August 2017

Physics and Astronomy Professors Receive DOE Early Career Awards

Two Stony Brook University Department of Physics and Astronomy faculty in the College of Arts and Sciences recently received the Department of Energy (DOE) Early Career Award for their individual research projects related to the discovery of dark energy and dark matter.  

Marilena Loverde, left, and Anja von der Linden

Assistant Professor Anja von der Linden was awarded for her project, “Towards Precision Cluster Cosmology with Large Synoptic Survey Telescope (LSST)”; Assistant Professor Marilena Loverde, also appointed in the Yang Institute for Theoretical Physics,  was awarded for “Discovering Dark Energy, Dark Matter, and Neutrino Properties with Cosmic Structure.”  Each will receive $750,000 over five years to develop their research.

“This is a wonderful distinction for both Professors von der Linden and Loverde, whose research programs will greatly help us further understand the origin and evolution of the Universe,” said Stony Brook University President Samuel L. Stanley Jr. “The Department of Physics is fortunate to have these scientists among its faculty, both of whom are well deserved of the prestigious Department of Energy Early Career Award.”

The Early Career Research Program, now in its eighth year, supports the development of individual research programs of outstanding scientists during the crucial early career years and simulates research careers in the disciplines supported by the DOE Office of Science.

“Marilena Loverde and Anja von der Linden’s work exemplifies the world-class research being conducted by our outstanding faculty,” says Michael A. Bernstein, Provost and Senior Vice President for Academic Affairs at Stony Brook University. “We are tremendously pleased about this much-deserved recognition for two of our rising stars.”

Both von der Linden’s and Loverde’s research programs address the mystery of the composition of the Universe: less than five percent is in a form of matter familiar to us – planets, stars, gas, photons, and neutrinos. The vast majority of the Universe is in the form of dark matter (about 25 percent) and dark energy (about 70 percent). While dark matter is a form of matter that does not interact with us apart from gravity, dark energy is even more mysterious — it describes the puzzling fact that the expansion of the Universe is accelerating, rather than slowing down due to gravity.  Prof. von der Linden compares it to ”throwing a ball up in the air, and, after initially slowing down, seeing it accelerate upwards.”  

The Department of Energy is involved in several large cosmic surveys, which will provide precision maps of the Universe on the largest scales. These maps themselves are snapshots of the Universe over the past several billion years of cosmic history. From them, we can study the origin and evolution of structure in our Universe and learn about dark energy, dark matter, and the elusive neutrino. Professor Loverde’s research focuses on the theoretical framework for modeling and interpreting cosmic structure; Professor von der Linden’s research focuses on measurements of the distribution of the largest objects in the Universe, clusters of galaxies, as a way of quantifying cosmic structure.

Marilena Loverde

“My research will develop the theory of structure formation in the presence of cosmic neutrinos and other novel types of matter,” Professor Loverde said. “Despite being the second most abundant particle in the known universe, we don’t know how much the neutrino weighs. This is something we hope to learn from cosmic surveys, but we need a more complete theory of cosmic structure formation.  My primary goal is to make sure that our models are sufficiently accurate to detect the neutrino mass, but this work will also generate new tools to study dark matter, dynamical dark energy, and structure formation in the Universe.”

“Solving the puzzle of dark energy requires precision measurements of the expansion history and evolution of structure of the Universe,” Professor von der Linden said. “Clusters of galaxies provide particularly powerful measurements of the Universe,  as the number of clusters as a function of mass and its evolution with time is very sensitive to the details of the inner workings of the Universe, including the properties of dark energy, dark matter, and the masses of neutrinos.  The challenge for cluster cosmology lies in accurately measuring the masses of clusters, and the most promising technique to determine the absolute mass calibration of clusters is through weak gravitational lensing.”

Loverde’s research aims to develop theoretical templates for several large DOE projects, including the Large Synoptic Survey Telescope (LSST), the Dark Energy Spectroscopic Instrument (DESI), and a Stage IV Cosmic Microwave Background (CMB-S4) survey. von der Linden’s project aims to provide the precision measurements necessary to compare to theoretical predictions; in this case, cluster mass estimates based on the weak-lensing capabilities of LSST.  The 8.4-meter LSST is currently being constructed in Chile, and will feature the largest digital camera ever built, with over 3200 megapixels (the sensors for the camera are being developed at nearby Brookhaven National Lab).  

