Sustaining diversity and INCLUSION throughout a summer of social distancing

08.25.20 -

In present-day, the conditions of climates that surround us are constantly changing, from meteorological to cultural and social, we are required to adapt and move away from certain concepts of how things used to be done. During these trying times, supporting efforts and initiatives that work toward achieving more diversity, inclusion, and equity is essential to bringing us, as a society, closer together. Even as we practice social distancing this summer, sustaining these efforts continue to remain a top priority to the National Center for Supercomputing Applications, remotely and in-office.

Although working and studying remotely has its challenges, NCSA’s REU-INCLUSION (Incubating a New Community of Leaders Using Software, Inclusion, Innovation, Interdisciplinary and OpeN-Science, led by PI Daniel S. Katz and co-PI and coordinator Olena Kindratenko) fellows were still able to participate in the 10-week Research Experience for Undergraduates program which included students from the Inter-American University of Puerto Rico and the University of Illinois at Urbana-Champaign. Also, interns from our Student Pushing INnovation (SPIN) program (led by Olena Kindratenko) were able to continue working on these projects. Both programs allowed students to virtually collaborate with field expert mentors, participate in networking events and professional development seminars, and gain invaluable experiences that contribute to shaping their futures.

This summer, REU-INCLUSION fellows and SPIN Interns worked on a variety of projects and received hands-on experience with utilizing high-performance computing, artificial intelligence, advanced visualization, machine learning, open-source software, and deep learning across multiple disciplines. From astronomy to computer science, both fellows, and interns worked closely with NCSA affiliated field experts who mentored, guided, and provided insights to students throughout their respective projects. Below we share project details, stories, and experiences of students and mentors from our REU-INCLUSION and SPIN programs.

Project: Human Fall Detection

Mentor: Volodymyr Kindratenko
REU Fellow: Arnaldo Roman, Computer Science, Inter-American University of Puerto Rico
SPIN Interns: Aneesh Lodhavia, Computer Science; Dhruv Sirsikar, Computer Science; Prannav Gupta Computer Engineering; all at UIUC

This project started last fall as part of Professor Volodymyr Kindratenko's RC Evans Disruption Fellowship at UIUC's Gies College of Business to develop a system to detect human falls. Throughout the year, many students worked diligently on this project and worked closely with Kindratenko and Shirui Luo, a postdoctoral researcher at NCSA's Innovation Systems Lab who advised students and helped with the overall model development. This summer, the REU-INCLUSION program contributed to the assembly of a diverse team which resulted in the culmination of prototypes of the developed system to detect human falls. "Teamwork is what made this project a success," says Volodymyr Kindratenko, senior research scientist, lead of the Innovative Systems Lab and co-director of the Center for AI Innovation at NCSA. "The students worked together to solve a challenging problem that required a lot of manual work to label the datasets, train several models, and write a lot of code to make use of these models. In the end, they came up with two unique approaches to solve the problem, using different technologies with unique characteristics and tradeoffs. It was a joy working with these students throughout the summer program." The program strives to provide an inclusive environment that promotes collaboration between field experts, REU fellows, and SPIN interns to advance research and broaden the scientific community.

Luo adds, "It has been a joyful and fruitful summer to work together with these intern students. The REU and SPIN programs provide participants great opportunities to get involved in interesting and challenging projects at NCSA. During the last two months, we were able to review and revise two deep learning models for human fall detection, which can potentially reduce safety hazards in public places. Finally, we implemented the models on a low-power edge device that can run in real-time. Both the students and mentors can learn and benefit a lot."

REU-INCLUSION fellow Arnaldo Roman and SPIN intern Dhruv Sirsikar used IBM's PowerAI Insights tool deployed on HAL (Hardware Accelerated Cluster) and publicly available datasets to train an action recognition model based on the Structured Segment Network (SSN). Once the model was deployed for remote use, they worked on developing an application that sent short video sequences to the IBM PowerAI Insights server that runs SSN to get a response. Sirsikar implemented a Python-based web application that can run on any device while Arnaldo worked on an Android-based application that runs on a mobile platform.

"I've learned a lot from using artificial intelligence and machine learning, how this can help many people. In the project, my role was to work with training a model so that it could detect a falling action in a given video. My mentor was very communicative, supportive, and understanding," says Roman. "I'm very honored to have been a part of such a big group with many different ethnicities and appreciate the opportunity. I will always cherish the experience and knowledge gained from REU-INCLUSION. I am proud to be a part of such an amazing program that offers this experience to students from all over the world." Roman shares that he plans to either join the CS workforce or further advance his education in grad school after graduating from the Inter-American University of Puerto Rico in 2022.

