About ACM/CSTA Cutler-Bell Prize in High School Computing

ACM and the Computer Science Teachers Association (CSTA) selected four high school students from among a pool of graduating high school seniors throughout the US for the ACM/CSTA Cutler-Bell Prize in High School Computing. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy, and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is Researcher Emeritus at Microsoft Research.

Each Cutler-Bell Prize winner receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s 2024 Annual Conference, July 16-19, in Las Vegas.

The winning projects illustrate the diverse applications the next generation of computer scientists is developing.

Shobhit Agarwal, Reedy High School, Frisco, Texas

Every three years, Shobhit Agarwal visits his grandparents in Jhansi, India, a town with the poorest healthcare infrastructure in northern India—where 85% of the population does not attend yearly checkups. After seeing a mental decline in his grandfather, Agarwal immersed himself in his grandparents’ hometown, interviewing local citizens and doctors. He was driven to create a low-cost system that recognizes a variety of diseases while simultaneously forecasting the progress of the disease. This system is OmniDoc, a framework that accurately predicts diagnoses, prognoses, and treatments given a patient profile. This system is currently deployed in Jhansi in two ways. First, hospital volunteers at the Naja Hospital conducted door-to-door visits to collect patient information. This data is inputted into Agarwal’s framework, and if the algorithm detects a disease, a patient books a free appointment with a local physician; the model data is subsequently forwarded to the doctor. Five hundred homes were visited, and nearly 40% of those patients were sent to clinics based on algorithm-identified risk. Hospital statistics show that 95% of the patients who arrived in the clinic due to the campaign had the algorithm’s diagnosis subsequently confirmed by a physician, indicating that the model accurately identified patient condition with minimal data. This success led to the deployment of OmniDoc at the Jhansi Orthopedic Hospital for their 15-person radiology department.

Franziska Borneff, Hidden Valley High School, Cave Spring, Virginia

During her junior year, Franziska Borneff became interested in monitoring the flow rates of Arctic rivers. Using her newly developed coding skills, she began to plot and trend analysis for climate research. Her own research aligned with the news articles about climate change, and this influenced her to continue to study these data trends. The Arctic rivers are important in the process of detecting climate change, as they directly influence ecosystems and the livelihoods of humans. Borneff researched the relationship between atmosphere and waterways, concluding that air temperature, river discharge, and sea ice concentration are the most significant data points. Her research creates a method to track critical dates related to the spring thaw of Arctic rivers and assess their impact on local populations. She collected daily temperature, river discharge, and sea ice cover data from publicly available sources for the six major Arctic rivers, finding the thaw date is earlier than ever. Borneff then connected with the students of the Yupik Eskimo Village in Marshall, Alaska, to see how the earlier thaw impacted the local community. Through this meeting, she read stories about how the familiar rhythms of nature have been disrupted and the uncertain future of the Yupik people as a result of these shifts. Borneff hopes her research will spark studies in sensitive Arctic regions and enlighten politicians to initiate government action that is informed by scientific understanding. The collaboration between quantitative data documenting warming and human narratives testifying to the accuracy of the data is essential.

Daniel Mathew, Poolesville High School, Poolesville, Maryland

Daniel Mathew’s project, MiniMesh, danced between invention and improvement. Starting out on his bedside desk, Mathew dumped out scrap electronic parts and assembled a device named PreVis to track the location of a single point on a human for movement analysis with a LiDAR mounted on a controllable servo. PreVis went everywhere, from discussing him in Congress to presenting him at research conferences. PreVis was Mathew’s first step toward human-computer interaction. PreVis then evolved into MiniProse, a free mobile application. Mathew studied the mathematics of current pose estimation solutions and then developed the core algorithm for MiniProse. The final algorithm, MiniMesh, scrapped the original two prototypes and was built from the ground up. Mathew developed a new framework. Mathematically proving optimization identities and writing machine learning algorithms, MiniMesh could reconstruct the entire human mesh with thousands of points. Mathew took this algorithm to companies for skin cancer research and military organizations for augmented-reality surgery. By predicting the location of thousands of points on the human body on portable devices, all in real-time, MiniMesh has applications in several fields. In the original biomechanical use case, MiniMesh could be used for at-home gait analysis by tracking joint locations and improving sports techniques by analyzing the metabolic cost of human movements. For assistive surgery, MiniMesh accurately and efficiently maps the human topology to aid surgeons. For animation, MiniMesh replicates expensive VFX, enabling amateur animators at no cost.