“Professors  von der Linden and Loverde are pursuing one of the central questions in cosmology:  95% of the matter in the Universe is unaccounted for,” says Sacha Kopp, Dean of the College of Arts and Sciences. “Their studies bring us closer to understanding the make-up and origin of the Universe.”

Starting in 2023, LSST will image the entire night sky once every three nights, and continue to do so for 10 years.

Anja von der Linden

This will create the deepest image of the Universe over half of the entire sky.  LSST will sensitively measure the shapes and distances of billions of galaxies.  “Weak lensing” refers to the statistical analysis of these in order to infer the distortion of space-time due to the matter distribution of the Universe. The purpose of von der Linden’s project is to develop and test techniques necessary to utilize LSST weak-lensing data for cluster cosmology, and apply them to targeted pre-cursor as well as LSST data.  

“This award is fantastic news for our research group, and I am grateful to the DOE for supporting our work,”  von der Linden says. “LSST will be a tremendously exciting project, and I look forward to Stony Brook taking part in it. The results of our project will enable cluster surveys to harness their tremendous statistical potential and be a leading probe of cosmology in the next decade.”

“I am absolutely thrilled to receive this award,” Loverde says. “I’m extremely grateful to the Department of Energy for this support. This is a huge boost for the cosmology group here at Stony Brook University, and I’m excited about the work ahead.”

Prior to joining the College of Arts and Sciences Department of Physics and Astronomy in 2015, Professor von der Linden was a Tycho Brahe fellow at the DARK Cosmology Centre in Copenhagen and the Kavli Institute for Particle Astrophysics and Cosmology (KIPAC), Stanford University. She received her PhD in astrophysics from the Max-Planck-Institute for Astrophysics, Garching, Germany, and the Ludwig-Maximilians-Universität, München, Germany.

Professor Loverde joined Stony Brook College of Arts and Sciences in 2015, holding a joint appointment in the C.N. Yang Institute for Theoretical Physics (YITP) and the Department of Physics and Astronomy. She received a BA in Mathematics and Physics from the University of California, Berkeley, in 2003, and a PhD in Physics from Columbia University in 2009. Prior to joining Stony Brook University she was a postdoctoral fellow at the University of Chicago and at the Institute for Advanced Study.

— Rachel Rodriguez

Scientists Find New Method to Control Electronic Properties of Nanocrystals

Researchers from Stony Brook University, Brookhaven National Laboratory and the Hebrew University of Jerusalem have discovered new effects of an important method for modulating semiconductors.


The method, which works by creating open spaces or “vacancies” in a material’s structure, enables scientists to tune the electronic properties of semiconductor nanocrystals (SCNCs) — semiconductor particles that are smaller than 100 nanometers. This finding will advance the development of new technologies like smart windows, which can change opaqueness on demand.

Anatoly Frenkel, a professor in Stony Brook’s Department of Materials Science and Chemical Engineering in the College of Engineering and Applied Sciences, holds a joint appointment at Brookhaven National Laboratory and was the lead BNL researcher on this study.

Scientists use a technique called “chemical doping” to control the electronic properties of semiconductors. In this process, chemical impurities — atoms from different materials — are added to a semiconductor in order to alter its electrical conductivity. Though it is possible to dope SCNCs, it is very difficult due to their tiny size. The amount of impurities added during chemical doping is so small that in order to dope a nanocrystal properly, no more than a few atoms can be added to the crystal. Nanocrystals also tend to expel impurities, further complicating the doping process.

Seeking to control the electronic properties of SCNCs more easily, researchers studied a technique called vacancy formation. In this method, impurities are not added to the semiconductor; instead, vacancies in its structure are formed by oxidation-reduction (redox) reactions, a type of chemical reaction where electrons are transferred between two materials. During this transfer, a type of doping occurs as missing electrons, called holes, become free to move throughout the structure of the crystal, significantly altering the electrical conductivity of the SCNC.

“We have also identified size effects in the efficiency of the vacancy formation doping reaction,” said Uri Banin, a nanotechnologist from the Hebrew University of Jerusalem. “Vacancy formation is actually more efficient in larger SCNCs.”

In this study, the researchers investigated a redox reaction between copper sulfide nanocrystals (the semiconductor) and iodine, a chemical introduced in order to influence the redox reaction to occur.

“If you reduce copper sulfide, you will pull out copper from the nanocrystal, generating vacancies and therefore holes,” said Frenkel.

The researchers used the x-ray powder diffraction (XPD) beamline at the National Synchrotron Light Source II (NSLS-II)—a DOE Office of Science User Facility—to study the structure of copper sulfide during the redox reaction. By shining ultra-bright x-rays onto their samples, the researchers are able to determine the amount of copper that is pulled out during the redox reaction.

