![\"Cindy](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-cindy-gary-500w.jpg\")
<\/p>\n
CAREER awards boot camp<\/strong><\/h4>\nCindy Gary, assistant dean of grants and contracts for the Hajim School, hosts a summer NSF CAREER award \u201cboot camp\u201d to provide junior faculty with advice for submitting strong proposals.<\/p>\n
\n- How Gary sets junior faculty up for CAREER success >><\/a><\/strong><\/li>\n<\/ul>\n<\/div>\n
\n- Model how the brain extracts patterns from sensory data<\/li>\n
- Improve the ability of robots to respond to spoken commands<\/li>\n
- Explain how our brain stems help us listen and converse in noisy settings<\/li>\n
- Make it easier to operate large scale volunteer computing systems<\/li>\n
- Adapt novel imaging to pinpoint \u201chot spots\u201d on nanoscale devices<\/li>\n
- Model how the brain\u2019s entire waste removal system operates<\/li>\n<\/ul>\n
The researchers are Ralf Haefner<\/a>, assistant professor of brain and cognitive sciences; Thomas Howard<\/a>, associate professor of electrical and computer engineering; Ross Maddox<\/a>, associate professor of biomedical engineering and neuroscience; Sreepathi Pai<\/a>, assistant professor of computer science; and Andrea Pickel<\/a> and Jessica Shang<\/a>, assistant professors of mechanical engineering. The awards, NSF\u2019s most esteemed recognition for early-career faculty members, provide recipients with five years of funding to help lay the foundation for their future research.<\/p>\n
\nFinding patterns in large amounts of sensory data<\/strong><\/h3>\n![\"Ralf](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/Ralf-Haefner.jpg\")
Ralf Haefner (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\nFinding patterns in complex data is at the heart of forecasting in business and economics, analyzing data from large-scale experiments, and powering artificial intelligence (AI) and machine learning. The brain faces the same challenges in extracting patterns from the large amounts of data it receives from the senses.<\/p>\n
\u201cPerforming these computations exactly requires astronomical computational power and is impossible for both biological and AI systems,\u201d Haefner says. \u201cAs a result, both try to approximate exact solutions. However, approximations are sometimes wrong, and can be biased in specific ways.\u201d<\/p>\n
Haefner will construct mathematical models to investigate how the brain extracts patterns in the data it receives from photoreceptors in the eyes. His research will focus on two main aspects underlying this process: how the brain decides whether to combine two pieces of information, such as from two photoreceptors in the eyes or from two different senses; and the consequences of doing this over time and approximately, instead of instantaneously and exactly.<\/p>\n
In addition to better understanding aspects of the brain, Haefner\u2019s research will help in designing more efficient artificial intelligence systems.<\/p>\n
\n- Brain power >><\/a><\/li>\n<\/ul>\n
\nTeaching robots a sense of past and future<\/strong><\/h3>\n![\"Thomas](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-thomas-howard-500w-420x630.jpg\")
Thomas Howard (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\nHoward will develop algorithms that enable robots to respond to language that refers to the past, present, and future of their surroundings. Currently, for example, it is difficult for robots to understand instructions such as \u201cHand me the wrench I was using five minutes ago\u201d or \u201cPick up the cup that is about to roll off the table,\u201d and respond in a timely fashion. That\u2019s because the robot would need to think carefully about all the past and future states of its surroundings.<\/p>\n
Howard\u2019s research at Rochester has advanced the ability of robots to infer \u201cminimal but sufficient\u201d representations of their surroundings so that only the objects needed to understand statements are interpreted from sensor data. The project will \u201cmore tightly couple algorithms that interpret language and sensor data\u201d so humans can seamlessly use references to time and location when communicating back and forth with robots.<\/p>\n
\nHearing one voice among many<\/strong><\/h3>\n![\"Ross](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-ross-maddox-500w-384x630.jpg\")
