2020 EUREKA! 2.0 Faculty Research Proposals Project Title ... · adapting the internship into a EUREKA! 2.0 Research Option, in which case, they will be mainly working on computer

2020 EUREKA! 2.0 Faculty Research Proposals – Updated 4/24/2020

2020 EUREKA! 2.0 Faculty Research Proposals The following list details projects available for the 2020 EUREKA! 2.0 Program. All students participating in the program are required to have a computer with a camera and microphone as well as a strong internet connection, access to Zoom, and the additional equipment listed for their project. Project Title: Application of Data Driven Models to Forecast Flooding Events Mentor: Dr. Vidya Samadi, Assistant Professor Department: Agricultural Sciences Project/Faculty URL: [email protected] Project Description:

This internship project focuses on simulating water resources systems in the Carolinas. The students will work remotely on the application of a new package, "FAIS" (Flood Analytics Information System) developed using NSF grant to gather real-time flood data from different web servers. The students will work closely with the faculty and her graduate students to: i) elaborate dataset formatting and preparation, ii) stimulate interest on Data Analytics and web data gathering, iii) implement the FAIS package to gather the data, iv) gain experience with coding and data retrieval from multiple remote websites, and v) motivate the students to pursue education in an interdisciplinary STEM field of information technology and civil engineering. The design and construction of educational modules are proposed for research activities such as learn how to code in python and how to gather flood real time data from various web servers. These will allow the students to learn the importance of informatics and technology in engineering related research. The faculty and her grad student work with the intern through open source cyberinfrastructure such as GitHub.

Student Involvement:

The intern(s) will work on my ongoing research project funded by NSF and will develop a model to simulate flooding events in South Carolina. The intern(s) will also be trained to study the impacts of flooding on critical infrastructure, agriculture, and the environment. They will also contribute to data gathering and archiving research works and learn how to disseminate data at open source cyberinfrastructure such as GitHub. The team will have weekly meetings through Zoom and the faculty will create tasks for the student weekly at Github.

Opportunities:

The intern(s) will be presenting the results at a Clemson research conference, the SC Academy of Science, and other related meetings. It is expected that the intern(s) will be co-authoring research paper with grad students and the faculty member.


Required Skills: Prior knowledge of Windows and Microsoft Office are required. Knowledge about coding, programming, and managing GitHub is a plus.

Additional Equipment Required: Python (free software)


Project Title: Robotics and Autonomous Vehicles Mentor: Dr. Yunyi Jia, McQueen Quattlebaum Assistant Professor Department: Automotive Engineering Project/Faculty URL: http://cecas.clemson.edu/cra/ Project Description:

Develop advanced technologies to boost the development of robotics and autonomous vehicles. The technologies include perception and sensing systems to monitor the environments, planning and control algorithms to control the robot/vehicle, machine learning algorithms to enhance the robot/vehicle performance, and human-machine interfaces to enable natural interactions between humans and robots/autonomous vehicles.


The research intern will be guided by the professor and work with a group of graduate students on the project. Opportunities:

Students will have the opportunity to keep working as a research assistant in the lab. Required Skills:

Students should have a knowledge of programming. Additional Equipment Required: Sensors and software provided by faculty


Project Title: Autonomous Wheelchair and Assistive Mobility Research using Computer Vision and AI Mentor: Dr. Bing Li, Assistant Professor Department: Automotive Engineering Project/Faculty URL: http://cecas.clemson.edu/autonomy Project Description:

The goal of this research is to develop mobility assistance and assistive technologies to provide automated mobility or augment mobility safety for people who are in need. For example, a participant sits on an automated wheelchair, handicapped individuals frequently rely heavily on various assistive technologies including wheelchairs and the purpose of these technologies is to enable greater levels of independence for the user. The goal of this research is to develop autonomous wheelchair and assistive mobility technologies to provide automated mobility and/or to augment mobility safety for people who are in need. For example, a person sits on an automated wheelchair, and it brings the person from inside to the outside autonomous vehicle. Finally, the wheelchair and vehicle will work together to provide accessibility to the person for his travel or work commute. The involved technologies include autonomous robot, computer vision and artificial intelligence (AI).


My original on-site internship was concerning research prototype (mechanical retrofitting, hardware and software) development by letting the interns work with my Ph.D. students side by side. To cope with the current challenging situation of COVID-19, I have a clear idea of adapting the internship into a EUREKA! 2.0 Research Option, in which case, they will be mainly working on computer vision data/algorithms (for AI-based), online cloud computing (e.g. Google Cloud), and portable sensors, so that all of their research can move forward on their home computer/laptop with Internet. I will define feasible goals for each intern; each intern will be guided by me and one of my Ph.D. students; I will invite the interns into my weekly Lab meeting (WebEx); They will present their weekly progress, and final achievement in the form of presentation/report.