Based on their observations at NSLS-II, the team confirmed that adding more iodine to the system caused more copper to be released and more vacancies to form. This established that vacancy formation is a useful technique for tuning the electronic properties of SCNCs.

Still, the researchers needed to find out what exactly was happening to copper when it left the nanocrystal. Understanding how copper behaves after the redox reaction is crucial for implementing this technique into smart window technology.

“If copper uncontrollably disappears, we can’t pull it back into the system,” Frenkel said. “But suppose the copper that is taken out of the crystal is hovering around, ready to go back in. By using the reverse process, we can put it back into the system, and we can make a device that would be easy to switch from one state to the other. For example, you would be able to change the transparency of a window on demand, depending on the time of day or your mood.”

Stony Brook Receives $1M for Transformative Research on the Aging Brain

The U.S. has a population of more than 50 million seniors for the first time in history. As that number climbs, Stony Brook University has received a three-year $1 million grant from the W.M. Keck Foundation to fund research that uses brain imaging data to understand how the nutrition of brain neurons affects cognition in aging humans. The research could provide a critical first step toward personalized medicine in neurology for aging patients.

This collaborative project is led by Associate Professor Lilianne R. Mujica-Parodi.
The project, “Protecting the Aging Brain: Self-Organizing Networks and Multi-Scale Dynamics Under Energy Constraints,” is led by Lilianne R. Mujica-Parodi, Associate Professor of Biomedical Engineering at Stony Brook University School of Medicine. The work involves interdisciplinary research and collaboration between Stony Brook University and the Martinos Center for Biomedical Imaging at Harvard Medical School and Massachusetts General Hospital.

“This prestigious grant from the Keck Foundation supports innovative imaging research that will help transform the way scientists study the aging brain,” said Stony Brook University President Samuel L. Stanley Jr. “The funding also comes at a crucial time, as the aging of America will continue and the importance of dietary and other interventions to protect the aging brain are more vital than ever.”

Dr. Mujica-Parodi and co-investigators will integrate human neuroimaging data – from 7-Tesla fMRI and positron emission tomography – with multi-scale biomimetic modeling to test hypotheses with respect to how energy constraints based on diet and mitochondria affect neural efficiency in the aging brain.

“The collaborative work of Stony Brook faculty on the aging brain with scientists from other leading medical research institutions provides a strong basis for advancing this important area of 21st-century medicine,” said Kenneth Kaushansky, Senior Vice President for the Health Sciences and Dean of the School of Medicine. “Using extremely sophisticated imaging algorithms to trace neural pathways, coupled to metabolic interventions seen under stress, Dr. Mujica-Parodi will likely gain practical insights into methods to improve cognition in elderly individuals.”

The research builds on the pilot work of Mujica-Parodi and colleagues at Stony Brook University’s Laufer Center for Physical and Quantitative Biology and the Martinos Center for Biomedical Imaging. The team approaches brain network connectivity, assessed by fMRI and associated cognitive function, as a dynamic emergent phenomenon. They developed a metabolic-neuron hybrid model that can be used in the imaging research to identify and gauge energy input via glucose, glycogen and ketone kinetics.

“By using the imaging and biomimetic modeling techniques, we will investigate the use of exogenous ketones, a fuel source that is an alternative to glucose, as a way to ameliorate age-related effects,” explained Mujica-Parodi. “We hope our findings prove that personalized medicine for neurology is within our reach and that our methods can be a model toward that goal.”

The research team will use their approach to predict how neural networks self-organize in response to changes in energy supply and demand, and then compare those results to data on individuals to better understand the exact connection between nutrition to brain neurons and cognitive capacity.

NSF Funds Cross-Cutting CEAS Collaboration to Optimize Cloud Computing for Real-Life Applications

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

Risks to Stony Brook's Research Infrastructure from Proposed F&A Rate Reduction

Dear Faculty Colleagues,

I write today concerning a disturbing proposal that is being discussed in Washington that could have serious repercussions for the funding that we receive from federal agencies in support of research that is vital to the well-being of our citizens and our nation.

Recent discussions within the White House Office of Management and Budget (OMB) and the U.S. Department of Health and Human Services (HHS) have suggested that the federal science budget could be dramatically reduced by slashing facilities and administrative (F&A) cost reimbursements to universities. This proposal - which some in Congress may endorse - should concern all of us.

