowledge about the structure of everything in the universe today.”

Establishing the Center is a big step toward discovering the unknown essentials of matter for Stony Brook and BNL, which already have internationally renowned programs in nuclear physics. But before solving such a mystery, one must first know the clues. Here’s a quick breakdown.

Matter is any substance that has mass and takes up space. An atom is the smallest unit of matter. At an atom’s core is its nucleus, made of protons of neutrons — subatomic particles collectively called nucleons. Looking deeper, nucleons are made of elementary particles called quarks and gluons, and this is where the trail goes cold.

“The role of quarks and gluons in determining the properties of protons and neutrons remains one of the greatest unsolved mysteries in physics,” said Doon Gibbs, Ph.D., Brookhaven Lab Director.

Solving this mystery is the focus of quantum chromodynamics (QCD), a branch of theoretical physics that investigates how quarks and gluons interact as fundamental elements of matter.

Stony Brook and BNL’s new center is slated to become a leading international research and educational hub for QCD over the next several decades, uniting our faculty, students and researchers with BNL staff and scientists from around the world in an effort to crack the quantum case.

One key aspect of the Center’s launch is a proposed Electron Ion Collider (EIC), a powerful new particle accelerator that would create rapid-fire, high-resolution “snapshots” of quarks and gluons contained in nucleons and complex nuclei — crucial to QCD progress.

Abhay Deshpande, PhD, Professor of experimental nuclear physics in the Department of Physics and Astronomy in the College of Arts and Sciences at Stony Brook University
“An Electron Ion Collider would reveal the internal structure of these atomic building blocks, a key part of the quest to understand the matter we’re made of,” Gibbs said.

Abhay Deshpande, professor of experimental nuclear physics in the Department of Physics and Astronomy, has been named Director of the Center, as well as Director of Electron Ion Collider Science at BNL.

A champion of the EIC for decades, Deshpande is positioned to lead development of the collider, which was deemed highest priority for new facility construction by the National Science Foundation’s Nuclear Science Advisory Committee in an effort to strengthen and expand U.S. leadership in nuclear physics and stimulate economic benefits well into the 2040s.

Like most mysteries, collaboration is the key to success, so Deshpande is focused on uniting QCD and EIC experts from around the globe with Stony Brook students who will serve as the next generation of researchers in the field.

“Overall, I want the worldwide community of EIC enthusiasts to see the Center for Frontiers in Nuclear Science as their ‘home away from home,’ where they can come and work on EIC-related research,” Deshpande said. “My hope is that within a short time, the students at Stony Brook will have more opportunities to work with researchers at Brookhaven, and vice-versa.”

Despite the complexity of nuclear physics and related areas of study, the results of such research could reveal the most basic aspects of our very existence.

“Nuclear physics is a deep and important discipline, casting light on many poorly understood facets of matter in our universe,” said Jim Simons, chairman of the Simons Foundation. “It is a pleasure to support research in this area conducted by members of the outstanding team to be assembled by Brookhaven Lab and Stony Brook University.”

Through major funding, the Simons Foundation is bonding a partnership between Stony Brook and BNL perhaps as strong as the interaction between quarks and gluons.

“Basic science research seeks to improve our understanding of the world around us, and it can take human understanding to wonderful and unexpected places,” said Marilyn Simons, president of the Simons Foundation. “Exploring the qualities and behaviors of fundamental particles seems likely to do just that.”

— By Brian Smith

Sep 07

Scientists have yet to understand and explain how life’s informational molecules – proteins and DNA and RNA – arose from simpler chemicals when life on earth emerged some four billion years agoScientists have yet to understand and explain how life’s informational molecules – proteins and DNA and RNA – arose from simpler chemicals when life on earth emerged some four billion years ago. Now a research team from the Stony Brook University Laufer Center for Physical and Quantitative Biology and the Lawrence Berkeley National Laboratory believe they have the answer. They developed a computational model explaining how certain molecules fold and bind together to grow longer and more complex, leading from simple chemicals to primitive biological molecules. The findings are reported early online in PNAS.

Ken Dill
Ken Dill explains the computational model that shows how certain molecules fold and bind together in the evolution of chemistry into biology, a key step to explain the origins of life.
Previously scientists learned that the early earth likely contained the basic chemical building blocks, and sustained spontaneous chemical reactions that could string together short chains of chemical units. But it has remained a mystery what actions could then prompt short chemical polymer chains to develop into much longer chains that can encode useful protein information. The new computational model may help explain that gap in the evolution of chemistry into biology.