Kosha Upadhyay, Bellevue High School, Bellevue, Washington

Kosha Upadhyay watched her neighbor of eight years struggle with dementia. Following his passing, she wanted to understand the struggle of people with dementia and began volunteering at a dementia care center. Upadhyay knew she couldn’t give these patients back what they lost but wanted to preserve what they had left. This inspired her to work on creating a better therapy for those suffering from dementia. This therapy, MemSpark, is an automated end-to-end system that creates a novel brain-training therapy using virtual reality and tracks dementia progression through artificial intelligence. Upadhyay studied brain morphology and neurodegeneration to create a therapy that affected dementia at its root cause. Since decline can affect any part of the brain, she designed a novel set of games that exercised all parts of the brain. Eight serious games were designed to exercise all cognitive functions by considering a set of promotive factors (immersion, confidence, focus) and preventive factors (anxiety, frustration, self-pity). Each serious game produced a set of two features—accuracy and time which were then inputted into an AI model for profiling. The data generated by the Virtual Reality (VR) system was pre-processed and passed into an AI model. After studying multiple AI models, Upadhyay chose a multi-layer perceptron neural network due to its suitability for the mode of data, along with its high accuracy and regression adaptability. The neural network produced cognitive profiling scores across three categories: recall, reasoning, and executive function. The profiles were aligned to the ADAS-Cog test–an industry standard test for evaluating dementia. Upadhyay tested her therapy across 14 people split into experimental and control groups. Her solution was able to slow down dementia progression by 65%—which surpasses current mainstream therapies and presents the potential to enhance the way we approach dementia care.

ACM and the Computer Science Teachers Association (CSTA) selected four high school students from among a pool of graduating high school seniors throughout the US for the ACM/CSTA Cutler-Bell Prize in High School Computing. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy, and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed.

These projects illustrate the diverse applications being developed by the next generation of computer scientists.

Okezue Bell, Moravian Academy, Bethlehem, Pennsylvania

With only 1% of the computer science space being Black, the innovation landscape within the field is reflective of that. There are few race- and class-responsible solutions built effectively for communities that have been historically discriminated against. “Fidutam” is a novel, putative first effort to foster a needs-responsive approach to providing financial accounts for unbanked populations. Bell uses state-of-the-art encryption to ensure the safety of user’s data, creating private signatures using a selfie, name and personal data, and location. The solution focuses on financial documentation, which is proven to be the biggest barrier to entry for the unbanked, Bell created Fidutam not only to provide financial access to unbanked individuals but to develop a platform to enable the upward mobilization of the global poor to revive their community’s economy. This increases their share in the global development landscape of computer science and also encourages and enables those whose voices are often underrepresented in CS to penetrate or quality control the field to ensure the existing products have utility in their milieus.

Nathan Elias, Liberal Arts and Sciences Academy, Austin, Texas

In his project, “A Novel Method for Automated Identification and Prediction of Invasive Species Using Deep Learning,” Elias developed InvasiveAI, a service that helps farmers, agricultural workers, and average citizens in the fight against invasive species. He designed an app that utilizes Artificial Intelligence and machine learning methods to accurately detect, predict, and visualize invasive species growth. Using the app, 200 unique invasive plants, wildlife, insects, and pathogens, can be identified. Elias also created a 3D image detection algorithm to identify over 75 invasive species aerially. Elias envisions that InvasiveAI will contribute to the field of computer science by expanding CS’ reach in environmental and citizen science systems, while also furthering advancements in geospatial and AI-based tracking toolkits. This project was inspired by the loss of Elias’ grandfather’s farm in Southern India to the invasive species Kariba.

Hannah Guan, BASIS San Antonio Shavano, San Antonio, Texas

Guan’s project, “Multi-Dimensional Interpretable Interaction Network (MDiiN) for Modeling Aging Heath and Mortality” was inspired by the retired military population of the city of San Antonio. She wanted to create an efficient and affordable system that would be able to diagnose and find remedies for highly pervasive age-related diseases like cancer or Alzheimer’s. Guan’s research can influence elders’ quality and equity of life worldwide. MDiiN is a computation and affordable predictive model that evaluates health risk factors for elders. It’s the first three-dimensional interaction network to uncover high-dimensional interactions among health variables during the aging process. Doctors can use MDiiN to predict the onset of age-related diseases, which would significantly increase the quality and longevity of life across the grid. It’s fast and easy to run, taking less than a second to get results. This research contributes to computer science by strengthening health equality in our society, improving global health security, and leading to tremendous public health benefits.

Sirihaasa Nallamothu, University High School, Normal, Illinois

In her project, Predicting and Identifying Relevant Features of Vasovagal Syncope in Patients with Postural Orthostatic Tachycardia Syndrome (POTS) using machine learning methods and physiological data, was inspired from a TikTok that led Nallamothu down a rabbit hole about POTS. To her surprise, there were no research studies or consumer solutions to predict syncope on real-world data, and she was determined to use her machine learning skills to predict syncopal episodes. Nallamothu is the first person to conduct an IRB research study and collect human subject field data on POTS patients in the real world using non-invasive technologies. She wrote a Python script to extract the 15-minute window signal data of heart rate, blood volumetric pressure, EDA, temperature, and accelerometer data. Nallamothu also uses the concept called “late fusion” in temporal multimodal machine learning. This research is providing a starting point for future research into real-time prediction and integration into a smartwatch, which will help millions who experience vasovagal syncope research a safe and comfortable position before fainting. After completing her research, Nallamothu plans to work toward creating a consumer product and pairing her algorithm with a smart watch.-->{C}