Ross Maddox (photo provided)<\/figcaption><\/figure>\nAfter sound waves are converted into electrical signals in the ear, the signals are conveyed along an auditory brainstem to the brain\u2019s cortex, where auditory perception occurs. But scientists are still trying to understand exactly how this \u201cbeautiful, but complicated network of connections\u201d helps us focus our listening, says Maddox.<\/p>\n
For example, do the downward connections that extend from the cortex back along the auditory brainstem help us concentrate on one voice among many?<\/p>\n
To help answer questions like these, Maddox will use new methods to measure auditory brainstem responses in human subjects engaged in goal-oriented, lifelike tasks involving natural speech\u2014not the rapid bursts of clicks and other stimuli used in traditional testing.<\/p>\n
The results could help explain why even people with normal hearing sometimes struggle to understand conversations amid background noise.<\/p>\n
\nMaximizing disparate GPUs in volunteer computing systems<\/strong><\/h3>\n![\"Sreepathi](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-sreepathi-pai-500w-420x630.jpg\")
Sreepathi Pai (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\nPeople all over the world donate time on their computers to large-scale volunteer computing systems such as Einstein@Home<\/a> and Folding@Home<\/a>. They do so to help solve important scientific problems with volunteer systems that rival the largest supercomputers in the world.<\/p>\nHowever, these volunteer systems consist of hundreds of different kinds of graphics processing units (GPUs) to speed up scientific calculations. This heterogeneity hinders maximum performance.<\/p>\n
Pai will develop new automatic performance tuning algorithms to maximize the GPU performance in these systems.<\/p>\n
\u201cBy developing autotuning algorithms that can deal with the heterogeneity, providing feedback to programmers about unrealized performance, and working at scale in real volunteer computing systems, this project will enable these systems to maximize GPU performance and accelerate scientific discovery in fields such as medicine, biology, and astronomy,\u201d Pai says.<\/p>\n
\nPinpointing \u2018hot spots\u2019 that overheat electronic devices<\/strong><\/h3>\n![\"Andrea](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-Andrea-Pickel-500w-420x630.jpg\")
Andrea Pickel (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\nThe electronic devices that surround us in everyday life\u2014our computer hard drives and smartphones, for example\u2014operate at increasingly high levels of power that flow through smaller and smaller components. The devices can easily overheat, decreasing their performance, reliability, and longevity.<\/p>\n
Pinpointing the \u201chot spots\u201d that cause the overheating has proved elusive in this landscape where key features are measured in mere nanometers.<\/p>\n
Pickel is adapting, for the first time, a Nobel Prize\u2013winning optical \u201csuper-resolution\u201d imaging technique to generate accurate, high spatial resolution temperature maps from photons emitted by luminescent nanoparticle coatings placed on the surfaces of nanoscale devices.<\/p>\n
The technology could provide an invaluable tool to determine and address the primary causes of thermal failure in nanoscale devices.<\/p>\n
\nModeling the brain-cleansing interaction of blood flow and cerebrospinal fluids<\/strong><\/h3>\n![\"Jessica](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-Jessica-Shang-500w-420x630.jpg\")
Jessica Shang (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\nShang will create a computer model to better understand the mechanisms of fluid flow that \u201cdrive\u201d the brain\u2019s glymphatic waste disposal system.<\/p>\n
First discovered by Maiken Nedergaard, codirector of the University\u2019s Center for Translational Neuromedicine<\/a>, the glymphatic system uses the brain\u2019s cerebrospinal fluid to carry off metabolic wastes that have been linked to Alzheimer\u2019s and other neurodegenerative diseases. Recent research suggests that the flow of cerebrospinal fluid is linked to pulsing of blood through adjoining arteries.<\/p>\nHowever, experimental observations have been limited to the brain\u2019s outer surface.<\/p>\n
Shang is hoping that a computational model that can simulate the interaction of blood and cerebrospinal fluid flows throughout the brain \u201cwill advance our capabilities to correlate age-related ailments with neurodegeneration, predict patient outcomes, and drive treatment and prevention strategies.\u201d<\/p>\n