"During this project, my role involved developing an ML model which could run satisfactorily and detect a human being falling accurately and efficiently. I worked with formatting data in a suitable way to feed into our SSN model which could detect a falling action. My mentor was very helpful and had a vast knowledge of the project. Meeting with him thrice a week allowed me to continuously keep abreast of my progress and work towards a defined goal." says Sirsikar. "I believe that REU and SPIN are taking strides to improve diversity in STEM. Through the REU Inclusion program, I met many people from very diverse fields of study. Many workshops took place to bolster diversity in STEM. Workshops like "Women in STEM" were important to understanding how minorities perform in STEM and I believe it's very important to encourage their participation." Sirsikar shares that he plans to work and gain experience in the software engineering industry after graduation then pursue an MS in Computer Science.

Aneesh Lodhavia and Prannav Gupta, SPIN interns and UIUC undergraduates, worked on training a deep learning model that could be executed on an IoT edge platform using Intel's OpenVINO-supported hardware to enable real-time execution. They analyzed the performance of several models that could feed optical flow into a convolutional neural network in real-time. Aneesh trained the I3D CNN model on the HAL cluster and ported it to the OpenVINO framework. Meanwhile, Prannav implemented a C++-based code that works on the Raspberry Pi board with Intel Neural Compute Stick 2. This model has the advantage of working directly on raw video without the need to compute optical flow.

"I am extremely fortunate to have been able to participate in the SPIN program, as it provides all participating students with a unique challenge and a wealth of resources. Through the mentorship, I gained confidence in my ability to analyze novel problems and apply my prior computer science knowledge to new domains," says Lodhavia. "I felt that SPIN fostered an inclusive community of highly talented and motivated students. I witnessed how varied backgrounds and experiences were conducive to innovation and problem-solving. SPIN highlights the importance of diversity in STEM through the unique undertaking every student had in their particular area of research. Though we faced the unprecedented challenge of working remotely due to the pandemic, I learned how to effectively communicate with the team and present ideas for constructive feedback." Lodhavia shares that the AI experience gained through his SPIN project will be extremely beneficial during his time as a C3SR-URAI scholar in the upcoming school year. He is expected to graduate in 2022 with his BS and MS in Computer Science and is interested in pursuing a career in the industry.

"The SPIN program gave a really good insight into how research happens and allowed me to explore a lot of other domains through events such as the lightning talks and the final poster presentations. I was responsible for deploying the trained model on a low-powered Raspberry Pi to detect human falls and developing a notification/chatbot system to alert someone when a fall is detected. My mentor provided me continuous feedback which helped me learn a lot about various computer architectures and frameworks and to consider certain limitations while designing end-to-end solutions," says Gupta. "I was able to completely design and implement an application in collaboration with my teammates and mentor virtually. I think that the SPIN and REU programs are a great way to encourage more people, especially those from traditionally underrepresented backgrounds, to explore a career in STEM and academia. Overall, I had an amazing experience." Gupta shares that there are options worth exploring both academically and professionally after graduating in 2022.

Project: Resolving Racial Health Disparities by using Advanced Statistics and Machine Learning on Complex Multidimensional Datasets

Mentor: Zeynep Madak-Erdogan
REU Fellow: Hector Cruz, Computer Engineering, Inter-American University of Puerto Rico

This project uses machine and deep learning to help understand the exact combinations of factors that drive health disparities. Be it racial, economic, rural-urban, gender- or age-based, understanding the underlying causes and making reliable predictions that drive informed decisions by policymakers and health practitioners requires tackling complex datasets. Another aspect to consider is civil infrastructure: quality of water, sewage, electricity, proximity to education, transportation, and medical centers, and the quality of buildings where people live and work. This project uses advanced geostatistical methods to isolate neighborhood clusters and test whether these neighborhoods are more or less likely to exhibit certain soil or water contamination, or socioeconomic patterns and increased health risks. The project required the development of advanced statistical and machine learning approaches to study the effects of pollution and poverty on rural and racial health disparities in Illinois.