“We created a computational model that illustrates a fold-and-catalyze mechanism that amplifies polymer sequences and leads to runaway improvements in the polymers,” said Ken Dill, lead author, Distinguished Professor and Director of the Laufer Center. “The theoretical study helps to understand a missing link in the evolution of chemistry into biology and how a population of molecular building blocks could, over time, result in the emergence of catalytic sequences essential to biological life.”

In the paper, titled “The Foldamer Hypothesis for the growth and sequence-differentiation of prebiotic polymers,” the researchers used computer simulations to study how random sequences of water-loving, or polar, and water-averse, or hydrophobic, polymers fold and bind together. They found these random sequence chains of both types of polymers can collapse and fold into specific compact conformations that expose hydrophobic surfaces, thus serving as catalysts for elongating other polymers. These particular polymer chains, referred to as “foldamer” catalysts, can work together in pairs to grow longer and develop more informational sequences.

This process, according to the authors, provides a basis to explain how random chemical processes could have resulted in protein-like precursors to biological life. It gives a testable hypothesis about early prebiotic polymers and their evolution.

“By showing how prebiotic polymers could have become informational ‘foldamers’, we hope to have revealed a key step to understanding just how life started to form on earth billions of years ago,” explained Professor Dill.

Co-authors of the paper include Elizaveta Guseva of the Laufer Center and Departments of Chemistry and Physics & Astronomy at Stony Brook University, and Ronald N. Zuckermann of the Lawrence Berkeley National Laboratory in Berkeley, Calif.

The research was supported in part by the National Science Foundation.

Sep 18

In 2017, Stony Brook graduate student and ethnomusicologist Jay Loomis and assistant professor of computer science Roy Shilkrot teamed up to secure a grant to create 3D printed replicas of ancient wind instruments.

Assistant Professor of Computer Science Roy Shilkrot, left, and grad student and ethnomusicologist Jay Loomis collaborate on creating 3D replicas of ancient wind instruments.

The goal? To give museum-goers an opportunity to interact with rare instruments rather than merely viewing them through a glass enclosure.

Loomis had been interested in wind instruments since he was a boy in Wisconsin, when he was struck deeply by flute music wafting from his car radio. After he moved to Long Island, his thirst for playing dovetailed with an insatiable curiosity about indigenous musical instruments. He hoped to build such instruments, as a way of sharing aspects of Native American culture with the public.

In his travels as an academic, he encountered musical virtuosos, acoustic experts and computer scientists who shared his passion. That passion gained momentum when Loomis became a teaching assistant at cDACT, the Stony Brook-based Consortium for Digital Art, Culture and Technology.

Through cDACT Director Margaret Schedel, Loomis connected first with Shilkrot and later Hideo Sekino, a visiting professor from Tokyo Institute of Technology, who is associated with the Institute for Advanced Computational Science at Stony Brook.

In spring 2017, Loomis and Shilkrot developed a 3D scanner and used desktop and professional 3D printers to recreate playable replicas of wind instruments, including flutes, ceramic ocarinas and whistles of different shapes and sizes. An integral part of the process was to recreate the sound of the original instrument and mirror its physical characteristics as well.

The greatest challenge the collaborators experienced was in designing the cavity of the instrument, which was essential to recreating the authentic sound.

The results were encouraging but weren’t as precise as Loomis wanted. Schedel recommended collaborating with Sekino due to his interest in the traditional Japanese flute known as a shakuhachi. After she introduced the two musicians, Loomis was inspired to feature the instrument in an electronic piece he co-composed with Timothy Vallier.

Sep 21

A team of researchers in the Department of Computer Science was recently awarded $3.5M by the Office of Naval Research to support “debloating,” a process that could help guard against security breaches that threaten the privacy and integrity of personal data.

Professors R. Sekar, left, and Michalis Polychronakis, in the classroom

Debloating is the process of removing and streamlining code, thus enhancing software performance as well as security. As part of the researchers’ debloating project, titled “Multi-layer Software Transformation for Attack Surface Reduction and Shielding,” Professors R. Sekar and Michalis Polychronakis will leverage recent advances they have made in binary code analysis and transformation to remove code bloat and tighten security of today’s software.

“Our project is based on the experience and insight gained from our prior research in this area,” said Polychronakis, a cybersecurity expert who joined the Department of Computer Science as an assistant professor in 2015. “To keep it well-managed and to optimize effectiveness, we specifically targeted three main areas: code analysis foundations, debloating and dynamic attack surface reduction, and software shielding,”

The funding is particularly timely in light of recent news that one of the country’s largest credit reporting agencies, Equifax of Atlanta, was the victim of hacking on a scale that has not been seen in years, exposing Social Security numbers and driver’s license numbers of 143 million U.S. citizens.