\nBroadening the impact<\/strong><\/h3>\nThe National Science Foundation requires CAREER award recipients to demonstrate how their research can have a broader educational impact. Several of this year\u2019s recipients plan to introduce STEM concepts related to their research to women and underrepresented minority students in the Rochester City School District.<\/p>\n
Howard, Pai, and Shang, for example, will work with Rochester City School District high school students participating in the Upward Bound program hosted by the University\u2019s Kearns Center for Leadership and Diversity<\/a>. Pickel\u2019s lab will build educational kits for students at a new, all-girls STEM elementary charter school in the district. Maddox will develop a short course for students at Rochester\u2019s East High School and from City College of New York through the NEUROEAST<\/a> and NEUROCITY<\/a> programs at the University\u2019s Medical Center.<\/p>\nHoward will also revamp the popular University robotics courses he teaches to integrate aspects of his CAREER research. The award provides $14,000 to purchase components for students to develop, build, and program 20 robot prototypes capable of navigation, mapping, estimation, and language interaction.<\/p>\n
Pai also hopes to explore ways to help Rochester\u2019s famed Strong National Museum of Play<\/a> preserve its collection of original electronic games\u2014including Pong, Space Invaders, Grand Theft Auto, Mario Brothers, Pac-Man, and other classics in its Word Video Game Hall of Fame<\/a>.<\/p>\nPickel will create an open-source hardware repository that provides access to the designs and building instructions for her lab\u2019s new thermal imaging technique, so other researchers can use it in their labs.<\/p>\n
Haefner will develop a curriculum for an interdisciplinary, college-level course for students in brain and cognitive sciences and computer science working on projects at the intersection of computational neuroscience and artificial intelligence.<\/p>\n![\"Professor](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-upward-bound-pai-robots-630x420.jpg\")
NSF CAREER award recipient Sreepathi Pai taught Kierra Dickson, an 11th-grade student from the Rochester City School District, and fellow Upward Students to program Turtle robots to make drawings. (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n
\n
- \n
- Model how the brain extracts patterns from sensory data<\/li>\n
- Improve the ability of robots to respond to spoken commands<\/li>\n
- Explain how our brain stems help us listen and converse in noisy settings<\/li>\n
- Make it easier to operate large scale volunteer computing systems<\/li>\n
- Adapt novel imaging to pinpoint \u201chot spots\u201d on nanoscale devices<\/li>\n
- Model how the brain\u2019s entire waste removal system operates<\/li>\n<\/ul>\n
The researchers are Ralf Haefner<\/a>, assistant professor of brain and cognitive sciences; Thomas Howard<\/a>, associate professor of electrical and computer engineering; Ross Maddox<\/a>, associate professor of biomedical engineering and neuroscience; Sreepathi Pai<\/a>, assistant professor of computer science; and Andrea Pickel<\/a> and Jessica Shang<\/a>, assistant professors of mechanical engineering. The awards, NSF\u2019s most esteemed recognition for early-career faculty members, provide recipients with five years of funding to help lay the foundation for their future research.<\/p>\n
\nFinding patterns in large amounts of sensory data<\/strong><\/h3>\n
Ralf Haefner (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n Finding patterns in complex data is at the heart of forecasting in business and economics, analyzing data from large-scale experiments, and powering artificial intelligence (AI) and machine learning. The brain faces the same challenges in extracting patterns from the large amounts of data it receives from the senses.<\/p>\n
\u201cPerforming these computations exactly requires astronomical computational power and is impossible for both biological and AI systems,\u201d Haefner says. \u201cAs a result, both try to approximate exact solutions. However, approximations are sometimes wrong, and can be biased in specific ways.\u201d<\/p>\n
Haefner will construct mathematical models to investigate how the brain extracts patterns in the data it receives from photoreceptors in the eyes. His research will focus on two main aspects underlying this process: how the brain decides whether to combine two pieces of information, such as from two photoreceptors in the eyes or from two different senses; and the consequences of doing this over time and approximately, instead of instantaneously and exactly.<\/p>\n