Opportunities:

Students can get their internship research into publication. I actually have a current local high school junior student, who has been working with me from last year, just submit a conference paper in this week (April 2020). Local students could get the opportunity to continue research in my group even after the internship period. They can master artificial intelligence (AI) computing techniques for data (e.g. photos, camera data, sound, et al) using cloud computing, and they can apply what they learned from this internship in any of their future projects and even for a great societal impact. They can practice their presentation skills, and learn how a scientific research group works for research merit and broader impact.


Required Skills: Students should have basic skills of programming experience (e.g. Python, Java, Matlab or equivalent) as well as regular computer/web operation skills.

Additional Equipment Required: Programming environment setup (e.g. Python, Java, Matlab or equivalent) and portable sensors (e.g. standard camera, stereo camera, RGB-Depth camera, or 3D camera-LiDAR), provided by faculty


Project Title: Microbial Metapopulation Models Mentor: Dr. Sharon Bewick, Assistant Professor Department: Biological Sciences Project/Faculty URL: https://bewicklab.weebly.com/ Project Description:

Many animal species live in metapopulations - patches of habitats loosely connected by a small amount of animal movement (dispersal) between patches. This has well-studied implications for the persistence and population abundances of a number of animal species. Less well understood are the implications for parasites and commensal microbes that inhabit these animals. We will be using mathematical and computer simulation models to study how metapopulation structure impacts microbial populations and communities on host organisms.


Students will use NetLogo to develop computer simulation models of microbial populations living on hosts whose own populations are structured into metapopulations.

Opportunities:

Continued work in the Bewick lab is encouraged for students who enjoy their experience. Students who have become comfortable coding or developing mathematical models could develop their own projects and research questions, if interested, and these would, ideally, lead to publications. Longer term, opportunities in third and fourth year to participate in UPIC programs or to conduct Honors Thesis work would also be encouraged.

Required Skills:

An interest in computer programming and mathematics is required. Previous experience coding is desirable, but not required. Additional Equipment Required: Textbooks listed by faculty


Project Title: Enhancing Production of Therapeutic Antibodies by Control of Cellular Stress Response Mentor: Dr. Mark Blenner, McQueen Quattlebaum Associate Professor Department: Chemical and Biomolecular Engineering Project/Faculty URL: http://proteinengineering.sites.clemson.edu/ Project Description:

The majority of biopharmaceuticals are produced in Chinese Hamster Ovary (CHO) cells. Improving the production rates of these cell lines can lead to cheaper drugs and more rapid development of novel therapeutics; however, the genetic modifications needed to improve productivity are unclear. Several chemical additives are known to improve the productivity of CHO cells, but often at the cost of product quality, which can render a therapeutic molecular less effective. In this project, we are exploring combinations of productivity enhancers and stress inhibitors that improve productivity without sacrificing quality.


Research interns will do online training in preparation for eventual lab experiments, including mammalian cell culture, purifying RNA, performing quantitative polymerase chain reaction (PCR), protein analysis and western blot. Research interns will be actively involved in analysis of mRNA-seq data analysis and will learn to use the high performance computing cluster and run scripts to analysis large genomic datasets.

Opportunities:

The research projects in my lab will generally have a long life span; therefore, long term research opportunities are plentiful. My hope is that interns enjoy their research experience and continue working with me, and with my group for their years at Clemson. All work in the lab is likely to contribute to a peer-reviewed publication, and authorship potential exists for motivated researchers. Several prior EUREKA! students continued their research during the academic year. Other opportunities include potential to attend scientific meetings, interacting with AMBIC members and future industrial internship opportunities.

Required Skills:

Interns do not need any specific skills or experiences, but the intern should be highly motivated and interested in chemical engineering, bioengineering, biomolecular engineering, genetic engineering, or biochemistry.

Additional Equipment Required: N/A


Project Title: Computationally Guided Design of Materials Mentor: Dr. Rachel Getman, Associate Professor Department: Chemical and Biomolecular Engineering Project/Faculty URL: http://computationalcatalysis.sites.clemson.edu Project Description:

Do you ever wonder what it specifically it is about a material that makes it work the way it does? That is what our group strives to uncover. We use computational techniques to model material function and to predict material compositions that can optimize performance. Projects currently available involve optimization of catalysts, which are materials that accelerate the rates of chemical reactions without being consumed themselves, and magnetic nanoparticles, which have wide applications spanning from nanodevices to biomedicine. In each project, we are using software both to calculate material properties and to simulate performance. Material optimization is done using machine learning based on data points from our collaborators and that we generate ourselves.