Advanced, big-data computational methods developed in this project will provide tools for a true systems approach to health disparities, that allows a multi-scale, multi-dimensional analysis of all aspects of this problem. This will arm citizen scientists with necessary data to argue their case to legislators, and identify the right complex of factors to be targeted as part of the societal intervention strategy. Over the summer, REU fellow Hector Cruz, a computer engineering student at the Inter-American University of Puerto Rico, contributed to this project and worked closely with Zeynap Madak-Erdogan, professor of Food Science and Human Nutrition. "It is a privilege to work with students like Hector. We are very grateful for NCSA's REU and SPIN programs that led to a productive summer," says Madak-Erdogan.

"In the REU program, I learned to ask questions whenever I am unsure of anything because you do not need to know everything beforehand. Valuable experiences are gained through hands-on opportunities such as this one. My mentor was patient, encouraging, and resourceful. She taught me to take everything step by step by setting weekly goals that I could focus on," says Cruz. "My role was to use machine learning to get several molecules that could show the disparities between African American women vs. Non-Hispanic White women which also increased my understanding of diversity and emphasized its importance. I was able to meet a lot of people with different ethnicities, not only students but also professors and presenters which leads me to believe that the program is committed to improving diversity and inclusion in STEM." Cruz shares that he is exploring career and advanced education opportunities to prepare for graduation in 2021.

Project: Riding the Epidemic Wave: Nowcasting and Forecasting of COVID-19 in Illinois and Beyond with Various Intervention Protocols

Mentor: Ahmed Elbanna
REU Fellow: Mary Cook, Bioengineering, UIUC

This project seeks to model the COVID-19 pandemic and its impact across the United States through data analysis and stochastic simulation to better understand and predict virus activity and patterns. Weekly case and death data collected by Unacast, Google, and divoc-91 is analyzed through the general Susceptible-Infected-Recovered model to identify accurate patterns. When the data is inputted into the model, it allows for the connection between contracted cases, case deaths, adherence to state guidelines, and reduction in mobility. Due to current events and global effects of this pandemic, this information is crucial to the development of policies and guidelines to help mitigate its spread.

This summer, REU-INCLUSION fellow and UIUC Bioengineering student Mary Cook, worked alongside Ahmed Elbanna, associate professor of Civil Engineering at Illinois. "I have learned so much through this project under Elbanna's mentorship. I appreciate that he has consistently made himself available to meet with me, and has provided me with support and feedback along the way," says Cook. "I liked the way that he structured my research project direction to align with my interests and curiosity. He encouraged me to ask questions and share struggles that I experienced, and even invited me to extend my research beyond the internship program."

Using MATLAB, a virtual application and toolbox that allow users the ability to analyze data, develop algorithms, and create models, Cook developed a stochastic model that simulates state curves in regards to COVID-19 cases. "I learned that there are many different approaches to attack the same problem," says Cook. "My work with COVID-19 was focused through a specific lens. I attended several other COVID-19 modeling presentations by fellow interns, and it was very interesting to learn how other departments are using different technologies and angles to accomplish the same goal of better understanding the virus' spread."

Cook shared that working remotely helped her further develop her communication skills and helped keep her accountable to project deadlines and responsibilities. "My time as an REU fellow has introduced me to many people and applications of research primarily through organized professional development workshops. I value the connections that I’ve made with my peers through social meetings and professional events, and it was a very encouraging environment where peers in the scientific community can connect and learn about various research projects," says Cook. "I especially appreciated the Women in STEM workshop and hearing women share their struggles and experiences in research and industry positions. I also appreciated the diverse group of panelists that were chosen to speak about grad school, which showed to me REU's commitment to prioritizing inclusion. Not only was it beneficial to hear experiences different from my own, but it was inspiring to be able to see myself in the people that were speaking."

Project: Weighing Black Holes with Deep Learning

Mentor: Xin Liu
REU Fellow: Sneh Pandya, Physics, UIUC

This project focuses on developing a convolutional neural network that can predict the mass of supermassive black holes (SMBHs) using time series spectra and redshift data. SMBHs, also known as quasars, are one of the most energetic luminous cosmic objects in the Universe that are actively growing by accreting gas from its surroundings and emitting light time series. It is also ubiquitously found at the center of most galaxies. Measuring its masses is important to fundamental science and provides insight to better understand the origin and evolution of quasars, and enabling its usage as a Standard Candle in cosmology. However, traditional weighing methods use spectral data which are highly expensive to gather and heavily affect the amount of time that it takes to measure each SMBH. To put things into perspective, scientific community efforts have accumulated around one million existing masses over 20 years. The highly anticipated Rubin Observatory project, formerly known as the Large Synoptic Survey Telescope project, is predicted to discover around one billion new SMBHs across most of the observable universe. Utilizing traditional methods to weigh this new data would take 20,000 years to complete, therefore, a more efficient approach is necessary.