ACM and the Computer Science Teachers Association (CSTA) selected four high school students from among a pool of graduating high school seniors throughout the US for the ACM/CSTA Cutler-Bell Prize in High School Computing. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy, and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Harshal Bharatia, Plano Senior High School, Plano, Texas
In his project, Thermocloud: A Smart Collaborative Thermostat, Harshal Bharatia used agile methodology and an interactive design and development cycle. The purpose of this project is to design and construction of a cloud-based collaborative learning thermostat that optimizes the operation of HVAC systems by learning to collaborate and use the best machine learning approach to maximize comfort and energy savings for each system. Using a collaborative cloud-based learning approach across many houses, it learns to adapt the operation of an HVAC system by identifying the best currently-available machine learning approach and uses this approach to maximize comfort and energy savings. With cost-effective hardware, it enables collaboration with other similar thermostats and controls the HVAC system in a reliable fashion. It also supports additional energy-saving features such as multi-story equalizer, blackout mitigation, and user-driven cost versus comfort trade-off. This approach was truly innovative as it was domain agnostic and allowed a very large number of clients to lazily update the route-mapping and the system automatically addressed degradation as a result feedback triggered automatic cluster refinement, model retraining, and strategy selection to improve performance. With more than 34% energy savings, Bharatia patented the novel Thermocloud approach and released it in public-domain at intellicusp.org/thermocloud, as by enabling people to freely save energy, Bharatia hopes the fight against climate change leads to a better tomorrow.

Yash Narayan, The Nueva School, San Mateo, California
Yash Narayan developed DeepWaste. This easy-to-use mobile application utilizes highly-optimized deep learning techniques to classify waste better than humans. A user using DeepWaste can simply point their phone camera to any piece of waste (food, bottle, paper, etc.) and get instantaneous feedback on whether the item is recyclable, compostable, or trash. Narayan was inspired to create DeepWaste after seeing the large volumes of misclassified waste at his local recycling center several years ago. Indeed, DeepWaste solves a critical problem, as inaccurate waste disposal, at the point of disposal is a significant contributor to climate change. When materials that could be recycled or composted are diverted into landfills, they cause the emission of potent greenhouse gases. His project demonstrates the efficacy of an accurate, easy-to-use, scalable solution to augment human performance in waste disposal, accessible right at the point of disposal–an innovative approach applying AI to a large-scale global problem. If DeepWaste improves human waste-disposal accuracy by even 1%, it would be equivalent to removing over 6.5 million gasoline-burning passenger vehicles from the road.

Shoumik Roychowdhury, Westwood High School, Austin, Texas
Shoumik Roychowdhury’s project, XNet: A Novel Machine Learning Model for Fast MRI Reconstruction, took inspiration from his own experience with MRIs. This project's vision is to create an effective and computationally inexpensive Deep Learning (DL) pipeline that can aid medical professionals in capturing MR images faster. The proposed work is a novel generative adversarial network architecture that uses two similar MR images which have been reconstructed from 0.1%, 2%, or 5% sub-sampled k-spaces, as inputs to produce a complete MR image with a peak signal-to-noise ratio (PSNR) equal or higher than full-space reconstructed MR images. This architecture is dubbed X-Net due to the model's shape looking like the letter 'X.' By treating the reconstructed sub-sampled MR images as matrices, X-Net's generator network can convolutionally auto encode information from two different reconstructed sub-sampled MR images, cross-pollinate features and attributes, convolutionally auto decode the new information, and magnify residual information to create an enhanced image. This resultant image is then sent to the pre-trained discriminator network, which determines whether it is real or fake. Next, the loss functions are automatically updated, and consequently, the generator's hyperparameters are automatically tuned. This process is repeated for 10,000 iterations until the model is finally trained. This tuned model is now ready for deployment in the real world, aiding medical professionals in providing fast and sharp MR reconstruction. In the future, Roychowdhury plans to successfully deploy and implement this solution across the healthcare industry, implementing this work in two key manners.

Hiya Shah, Amador Valley High School, Pleasanton, California
The main vision of Hiya Shah’s project, titled “Maji: Water Security,” is a mobile application that determines the real-time water quality of your home’s water pipes by using innovative machine learning and building a large database of water quality data to achieve our goal of decreasing water health consequences. Another vision of Maji is to computationally design an environmentally sustainable (lower energy costs and lower water wastage) forever chemical (PFAS) filtration membrane that can relay data to the mobile application in real-time. To scale Maji beyond her city, Shah is am currently working with the U.S. Environmental Protection Agency (as part of the U.S. President’s Environmental Youth Award) to implement it on the IOS App store for residents across the United States to use. In the immediate future, she seeks to develop the application for the Google Play Store and reach unincorporated areas and the global market by proposing the app to private water suppliers and local government officials for implementation.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “We hope that, whatever careers these students ultimately pursue, they will consider how technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

"In today's world, computer science is rapidly becoming an essential aptitude for students at all levels and in every area of study," explains ACM President Gabriele Kotsis. "In the coming years, students who have exposure to computer science education in K-12 settings will be at a decided advantage when they enter university or begin their careers. ACM is proud to be a partner with the CSTA in bestowing the Cutler-Bell Prize. Cutler-Bell Prize-winning students are exemplars for their peers. These students demonstrate that they have the vision to use computing as a tool to address pressing problems in society, as well as the technical aptitude to develop a practical plan outlining how they would make their vision a reality. We also congratulate the computer science teachers who guided these students and Cutler and Bell for funding this award."