So why has cybersecurity become such a problem?

One issue arises from the latest software development practices, which can turn out new programs and products for advanced speed and convenience in record time. Unfortunately, the increased coding, or “code bloat,” creates a larger attack surface with a proliferation of security vulnerabilities, just waiting for hackers. These recent advances in software development often result in the need for constant system updates or bug fixes.

But failure to implement these fixes can result in breaches — some of which, like the Equifax hack, can result in the mass exposure of private data.

“This is the absolute worst digital data breach in recorded history,” said Radu Sion, professor in the Department of Computer Science, and founder of Stony Brook’s National Security Institute. “Not only is its magnitude staggering, but its implications are bordering on disastrous and are likely to haunt us for decades.”

Radu Sion of Stony Brook’s National Security Institute

This is because the type data leaked are much more important than email account login info or targeted phishing results, Radu said. As a culture dependent on technology and thus more coding across our digital infrastructure, we have left ourselves vulnerable because we value growth in the market over stronger security, he explained.

“The attack surface will be reduced by removing unnecessary code and restricting capabilities of remaining code,” said Sekar, who received his PhD from Stony Brook in 1991. “We plan to disrupt unintended data flows that are often used in exploits and freeze data that does not need to be modified during operation.”

New protection mechanisms will help shield software against exploitation while significantly advancing control-flow containment, code isolation and diversification, Sekar added.

“Professors Sekar and Polychronakis’ transformative work is critical to addressing the issues we face in today’s era of exponential technological growth,” said Fotis Sotiropoulos, dean of the College of Engineering and Applied Sciences (CEAS). “I congratulate them on this recognition from the Office of Naval Research, and thank them for their important contributions to the College and to Stony Brook University.”

This funding comes to Stony Brook through an Office of Naval Research Broad Agency Announcement that seeks “innovative scientific and technological solutions to address U.S. Navy and Marine Corps” challenges. The Department of Computer Science, part of CEAS, has received nearly $7 million in research awards this summer. According to Samir Das, the department chair, cybersecurity research conducted through Stony Brook’s National Security Institute represents more than 60 percent of the summer research funding.“Unfortunately, this is not the last breach to expect,” Sion said.

About the Researchers

R. Sekar is a graduate of the Department of Computer Science at Stony Brook, earning his PhD in 1991. His research focus is on software and systems security, and on solving practical problems and building real systems including software vulnerability mitigation, malware, intrusion detection, and management of distributed systems.

Michalis Polychronakis joined the Department of Computer Science as an assistant professor in 2015 and earned his PhD in computer science from the University of Crete, Greece. Before joining Stony Brook, he was an associate research scientist at Columbia University. His research focuses on network and system security, network monitoring and measurement, and online privacy.

Aug 03

Alum Bryan Perozzi, now a research scientist at Google, won the Association of Computing Machinery SIGKDD, KDD 2017 Doctoral Dissertation award for his work at Stony Brook University. The annual award acknowledges excellent doctoral research in the field of data mining and knowledge discovery.

Bryan Perozzi and Steven Skiena

Perozzi thesis, Local Modeling of Attributed Graphs: Algorithms and Applications, was recognized as the best dissertation of the year in the data science community. His work involves graph embeddings — ways of representing the knowledge encoded in the structure of networks to make them accessible for machine learning models.

Focused on developing scalable algorithms and models for attributed graphs, Perozzi presented an online learning algorithm utilizing recent advances in deep learning to result in rich graph embeddings. The applications of this research are far reaching for the fields of data mining, information retrieval, profiling and demographic inference, online advertising and fraud detection.

Perozzi, whose advisor was Stony Brook Professor Steven Skiena, defended his thesis in May 2016. Upon learning of the award, he said, “Wow, what an honor! I’m humbled to have my work recognized by this prestigious early career award, and I am looking forward to giving a talk during the Doctoral Dissertation Award session on August 15.” The KDD 2017 Conference takes place in Nova Scotia, August 13-17.

Professor Skiena is especially proud of Perozzi’s research accomplishments, and they are collaborators on a number of published works. Their paper on DeepWalk graph embeddings has already been cited 270 times in Google Scholar since its publication in 2014.

“Bryan was a very creative, hardworking and independent graduate student here at Stony Brook, and his work on DeepWalk has proven extremely influential in the data science and machine learning communities. They got the right man for this award,” said Skiena.

At Google, Perozzi’s research relates to the intersection of data mining, machine learning, graph theory, and network science with a particular focus on local graph algorithms. In January 2017, he published and presented Ties that Bind: Characterizing Classes by Attributes and Social Ties, a collaboration with Stony Brook PhD student Aria Rezaei and Carnegie Melon faculty Leman Akoglu.