Combining astronomy Big Data and machine learning tools, the effort to develop a new interdisciplinary approach was led by Astronomy Professor Xin Liu. UIUC Physics major Sneh Pandya joined Liu's team as a SPIN intern. "Sneh has been working with me on a project that uses deep learning to estimate the masses of black holes using photometric light curves. He is an extremely fast learner and a natural communicator. He knew very little about coding when he started but now he is an elite at coding and data simulation. His biggest contribution has been spear-heading the data augmentation and statistical analysis," says Liu. "He wrote the entire script for augmentation and optimized it to run on the GPU cluster HAL at NCSA's Innovative Systems Lab. Sneh also contributed to data cleaning and organization, data visualization, and data simulation."

Contributing heavily to this project, Pandya even served as a valuable resource to his colleagues and peers, Liu adds "During our group meetings, he acted as a physics liaison, explaining the physics background and the relevant literature to other junior group members. He also designed the project poster and gave a lightning talk that reached a broad audience. In summary, Sneh has grown to be a project leader and is truly a pleasure to work with. He shows great passion and talent in physics, coding, as well as scientific collaboration and communication. I do not doubt that he has a bright future ahead of him."

Pandya joined SPIN last summer and continued to contribute to the project throughout this year. "I've worked on many aspects of the project but specifically on data analysis, data simulation and visualization, statistics, and regression analysis. At my current point, I like to help out any way I can. Recently I was exploring linear regression on some data that we didn't use in our neural network and found a feature that we ended up implementing that improved our results greatly. Lately, I've been focused on developing a visualization for our project in collaboration with the Advanced Visualization Lab at NCSA," says Pandya. "Xin is a great mentor and I'm extremely lucky to have gotten the opportunity to work with her. I started as an astronomy student in one of her classes, and after looking up some of her research interests I decided to reach out to her. Despite not having any prior background in computer science, she allowed me to work on this project and I've learned an incredible amount from her throughout. She's extremely kind and instructive and has stayed active in our project despite a busy home and academic life."

He recalls the experiences and knowledge gained as a SPIN intern: "I've certainly learned a lot about the many applications of advanced computing in science and more generally, our lives. I've seen projects that use advanced computing to make contributions to artificial reality, medical technology and diagnosis, and even investigating socio-economic issues in our country from this computational standpoint. It's opened my eyes to this interdisciplinary approach in research and has made me passionate about it. A key takeaway from my time as a SPIN intern is the importance of collaboration. This summer we had two students from Puerto Rico who were part of the REU program, and it was cool for us to work at the same institution and share our research experiences despite living such different lives. And to share this experience through our common struggle with the pandemic was something very valuable." Pandya shares that he is considering Ph.D. programs in Applied Physics or Astrophysics that specializes in quantum information sciences and computational cosmology as possible options after graduating in 2021.

Project: Multiscale Modeling of the Cell Membrane-Associated Phenomena

Mentor: Taras V. Pogorelov
SPIN Intern: Andrew Sunwoo Lee, Chemistry, UIUC

This project aims to develop workflows that combine computational and experimental molecular data to model and analyze the complex and challenging cell membrane environment. Modeling approaches include classical molecular dynamics, quantum electronic structure, and quantum nuclear dynamics. SPIN intern and UIUC Chemistry major Andrew Sunwoo Lee worked alongside Taras Pogorelov, research assistant professor at the Department of Chemistry, Center for Biophysics and Quantitative Biology, Beckman Institute for Advanced Science and Technology, a faculty affiliate at NCSA, and senior research scientist at the School of Chemical Sciences at the University of Illinois at Urbana-Champaign, and collaborated with experimental labs such as the Pogorelov Lab at Illinois.