"Each year, these winning projects showcase the continuing advancements of computer science and the power of high-quality computer science education,” said Jake Baskin, Executive Director of CSTA. “These students and their projects embody CSforGood, and it’s inspiring to see how they are leveraging their computer science skills to solve pressing problems. CSTA is proud to honor their work and thanks Gordon Bell and David Cutler for their continued support of the award.”

ACM and the Computer Science Teachers Association (CSTA) selected four high school students from among a pool of graduating high school seniors throughout the US for the ACM/CSTA Cutler-Bell Prize in High School Computing. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy, and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Sahithi Ankireddy, James B. Conant High School, Hoffman Estates, Illinois
“BEEP... BEEP...BEEP! The jarring noise was accompanied by the neon green waves bouncing up and down every few seconds. Fixated on the heart monitor, I followed the pattern, hoping the 'beep' would continue in order to indicate the survival of the patient—my father.”

Sahithi Ankireddy used the experience of her father’s heart attack to identify ways to detect heart disease faster and easier in those who aren’t deemed “at risk.” Recalling an article she read about the use of artificial intelligence in speeding up the process of diagnosis. In her project, Assistive Heart Disease Diagnostic Tool using Machine Learning and Deep Neural Networks, Ankireddy tested both machine learning models and deep neural networks using a publicly available heart disease database. Through her testing, Ankireddy recognized the Random Forest ML model was the best method for her project. Ankireddy sees her research and assistive heart disease diagnostic tool as helpful in resource-constrained environments. By using this tool, doctors can evaluate more people in less time and provide treatment to patients more quickly. Ankireddy is currently in the process of working with cardiologists to receive feedback on this tool.

Maurice Korish, Rae Kushner Yeshiva High School, Livingston, New Jersey
The United States Census Bureau cites that 9.4 million noninstitutionalized adults have difficulty with at least one daily activity—including eating. While technology exists to support these individuals, it often requires the person using the technology to remain in the same position during the feeding process. Maurice Korish has developed FeedBot to provide independence and a cost-effective solution for disabled people who are unable to properly use their upper limbs. FeedBot implements facial recognition technology to identify the location of an individual’s mouth. This information is then transmitted to a robotic feeding arm, which is also able to be controlled manually with a joystick. Korish has taken advantage of and is building upon open source libraries, and uses Raspberry Pi, to keep this solution low cost. The use of Raspberry Pi also allows for more mobility than a standard computer, providing more comfort and flexibility for the person using FeedBot.

Brian Minnick, Loudoun Valley High School, Purcellville, Virginia
In his project, Controlling a Fully 3D Printed 3D Printer Without Microprocessors, Brian Minnick looks to allow the printer to function without conventional parts. Minnick has created the first fully 3D printed 3D printer to demonstrate self-manufacture, and along with universality, or the ability to make many useful parts, not just duplicates of itself, marks the half-way point in the development of the technologies behind the self-replicating spacecraft. It also contains the first motor controller for a 3D printer that can be built without a microprocessor. Minnick has created this printer as a stepping-stone toward a self-replicating spacecraft.

Emily Yuan, Thomas S. Wootton High School, Rockville, Maryland
In the United States, more than half of violent crimes are not reported. And while most victims of violent crimes seek out medical treatment, the current system they use to report details provides general, unmappable data. Others choose not to share data because of fear. To address these issues, Emily Yuan created Spatial Drilldown, a visual interactive mapping system where users click down on parcels on a map to report incident locations. The goal of this application was to ensure the preservation of privacy. Yuan worked with the CDC research team and nurses from Atlanta Grady Memorial Hospital to test this prototype. Spatial Drilldown provides a novel, interactive technique for collecting crime data, specifically that which can be mapped, and thus, improving the quality of current violence data. Yuan hopes to integrate the application into electronic medical records systems for real use and expand the crime data to help reduce local violence.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “We hope that, whatever careers these students ultimately pursue, they will consider how technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

"In today's world, computer science is rapidly becoming an essential aptitude for students at all levels and in every area of study," explains ACM President Gabriele Kotsis. "In the coming years, students who have exposure to computer science education in K-12 settings will be at a decided advantage when they enter university or begin their careers. ACM is proud to be a partner with the CSTA in bestowing the Cutler-Bell Prize. Cutler-Bell Prize-winning students are exemplars for their peers. These students demonstrate that they have the vision to use computing as a tool to address pressing problems in society, as well as the technical aptitude to develop a practical plan outlining how they would make their vision a reality. We also congratulate the computer science teachers who guided these students and Cutler and Bell for funding this award."