In addition to better understanding aspects of the brain, Haefner\u2019s research will help in designing more efficient artificial intelligence systems.<\/p>\n
- \n
- Brain power >><\/a><\/li>\n<\/ul>\n
\nTeaching robots a sense of past and future<\/strong><\/h3>\n
Thomas Howard (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n Howard will develop algorithms that enable robots to respond to language that refers to the past, present, and future of their surroundings. Currently, for example, it is difficult for robots to understand instructions such as \u201cHand me the wrench I was using five minutes ago\u201d or \u201cPick up the cup that is about to roll off the table,\u201d and respond in a timely fashion. That\u2019s because the robot would need to think carefully about all the past and future states of its surroundings.<\/p>\n
Howard\u2019s research at Rochester has advanced the ability of robots to infer \u201cminimal but sufficient\u201d representations of their surroundings so that only the objects needed to understand statements are interpreted from sensor data. The project will \u201cmore tightly couple algorithms that interpret language and sensor data\u201d so humans can seamlessly use references to time and location when communicating back and forth with robots.<\/p>\n
\nHearing one voice among many<\/strong><\/h3>\n
Ross Maddox (photo provided)<\/figcaption><\/figure>\n After sound waves are converted into electrical signals in the ear, the signals are conveyed along an auditory brainstem to the brain\u2019s cortex, where auditory perception occurs. But scientists are still trying to understand exactly how this \u201cbeautiful, but complicated network of connections\u201d helps us focus our listening, says Maddox.<\/p>\n
For example, do the downward connections that extend from the cortex back along the auditory brainstem help us concentrate on one voice among many?<\/p>\n
To help answer questions like these, Maddox will use new methods to measure auditory brainstem responses in human subjects engaged in goal-oriented, lifelike tasks involving natural speech\u2014not the rapid bursts of clicks and other stimuli used in traditional testing.<\/p>\n
The results could help explain why even people with normal hearing sometimes struggle to understand conversations amid background noise.<\/p>\n
\nMaximizing disparate GPUs in volunteer computing systems<\/strong><\/h3>\n
Sreepathi Pai (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n People all over the world donate time on their computers to large-scale volunteer computing systems such as Einstein@Home<\/a> and Folding@Home<\/a>. They do so to help solve important scientific problems with volunteer systems that rival the largest supercomputers in the world.<\/p>\n
However, these volunteer systems consist of hundreds of different kinds of graphics processing units (GPUs) to speed up scientific calculations. This heterogeneity hinders maximum performance.<\/p>\n
Pai will develop new automatic performance tuning algorithms to maximize the GPU performance in these systems.<\/p>\n
\u201cBy developing autotuning algorithms that can deal with the heterogeneity, providing feedback to programmers about unrealized performance, and working at scale in real volunteer computing systems, this project will enable these systems to maximize GPU performance and accelerate scientific discovery in fields such as medicine, biology, and astronomy,\u201d Pai says.<\/p>\n
\nPinpointing \u2018hot spots\u2019 that overheat electronic devices<\/strong><\/h3>\n
Andrea Pickel (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n The electronic devices that surround us in everyday life\u2014our computer hard drives and smartphones, for example\u2014operate at increasingly high levels of power that flow through smaller and smaller components. The devices can easily overheat, decreasing their performance, reliability, and longevity.<\/p>\n
Pinpointing the \u201chot spots\u201d that cause the overheating has proved elusive in this landscape where key features are measured in mere nanometers.<\/p>\n
Pickel is adapting, for the first time, a Nobel Prize\u2013winning optical \u201csuper-resolution\u201d imaging technique to generate accurate, high spatial resolution temperature maps from photons emitted by luminescent nanoparticle coatings placed on the surfaces of nanoscale devices.<\/p>\n