"Our lab works in the highly interdisciplinary area of molecular biophysics where we use methods of chemistry, physics, biology, and computer science. This summer, I had a pleasure to mentor Andrew Lee, an intern with the SPIN internship at NCSA. I was impressed by how motivated and enthusiastic Andrew was and how much progress he was able to achieve in the short two months of the program. Andrew came to the lab at the end of his first academic year at UIUC without having experience in scientific computing," says Pogorelov. "By August, he had assembled lipid-based molecular systems used HPC resources to run molecular dynamics simulations using cutting-edge software developed at UIUC, and started to analyze the results that are now being connected with experimental results of our collaborators. I believe that the structure of the Summer component of SPIN and REU at NCSA played a big part in Andrew's progress. Importantly, the experience has prepared Andrew to continue his research in the lab in the fall semester, while taking classes."

Lee gained a lot of hands-on experience as a SPIN intern with various advanced digital resources at NCSA. "My role in the project was to study ergosterol dynamics in the membrane by utilizing various approaches: classical molecular dynamics, quantum chemistry methods, and comparing the ergosterol to the solid-state NMR data. I worked with my mentor, Taras Pogorelov, to bridge previously performed research analysis on cholesterol to my data on ergosterol and connect it to studies of the antifungal drug, amphotericin B," says Lee. "I was granted a prodigious number of resources that I was able to take advantage of. Having the appropriate technology and the correct industry to guide me in my studies was fundamental to advancing the study of ergosterol. As a SPIN intern, I was introduced to a multitude of new methodologies ranging from CHARMM-GUI to XSEDE supercomputer resources that enabled me to perform correct calculations for correct precision."

Mentorship and collaboration are important factors that heavily contribute to the academic and professional success of students in NCSA's REU-INCLUSION and SPIN programs. "My overall experience with my mentor was very rewarding. Taras Pogorelov has been a significant role model since the beginning of my time at Illinois. Despite limited experience, Taras allowed me to work for his lab team, experience work in fields of interest, and strive for greatness. Not only has he been there to guide me but he also taught me new application skills," says Lee. "By introducing me to NCSA SPIN, I have been able to accomplish a prodigious number of tasks: my first research report, my first research poster, and an opportunity to talk about a topic I am extremely passionate about. Taras inspires me to follow my passion and continue my studies in chemistry and biology. NCSA SPIN has taught me so much about different projects and allowed me to check out the works of other interns. Being able to observe the perspectives of other students and their studies gave me so much motivation for the future of our world. Having all these innovative interns share their analysis was a wonderful experience."

Lee further adds "The key takeaway throughout my time in SPIN was experiencing a professional culture and gaining insight into my interests. This program was unique in the sense that it allows students to study topics they are interested in and study under a professional. This internship truly allowed me to learn my strengths and apply these skills to other projects as well as identify areas for future development. In addition to forming professional connections with mentors, SPIN introduced me to many peers with similar interests. I believe REU and SPIN are taking strides to improve diversity and inclusion in STEM because they encourage and accept a wide array of students with different ethnicities, backgrounds, and perspectives. Another benefit of these programs is the wide variety of studies that encouraged me to expand my interests in STEM and view topics from a different perspective than what I was used to. This program was valuable because I was able to connect with new individuals socially and discuss topics that I thoroughly enjoy." Lee shares that he is destined for a future in medicine after graduating in 2023 and currently deciding whether to pursue a pre-med or pre-pharm track.

Project: Gun Violence Sensor

Mentor: Ruby Mendenhall
SPIN Intern: Sarah Kishta, Community Health, UIUC

This project examines the physiological effects of exposure to nearby gun crimes and its impact on the public life and health of African American (AA) mothers. This effort was led by Ruby Mendenhall, associate professor in Sociology, African American Studies, Urban and Regional Planning, and Social Work as well as faculty and affiliate of Carl R. Woese Institute for Genomic Biology (IGB); Institute for Computing in Humanities, Arts and Social Sciences (I-CHASS) and Cline Center for Democracy. Mendenhall and former NCSA visiting research programmer Kiel Gilleade created a mobile health study that analyzed and documented data gathered from wrist-worn wearable biosensors and physical movements tracked via smartphone GPS of 12 participants living in Englewood, Chicago. They collected real-time crime data from the City of Chicago to record specific times and locations of gunshot activity. Using these datasets, Mendenhall and Gilleade assessed the feasibility of detecting short-and long-term impacts of nearby gun crimes on the health and well-being of AA mothers then developed a diary platform that documents how violence affects public life and health in "hidden America." These diaries included unique data visualizations and became a tool to empower AA mothers to communicate how exposure to community violence affects their health to organize around changes in health and public policy.