"Each year, these winning projects showcase the continuing advancements of computer science and the power of high-quality computer science education,” said Jake Baskin, Executive Director of CSTA. “These students and their projects embody CSforGood and it’s inspiring to see how they are leveraging their computer science skills to solve pressing problems. CSTA is proud to honor their work and thanks Gordon Bell and David Cutler for their continued support of the award.”

The recipients of the 2019-2020 Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Four high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Kevin Meng, Plano West Senior High School, Plano, Texas
Two years ago, Kevin Meng’s grandmother suffered from a slip-and-fall injury that resulted in skull fracture. This accident, which was suffered out of the view of cameras, got Meng thinking: what if we could see through walls? In his project, Meng uses VisionRF, a deep neural network model that accepts raw radio frequency signals and outputs continuous video of 15-point human skeletons behind obstruction. Because radio camera data on its own is harder to analyze, analysis through Raspberry Pi-based programming supports mobile, real-time inference. This results in accurate and complete predictions of the human skeletons. The implications of this project are broad and can be used to support military operations, monitor the health of patients non-invasively and aid first responders in search and rescue missions.

Lillian Kay Petersen, Los Alamos High School, Los Alamos, New Mexico
Lillian Kay Petersen’s younger, adopted siblings faced food insecurity in their previous homes. Inspired by their experiences and the news of crop failures in Ethiopia, she became determined to help aid organizations in increasing food security in developing countries. To accomplish this, Petersen developed a tool to inform cost-effective nutrition interventions in sub-Saharan Africa, inclusive of predicting grain harvests, predicting acute malnutrition prevalence and optimizing the supply logistics of specialized nutritious foods. The tools can be adjusted to include-real time data, enabling aid organizations to adjust distributions accordingly. As the result of her work, Petersen was invited to speak at eleven aid and research organizations, including USAID, the USDA and the International Food Policy Research Institute. She was also an invited speaker at multiple conferences, including the 2018 and 2019 CGIAR Big Data in Agriculture Conventions in Kenya and India.

Axel S. Toro Vega, Dr. Carlos González High School, Aguada, Puerto Rico
While identifying topics for his research project, Axel Toro Vega read that more than 36 million people in the world are visually impaired and more than 217 million have some type of severe visual impairment. As a result, he decided to focus his research on developing a device to assist the visually impaired in having a healthier, safer, and more enjoyable lifestyle. Toro Vega created an initial prototype consisting of an ultrasonic sensor mounted onto a pair of glasses. He continued to test different sensor arrangements and tweaked the software for a simple and efficient user experience. After gathering additional feedback after a presentation at the Intel International Science and Engineering Fair, Toro Vega took his prototype further by integrating artificial intelligence. This project made Toro Vega realize the great accomplishments that can be reached through computer science and the core meaning of CS for Good.

Zeyu Zhao, Montgomery Blair High School, Silver Spring, Maryland
Inspired by his grandfather who is facing chronic kidney disease, Zeyu Zhao began researching the kidney exchange system in the U.S. and was shocked to learn that 3,000 kidneys are wasted each year and 13 people die daily, in part, due to failed matches. Zhao wanted to use computer science—specifically machine learning—to improve the current kidney exchange system. He created a data-driven approach to solving the kidney matching problem through the designation of a Graph Neural Network to guide a Monte Carlo Tree Search. Zhao identified baselines for his project and tested his algorithms against this baseline, thus improving the current kidney exchange by developing a data-driven approach to finding matches. The research from Zhao’s project could be extended to other applications, such as operations research.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “ We hope that, whatever careers these students ultimately pursue, they will consider the ways in which technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

“ACM has been a leader in integrating computer science into the K-12 curriculum for several decades and our participation in the annual Cutler-Bell Prize is an extension of our commitment in this area,” said ACM President Cherri M. Pancake. “It is always intriguing to learn about the Cutler-Bell Prize-winning projects, which reflect the students' creativity and ingenuity as well as what they have learned in the classroom. These projects embody what we call "computational thinking"—a unique way of approaching problem-solving inspired by the computing revolution. We are grateful for Gordon Bell and David Cutler's financial support of the prize, and we congratulate the students and their teachers for developing these inspiring projects.”

“This year’s winning projects are outstanding examples of the power of a high quality, K-12 computer science education," said Jake Baskin, Executive Director of CSTA. "These students' creativity and commitment to using their knowledge and skills to improve the world are inspiring and I cannot wait to see what they do next. CSTA is proud to honor their work and thanks Gordon Bell and David Cutler for their continued support of the award."

The recipients of the 2018-2019 Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Four high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s annual conference, July 7-10, 2019 in Phoenix, Arizona.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Naveen Durvasula, Montgomery Blair High School, Silver Spring, Maryland
Naveen Durvasula developed a principled method to predict, for a given patient-donor pair, the expected quality and waiting time of the transplant they would receive through kidney exchange. To accomplish this, Durvasula developed a realistic simulator to model the kidney-exchange process using data extracted from a private database. By simulating a given patient-donor pair in the pool many times and recording the quality and waiting time for the transplant, there can be an approximation of the probability distribution over these quantities. Realizing this method was not scalable, Durvasula created a prediction model to interpolate the output of the simulator. After testing the method, it was found it provides clinically acceptable estimates and outperforms all standard applications from the Sci-Kit learn pipeline.