Perozzi is the first PhD student in the Department of Computer Science, which is part of the College of Engineering and Applied Sciences at Stony Brook University, to receive this award.

About the Association for Computing Machinery
Founded in 1947, the ACM is the largest and oldest scientific and industrial computing society. SIGKDD is the ACM’s Special Interest Group on Knowledge Discovery and Data Mining. SIGKDD selects one winner and two runner-ups each year to receive the award. Selections are based on the relevance to KDD, originality, scientific significance, technical depth and soundness, and overall presentation and readability.

Aug 11

Researchers in the Departments of Computer Science, and Applied Mathematics and Statistics awarded $449k through the National Science Foundation’s NeTS program.

Anshul Gandhi, left, and Zhenhua Liu

Even for the personal smartphone or home computer user there is no avoiding the use of cloud computing. Cloud computing is low in cost, easily available, and offers access to useful services that would otherwise be out of reach. Services such as Netflix, Amazon Fire, and Expedia are only some of the popular online services being hosted on the cloud. On the backend, dynamic applications in the cloud are more lucrative if their deployments grow through dynamic capacity provisioning. Software deployments must be carefully provisioned to meet their performance requirements without wasting resources.

Most resource provisioning solutions today employ predictions to estimate demand and provide resources, accordingly. At times, this process could be fraught with errors. With the support of a National Science Foundation (NSF) Networking Technology and Systems (NeTS) award of $449k researchers Anshul Gandhi and Zhenhua Liu, seek to bridge the gap between predictors and provisioning solutions.

The goal of their NeTS project, Demystifying the Role of Prediction Models: Bridging Prediction Algorithms and Resource Provisioning, is to develop and leverage error models to fully realize the potential of predictors. According to Gandhi, “Our research will allow businesses to maximize resource utilization despite prediction errors.”

“This is the kind of cross-cutting research we encourage among our faculty, to advance technologies that push the boundaries and challenge traditional thinking,” said Fotis Sotiropoulos, Dean of the College of Engineering and Applied Sciences. “I applaud Professors Gandhi and Liu on their collaborative approach to this research, and congratulate them on this recognition from the NSF. I look forward to following the progress of their research.”

Gandhi and Liu will investigate the prediction error model which includes constructing models that capture the structure of prediction errors; developing an algorithmic framework; and designing systems to exploit the new prediction error-aware algorithms.

Joseph Mitchell, chair of the Department of Applied Mathematics and Statistics, said, “This is a compelling project that requires collective expertise from computer science, optimization, probability, and statistics, and represents an ideal collaboration between Computer Science and Applied Mathematics and Statistics, both in research and in educational impact.”

Gandhi and Liu will realize additional benefits of their research through technology transfer opportunities with industrial partners.

NSF identified this NeTS project as “transformative research” related to fundamental scientific and technological advances in networking as well as systems research. NSF funds projects such as these in the hope that it will lead to “the development of future-generation, high-performance networks and future internet architectures”.

Arie E. Kaufman, chair of the Department of Computer Science, said, “In addition to finding the answer to network performance challenges, this project is especially interesting because it will directly contribute to interdisciplinary courses taught in two major departments on campus.”

About the Researchers
Anshul Gandhi is an assistant professor in the Department of Computer Science and he is affiliated with the Department of Applied Mathematics and Statistics, and Stony Brook University’s Smart Energy Technologies Cluster. He earned his PhD in computer science from Carnegie Mellon University, where he was advised by Prof. Mor Harchol-Balter. Prior to joining Stony Brook, he spent a year as a post-doctoral researcher in the Cloud Optimization and Analytics group at the IBM T.J. Watson Research Center.

Assistant Professor Zhenhua Liu is currently based in the Department of Applied Mathematics and Statistics, and he is affiliated with Department of Computer Science, and Smart Energy Technology Cluster. He was recently on leave for the ITRI-Rosenfeld Fellowship in the Energy and Environmental Technology Division at Lawrence Berkeley National Laboratory during the year 2014-2015. Dr. Liu earned his PhD in computer science at the California Institute of Technology.

Gandhi and Liu also recently received another NSF award, titled Enhancing the Parasol Experimental Testbed for Sustainable Computing, as part of an infrastructure grant led by Rutgers University to study sustainable computing in datacenters, which is aligned with the Smart Energy Technology cluster’s objectives.

Both the Department of Computer Science and the Department of Applied Mathematics and Statistics are part of the College of Engineering and Applied Sciences at Stony Brook University.

–Christine Cesaria


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