Exhibited in 2018, the project's research efforts continue. This summer, Mendenhall and Gilleade are joined by SPIN intern and UIUC Community Health major Sarah Kishta to assist in producing a manuscript. "I worked as a research intern along with Professor Mendenhall on the Gun Violence Sensor research project. I looked into past research conducted on the use of biosensors to examine the physiological effects of exposure to nearby gun crimes on African American mothers. My role was to create a literature review on the latest finds and identify the gaps in the literature that relates to African American women living in neighborhoods with a high level of gun violence," says Kishta. "REU and SPIN are taking strides to improve diversity and inclusion in STEM. My fellow researches and mentors were all from different backgrounds with different mindsets who came together to work on research projects. This diversity allowed the sharing of different perspectives and the formation of new ideas to improve and enhance STEM."

Mendenhall adds "Kiel Gilleade and I are excited to work with Sarah, a pre-med student, as a co-author on a manuscript about gun violence and mobile health sensors. Sarah did an excellent job reviewing the scientific literature for us. Her literature review was critical in confirming that we produced new knowledge about how stress affects Black women living in neighborhoods with high levels of violence."

This experience has taught Kishta the importance of communication and the role that it plays in research and technology. "My overall experience with my mentors and SPIN program has been great. I started with zero experience in the research field. I felt lost and unsure of what I was doing. Throughout the process, my mentors gave me the necessary support and guided me throughout the project. Everything started to fall into place afterward. I learned that industry and technology have an impact on the research process. To conduct research, you have to keep up with everyday tech and industry updates and stay aware of what's developing in the world," says Kishta. "A key takeaway from SPIN is that it is best to be clear whenever you communicate with others. It's okay to not know everything, ask questions, and continue to learn every day. I never considered a career in research before this internship. After this summer, I am much more interested in the research opportunities and look forward to engaging in more research experiences." Kishta shares that she is pursuing a Master's in Health Administration after her 2021 graduation and plans to attend med school as well.

Read more about these REU and SPIN projects from the 2020 poster event and view additional information below.

SPIN and REU students who finished the program with distinction and recipients of the Outstanding Mentor certificate:

The following students received a letter of recognition signed by NCSA Director William "Bill" Gropp:

  • Saumya Agrawal, SPIN intern (Project: Discovery of Biomarkers for Coronary Microvascular Disease; Mentors: Alicia Arredondo Eve, Justina Zurauskiene, and Zeynep Madak-Erdogan)
  • Zixuan Chen, SPIN intern (Project: Virtual Reality and Ray Tracing for Computational Materials Science; Mentor: Andre Schleife)
  • Hector Cruz, REU INCLUSION fellow (Project: Understanding Breast Cancer Disparities in African American Women; Mentors: Zeynep Madak-Erdogan and Ashlie Santaliz Casiano)
  • Meridith Embry, SPIN intern (Project: Automation of Genomic Analyses for the Cloud, Grid, and Analytics Platforms; Mentor: Liudmila Mainzer)
  • Xiaobo Huang, SPIN intern (Project: Deep Learning for Gravitational Wave Astrophysics; Mentor: Eliu Huerta)
  • Sarah Kishta, SPIN intern (Project: Gun Violence Sensor Research Project; Mentors: Ruby Mendenhall and Kiel Gilleade)
  • Anshul Shah, SPIN intern (Project: Meeting the LSST Data Challenge: Galaxy Detection and Segmentation with Deep Learning; Mentor: Xin Liu)
  • Bing-Jyun Tsao, SPIN intern (Project: Machine learning approach to computational fluid dynamics; Mentors: Shirui Luo)
  • Hantao Zhang, SPIN intern (Project: Multiscale modeling of fracture in complex materials; Mentor: Ahmed Elbanna)
  • Chenyu Zhao, SPIN intern (Project: Speech-to-text Auto Captioning; Mentor: Michael Miller)

Mentors recognized as outstanding mentors and received an NCSA Outstanding Mentor Certificate:

  • Brian Allan
  • Charles Blatti
  • Kalina Borkiewicz
  • Ahmed Elbanna
  • Elif Ertekin
  • Weihao Ge
  • Kiel Gilleade
  • Xin Liu
  • Shirui Luo
  • Ruby Mendenhall
  • Michael Miller
  • Taras Pogorelov
  • Andre Schlefe
  • Aiman Soliman