Isha Puri, Horace Greeley High School, Chappaqua, New York
Isha Puri’s project focuses on the development of a system to detect the direction and frequency of gaze fixation to test for and diagnose dyslexia. Realizing that the analysis could be performed on eye movement patterns directly, Puri developed six main steps to the process: take a video of a child reading a standard passage using a webcam, separate the video into frames, isolate right and left eyes from the image, develop a highly accurate eye tracker that uses a webcam, extract fixation frequency and duration features to predict dyslexia and test on real patients. Puri’s software automatically extracts the duration and frequency of reader fixations in a webcam stream with a combination of machine learning methods and then builds a data-driven prediction model to predict a high-risk of dyslexia. This implementation provides a highly accurate and freely available eye tracking methodology for diagnosing a variety of medical conditions.

Eshika Saxena, Interlake High School, Bellevue, Washington
Eshika Saxena set out to explore the possibility of designing a portable and affordable microscope attachment for a smartphone that can capture images of blood cells from a peripheral blood smear and develop software that can enhance and analyze these images automatically and screen for disease without manual intervention. Saxena focused on screening for sickle cell disease, which is prominent in resource-constrained regions where an inexpensive screening solution is needed. This resulted in the successful development of the “HemaCam,” a hematological disease screening framework that makes complex disease screening as simple as taking a picture. HemaCam is comprised of a clip-on, 3D printed attachment that turns a smartphone camera into a microscope capable of capturing blood cell images. These images are analyzed by Saxena’s deep learning software to identify abnormalities and diagnose diseases instantly. The software learns from examples and is fully trained to recognize sickle disease with 95.63% accuracy. The framework makes in-home hematological disease screening viable and extends healthcare across borders. Saxena is in discussion with the “Sickle Odisha” organization in the sickle belt in India, to organize large scale field testing for HemaCam to accelerate disease screening.

Varun Shenoy, Cupertino High School, Cupertino, California
Varun Shenoy’s vision is to develop an effective method to diagnose the onset of wound complications during surgical operations using computer science. The design process was split into three phases: conducting a comprehensive literature survey, developing the algorithms and mobile application, and documenting the results of the research. During phase one, Shenoy defined the project statement and worked with Dr. Oliver Aalami to collect mages for the project's dataset. Next, Shenoy developed the computational model and mobile application, concluding that artificial neural networks would be the optimum classifier, and developed an application for a patient to interact with computational models. Shenoy concluded this project by writing a research report documenting the approach and experimental results in a presentation and poster format, showcasing the impact to not only the patient but the doctor, hospital and insurers. This research has the capability to positively impact postsurgical wound care in our society by leveraging the power of computer science.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “ We hope that, whatever careers these students ultimately pursue, they will consider the ways in which technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

“The Cutler-Bell Prize challenges high school students to not only stretch their imaginations but also to lay out the practical steps for how a computational approach could solve a pressing problem in society or business," said ACM President Cherri M. Pancake. "These are the kinds of skills students will increasingly need in our digital age. In short, the Cutler-Bell Prize encourages students to see the possibilities, as well as the excitement, that computing offers. ACM thanks Gordon Bell and David Cutler for sponsoring the award, as well as the growing number of students and teachers who participate each year.”

“The high caliber submissions we received this year are outstanding examples of the new ideas that are generated thanks to the increase in K–12 students learning computer science,” said Jake Baskin, Executive Director of CSTA. “Our recipients have created projects that have applicable real-world solutions, all resulting from the high-quality computer science education they have received.”

The recipients of the 2017-2018 Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Five high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s annual conference, July 7-10, 2018 in Omaha, Nebraska.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Sreya Guha, Castilleja School, Palo Alto, California
Sreya Guha’s “Related Fact Checks” service was built to combat fake news by connecting information written in articles to the related fact(s) on fact checking websites. The tool does not label articles as either fact or fiction, since many articles contain both; but instead, it provides relevant fact checks related to an article being read. A browser extension allows the service to be accessible to a wide audience with the hopes of slowing the tide of fake news. Facing the challenge of the abundance of fake news, Guha realized through her research that most fake news stories tend to stick to a small number of themes (anti-vaccine, anti-climate change etc.). Even in the absence of a fact check for a particular claim, giving the reader a fact check within the same theme can help them critically understand the story they are reading.

Amir Helmy, Eastside High School, Gainesville, Florida
Amir Helmy developed the Seizario app, “a mobile application designed to aid epileptic patients, their families and caregivers in managing their daily lives effectively, using smartphones. Seizario aims to offer two main features; automatic detection of several emergency scenarios, and easy and immediate communication of critical information to family members and caregivers.” Using an accelerometer-based classification algorithm, Seizario detects seizures and harmful falls. When detected, warning and alert messages are triggered and sent to pre-identified recipients with time, location, and activity. The app also records detailed log entries that can be used by caregivers and medical professionals for analysis and treatment improvement. By using smartphone technology, the potential for reaching more of the population vulnerable to seizures and falls is increased and the offers improved self-management and reduced response times.