Federal research funding for universities includes two major components. First, grants or contracts awarded to universities (almost always through a competitive process) contain direct costs attributed to individual projects. These include items such as salary support, research staff and students, supplies, equipment, travel, and publication costs.

The other component of a grant or contract is the facilities and administrative cost rate (F&A or ‘indirect’ costs). These costs cannot be assigned to a single project because they include items such as laboratory space, heat, lights, IT infrastructure, animal care facilities, hazardous waste disposal, power, insurance, and the support staff required to manage grants and to ensure compliance with a myriad of federal and state regulations (human subjects protection, export controls, conflict of interest, etc). In negotiating these rates, Stony Brook, like other research universities, includes only those resources actually used to support research. Independent analyses have demonstrated repeatedly that the federal government only partially reimburses universities, including Stony Brook, for these expenses, many of which have been invested prior to the awarding of the grant. These are also costs that Stony Brook would not incur if we were not a research-intensive university.

I am well aware that faculty often question the F&A rate, how it is calculated, and who does the negotiation. Stony Brook’s current on-campus F&A rate is 59.5%, which falls close to the median rate of research institutions.  This rate is set through a comprehensive process guided by strict OMB rules, called Uniform Guidance 2 CFR 200. Our staff produce and file an extensive report in which they calculate our actual F&A expenditures based on prior years and apportioned to research, instruction, or other. Our actual rate is then negotiated with staff from the U.S. Department of Health and Human Services Division of Cost Allocation Services, and set based upon a comprehensive review and assessment of these costs. Compliance with the rate and OMB and agencies’ rules regarding these F&A reimbursements is then audited by the federal government every year under the terms established in the Single Audit Act. Importantly, many direct cost items are excluded from the base used to determine the final F&A reimbursement level (tuition, equipment, major renovations or repairs, and subcontract awards).

It is important to understand that Stony Brook is already subsidizing the actual F&A costs that federal research grants incur. This is due to two factors. The first is that since 1991, the federal government has imposed an administrative cap of 26% on the total F&A rate for administrative costs. At the same time, the cumulative number of regulatory changes relating to research with which universities must comply has dramatically increased. Ensuring compliance with these additional regulations—whether associated with human subject protections, animal care, export controls, effort reporting, conflict of interest, scientific fraud, and misconduct investigations—costs money and employment of additional administrative staff. The independent General Accounting Office (GAO) has estimated that research-intensive universities are already contributing about 25% of total dollars in support of faculty-led research projects.

Another question faculty often ask is why we accept funding from foundations that do not pay the federal F&A rate? There are several explanations. For some foundations, what would normally be considered an F&A expense may be charged as a direct cost since foundations are not required to use federal rules. In other instances, university funds are used to cover these costs. Finally, total research funding from private foundations amounts to a small percentage of our total research volume so the impact is less evident and often absorbed. Federal funds, however, account for more than 70% of our external funding. 

What is the risk to Stony Brook if the federal government drastically reduces F&A reimbursement for our research costs without any meaningful reduction in regulations and administrative compliance costs? Currently, our F&A reimbursement supports salaries for grants and contracts support staff, IRB and IACUC compliance specialists, IT specialists that support grant proposal submission and management, and technology transfer specialists, just to mention a few.  As a researcher, you are already aware that Stony Brook has undertaken a major assessment of administrative burdens that investigators shoulder during the conduct of research.  Initial findings call for investment in several of these key areas to better support faculty in obtaining and managing federal research funding. A significant reduction in F&A reimbursement to Stony Brook would not only preclude such investment, but would severely undermine existing research support services.  Negatively affected would be cost sharing, graduate student tuition subsidies, lab renovations, faculty start-up packages, benefits, and beyond. Almost every aspect of how our university supports research would be seriously impacted.

This is where all of us can help in protecting and sustaining the phenomenally successful 70 year university-federal government partnership for American science. While the Stony Brook leadership and our colleagues at other AAU institutions have been trying to educate all the relevant sectors about the importance of sustaining the partnership through robust funding of research and F&A reimbursement, we need the support of individual faculty researchers. It can be especially helpful for individual faculty members to understand the threat to Stony Brook’s research enterprise and to speak out to others to encourage their support.

With my best regards,
Richard J. Reeder
Vice President for Research

Write Winning Grant Proposals Workshop, September 5th

Please click on the below link to register for the workshop:


Computer Science PhD Alum Wins Best Dissertation Among Data Science Community 0

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.

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