The technology could provide an invaluable tool to determine and address the primary causes of thermal failure in nanoscale devices.<\/p>\n
\nModeling the brain-cleansing interaction of blood flow and cerebrospinal fluids<\/strong><\/h3>\n
Jessica Shang (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n Shang will create a computer model to better understand the mechanisms of fluid flow that \u201cdrive\u201d the brain\u2019s glymphatic waste disposal system.<\/p>\n
First discovered by Maiken Nedergaard, codirector of the University\u2019s Center for Translational Neuromedicine<\/a>, the glymphatic system uses the brain\u2019s cerebrospinal fluid to carry off metabolic wastes that have been linked to Alzheimer\u2019s and other neurodegenerative diseases. Recent research suggests that the flow of cerebrospinal fluid is linked to pulsing of blood through adjoining arteries.<\/p>\n
However, experimental observations have been limited to the brain\u2019s outer surface.<\/p>\n
Shang is hoping that a computational model that can simulate the interaction of blood and cerebrospinal fluid flows throughout the brain \u201cwill advance our capabilities to correlate age-related ailments with neurodegeneration, predict patient outcomes, and drive treatment and prevention strategies.\u201d<\/p>\n
\nBroadening the impact<\/strong><\/h3>\n
The National Science Foundation requires CAREER award recipients to demonstrate how their research can have a broader educational impact. Several of this year\u2019s recipients plan to introduce STEM concepts related to their research to women and underrepresented minority students in the Rochester City School District.<\/p>\n
Howard, Pai, and Shang, for example, will work with Rochester City School District high school students participating in the Upward Bound program hosted by the University\u2019s Kearns Center for Leadership and Diversity<\/a>. Pickel\u2019s lab will build educational kits for students at a new, all-girls STEM elementary charter school in the district. Maddox will develop a short course for students at Rochester\u2019s East High School and from City College of New York through the NEUROEAST<\/a> and NEUROCITY<\/a> programs at the University\u2019s Medical Center.<\/p>\n
Howard will also revamp the popular University robotics courses he teaches to integrate aspects of his CAREER research. The award provides $14,000 to purchase components for students to develop, build, and program 20 robot prototypes capable of navigation, mapping, estimation, and language interaction.<\/p>\n
Pai also hopes to explore ways to help Rochester\u2019s famed Strong National Museum of Play<\/a> preserve its collection of original electronic games\u2014including Pong, Space Invaders, Grand Theft Auto, Mario Brothers, Pac-Man, and other classics in its Word Video Game Hall of Fame<\/a>.<\/p>\n
Pickel will create an open-source hardware repository that provides access to the designs and building instructions for her lab\u2019s new thermal imaging technique, so other researchers can use it in their labs.<\/p>\n
Haefner will develop a curriculum for an interdisciplinary, college-level course for students in brain and cognitive sciences and computer science working on projects at the intersection of computational neuroscience and artificial intelligence.<\/p>\n
NSF CAREER award recipient Sreepathi Pai taught Kierra Dickson, an 11th-grade student from the Rochester City School District, and fellow Upward Students to program Turtle robots to make drawings. (University of Rochester photo \/ J. Adam Fenster)<\/figcaption><\/figure>\n
\n
- Brain power >><\/a><\/li>\n<\/ul>\n
![\"Wendi](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/08\/inline-wendi-heinzelman-cindy-gary-630x566.jpg\")
![\"illustration](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2019\/01\/fea-high-blood-pressure-alzheimers.jpg\")
Study suggests how high blood pressure might contribute to Alzheimer\u2019s<\/strong><\/a><\/p>\n![\"High](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2021\/06\/fea-neuro-east-pipeline-program.jpg\")
Pipeline program lets East High students experience life in the lab<\/strong><\/a><\/p>\n![\"Two](\"https:\/\/www.rochester.edu\/newscenter\/wp-content\/uploads\/2022\/01\/fea-nitrogen-vacancy-centers-atomic-force-microscope.jpg\")
Using nanodiamonds as sensors just got easier<\/strong><\/a><\/p>\n