Amy Jin, The Harker School, San Jose, California
Amy Jin is using computer vision to evaluate surgical skill and “provide individualized feedback and training to surgeons.” This computer vision “coach” analyzes surgical performance through tool movements and usage patterns to reflect surgical skill and technique. By feeding surgical videos through her computational pipeline Jin has automated surgical skill assessment, focusing on efficiency, motion economy, and bimanual dexterity as areas of examination, in order to provide surgeons with information on how to improve their surgical technique and performance. Assessment results were validated by a team of surgeons. This work sets the stage for “building a context-aware system” to provide surgeons with targeted feedback and training to improve their surgical performance.

Benjamin Spector and Michael Truell, Horace Mann School, Bronx, New York
Submitting as a team, Benjamin Spector and Michael Truell created Halite, an online programming competition. Halite is now in its second iteration and is one of the largest limited-time programming competitions with more than 5,500 users over the course of the two competition runs. Starting with the goal of producing an open-source platform and game where “anyone could easily program a bot, but would also have the depth to support and interest experienced programmers,” Spector and Truell set ambitious requirements for the system, game, and competition desiring a visually appealing, secure, scalable, beginner-friendly, but difficult to solve, multi-faceted competition that would allow the user to write code in any language, test and visualize their bots locally, and once uploaded, would play against other bots in real time and the user would receive performance feedback in real time. Halite has successfully allowed thousands of users, mostly university and high school students some of whom have never programmed before, the opportunity to learn new skills ranging from programming languages to machine learning. The collaborative environment encouraged by Halite, and its creators, has had a tangible impact on computer science education through gamification.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “ We hope that, whatever careers these students ultimately pursue, they will consider the ways in which technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

“I always enjoy reading about the Cutler-Bell Prize-winning projects and the surprising technologies the students have envisioned to solve a problem in society or business,” says ACM President Vicki L. Hanson. “ACM has long championed the idea that integrating computer science education throughout the K-12 curriculum fosters computational thinking—or a new way of seeing the world. The Cutler-Bell Prize-winning projects are excellent examples of computational thinking in action. ACM thanks Gordon Bell and David Cutler, our partners at the CSTA, and the computer science teachers who have guided and inspired this year’s Cutler-Bell Prize recipients.”

“I am so impressed by the winning student projects, and the many other high quality submissions we received this year. The winning projects are examples of the novel solutions to real world problems that students create when they have access to a high quality computer science education,” said Jake Baskin, Executive Director of the Computer Science Teachers Association. “I can’t wait to see the explosion in new ideas as the number of K-12 students learning computer science continues to increase.”

For more information about the ACM/CSTA Cutler-Bell Prize in High School Computing, visit http://awards.acm.org/cutler-bell and http://www.csteachers.org/CutlerBell.

The recipients of the Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Three high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize recipient receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s annual conference, July 8th-11th, in Baltimore, Maryland.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Elizabeth Hu, Thomas Jefferson High School for Science and Technology (VA)
A computational model based on real-world data offers potential guidance for both policy and humanitarian aid decisions. Elizabeth developed a geographically explicit agent-based model, written in Java, to study the past and future patterns of refugees for researching past migration models. Traditional migration modeling techniques, including spatial interaction and regression, fail to account for individual differences and decision-making processes.

Avi Swartz, Cherry Creek High School for Computational Biology (CO)
Determining what proteins are present and the quantity of each protein component in biological samples is a key step in analysis to understand normal, as well as diseased, processes. Mass spectrometry is the best approach to effectively analyze large numbers of proteins in complex biological samples. Many mass spectrometry experiments often involve large numbers of proteins (e.g. over 600 proteins in an experiment). When done manually, this process takes around six hours for a small experiment of 25 proteins. Swartz’s computer program, the “Automated Peptide Selector” (APS), automates the picking of indicator peptides for any protein in any species. The researcher inputs a list of proteins and selects different weights for the selection criteria to adjust for a specific spectrometer. The researcher also selects information such as the species being studied and which versions of the databases they want to use. The program reduces the required user time to select peptides from six hours for 25 proteins to several minutes.

Aaron Walter, Yorkville High School for Computer Science (IL)
Aaron’s new software program Rubric Pro helps teachers recognize students’ understanding of curriculum components. It enables both teachers and students to learn, while improving the classroom experience by being accessible. Rubric Pro organizes components of a curriculum into a hierarchical structure. Teachers can then create rubrics to test the knowledge of their class based on the tree of components they have made. Rubric Pro’s structure allows you to easily create and analyze data from your curriculum’s components.

“It is an honor for us to be a part of this effort to recognize young people who share their visions of how computer science can improve society,” said Cutler and Bell. “The high school years can be very formative in helping young people decide on their careers. Although computer science is so interwoven into society and industry, it is still at the early stages of being fully integrated into the high school curriculum. We hope the Cutler-Bell Prize and the imaginative projects of these students will serve as examples of the benefits of expanding computer science education in K-12 settings.”

“What is wonderful about the Cutler-Bell Prize is how it encourages a spirit of innovation in young people,” says ACM President Vicki L. Hanson. “ACM has long stressed that incorporating computer science education into the K-12 curriculum is about more than learning to write computer code. Computational thinking fosters a way of looking at the world that these students will take with them regardless of the career path they choose. This year’s Cutler-Bell Prize recipients are recognized for taking the fundamentals they have learned in the classroom and developing novel approaches to solving pressing real-world challenges. We thank Gordon Bell and David Cutler for sponsoring this award, the CSTA, and, of course, the dedicated computer science teachers who have inspired and guided these students.”

“The Cutler-Bell Prize celebrates the power of creativity and innovation among today’s high school students when their learning experiences are linked to technology and computer science education,” said CSTA Executive Director Dr. Mark R. Nelson. “We appreciate the generosity and foresight of Cutler and Bell for making this award possible. We thank the judges who spent many hours reviewing the submissions received in this year’s competition. We are excited to recognize this second cohort of young recipients.”

For more information about the ACM/CSTA Cutler-Bell Prize in High School Computing, visit http://awards.acm.org/cutler-bell and http://www.csteachers.org/CutlerBell.

The first-ever recipients of the ACM/CSTA Cutler-Bell Prize in High School Computing were announced on Saturday, March 19th at the Living Computer Museum in Seattle. The prize, bestowed by ACM (Association for Computing Machinery) and CSTA (Computer Science Teachers Association), recognizes computer science talent in high school students. Each recipient was awarded a $10,000 prize and presented his or her project at the museum.

The ACM/CSTA Cutler-Bell Prize seeks to promote the field of computer science and encourage its study, as well as to empower young and aspiring learners to pursue computing challenges outside of the traditional classroom environment. The award was established by David Cutler and Gordon Bell. Cutler is a software engineer, designer and developer of several operating systems, including Windows NT at Microsoft, (where he is Senior Technical Fellow), and RSX-11M, VMS and VAXELN at Digital Equipment Corporation. Bell is an electrical engineer and an early employee of Digital Equipment Corporation, where he led the development of VAX. He is now a researcher emeritus at Microsoft Research.

"We are delighted to support this award to recognize, encourage and reward high school students in computing," said Bell and Cutler. "We created this contest as a way to identify and support some of the most innovative and talented youth in the world of technology and computer science."

The winning projects exemplify the diverse applications of a subject that touches every industry:

Valerie Chen, Thomas Jefferson High School for Science and Technology (VA)
Software systems are relied upon in almost every area of life, but inadequate software testing contributes to an annual cost of nearly $59.5 billion. Chen interned at the Naval Research Laboratory as part of the Science and Engineering Apprentice Program (SEAP), so she got to see first-hand how important this testing becomes for things like submarines. Chen created a software testing tool that she hopes will improve how systems are tested, thereby making our world a safer place.

Matthew Edwards, Blacksburg High School (VA)
Voting is a civic responsibility, but often federal elections see just over half of eligible citizens vote. Edwards wanted to figure out why more people don’t vote. His project addressed voter turnout and the right to vote. Edwards used computer science to develop a new strategy for voting online. He hopes that using technology in local, state and national elections will encourage and enable all citizens to vote and provide solutions to other social problems.

Karthik Rao, Briarcliff High School (NY)
Rao's winning project focused on fuel efficiency for the airline industry. Using old and new technologies, such as Global Positioning System (GPS), to create more efficient flight paths for airplanes, Rao showed that decreased fuel usage could translate into big savings economically and environmentally.

Cherry Zou, Poolesville High School (MD)
There are an estimated 556 million victims every year and 18 victims every second of cybercrimes. Zou chose to focus her project on cyberbullying and cybercrimes. She read terrifying stories of people taking their own lives after being cyberbullied via fake social media accounts. Her project aimed to use an author’s writing style to correctly identify anonymous social media posts. Zou wants users of social media to be held accountable for their harmful actions.

In today's job market there is an increased need for computer scientists. Estimates point to 4.4 million computer science job openings in 2024, according to the Bureau of Labor Statistics. The Cutler-Bell Prize hopes to encourage, identify and nurture interest in computer science and ultimately produce more computer scientists.

"We are grateful to Cutler and Bell for creating this prize," said ACM President Alexander L. Wolf. "ACM has led the effort to integrate computer science into the K-12 curriculum. As computing becomes increasingly prevalent in all walks of life, providing young people with access to quality computer science education is essential. We need to harness the creativity of our youngest citizens and cultivate their interest in being the creators of new and innovative technologies and products."

"Few fields can provide students with as much opportunity as computer science can today," said CSTA Executive Director Dr. Mark R. Nelson. "These students are developing exciting and original solutions to the world's biggest problems using computer science. The Cutler-Bell Prize demonstrates the possibilities if every student had access to a quality computer science education."