EUREKA! 2.0 students will use Clemson University's high performance computing cluster, Palmetto, to generate property predictions. In some cases they will also use tools such as machine learning to identify optimal properties and material compositions. They will also discuss results with our collaborators (experimental and computational) at Clemson University and elsewhere.

Opportunities:

Students are always welcome to continue their research in the group, through Creative Inquiry, Special Projects, or Departmental Honors Research.

Required Skills:

Students should be proficient at using their personal computers and be interested in learning learn new computational skills. Students who enjoyed their high school chemistry courses are also well-suited for this research.

Additional Equipment Required: If computer runs Windows, an SSH client (like MobaXterm, a free software)


Project Title: Computational Chemistry and Simulations of Polymer Nanoparticles for Imaging and Sensing Mentor: Dr. Jason McNeill, Professor Department: Chemistry Project/Faculty URL: http://www.clemson.edu/science/departments/chemistry/people/faculty/mcneill.html Project Description:

The project is focused on design of novel molecular architectures for ultra-small nanoparticles with unique optical properties for imaging and sensing in complex cellular structures. Fluorescence microscopy has long been an important tool in cell biology. Chemists have greatly increased the power of fluorescence microscopy, by making a wide range of differently colored fluorescent dyes and nanoparticles that bind to specific parts of the cell. Advances in sensitive detectors and brighter fluorescent dyes and nanoparticles have enabled the detection and tracking of single molecules in solution and even inside cells, providing a molecule-level view of cell processes. Super-resolution imaging methods have been developed in which a series of images of on-off switching of fluorescent dyes attached to cell structures are processed to reconstruct images with greatly improved resolution. We have recently demonstrated novel nanoparticles with greatly enhanced brightness, resulting in 20X improvement in resolution, down to below 1 nanometer. While the eventual applications of the nanoparticles are for biology and advanced materials, the student project is focused on analyzing recent imaging data from our lab and performing modeling and simulations in order to build an understanding of the nanoparticle switching mechanism in order to improve the nanoparticle properties and better tailor them to specific imaging and chemical sensing challenges. Alternatively, students can use computer simulations to explore the chemical and physical processes involved in nanoparticle formation and structure.


One subproject or task involves image data analysis. We have collected laser fluorescence microscopy imaging data of individual nanoparticles deposited on a glass slide, switching on and off. Student(s) will analyze the image data of nanoparticle switching behavior, using or modifying custom software algorithms, performing statistical analyses of the "on" and "off" times and particle-to-particle variability, and fitting to models, as part of a multi-pronged effort to better understand the underlying physical/chemical picture of the molecular states involved, how they interact, and the length scales and time scales of interactions. In another subproject or task, students will model the fundamental molecular states and molecular processes, such as fast electron transfer and energy exchange processes, which occur on the nanometer length scale and femtosecond timescale, and comprise the mechanism of the on-off switching. In another project, students will use computer simulations to explore the chemical and physical processes involved in nanoparticle formation, structure, and interactions with proteins and cellular membranes, in order to develop strategies aimed at tailoring nanoparticles for specific targets and applications.


Opportunities: The experience could lead to a continuing undergraduate research project, and should provide skills and experience in nanotechnology and computational chemistry methods. This work will be a part of a published research article exploring the mechanisms of on-off switching in these unique nanoparticles and will lead to improved nanoparticles that will lead to improvements in image resolution and broaden the range of systems amenable to study. Students will have the opportunity to learn how to perform scientific calculations on Clemson's Palmetto Super Computing cluster.

Required Skills:

We are looking for students with strong chemistry, physics, and mathematical skills and interest. Some experience or interest in using computer software to solve physics and math problems, and to graph and analyze data sets would be useful. Some interest in lasers, microscopy, and optics would also be useful.

Additional Equipment Required: Matlab, Slack, and access to Palmetto Cluster (available through Clemson)


Project Title: Understanding Lunar Regolith Simulants and Their interactions with Drilling Tools for In Situ Resource Utilization Mentor: Dr. Qiushi Chen, Associate Professor Department: Civil Engineering Project/Faculty URL: http://cecas.clemson.edu/geomechanics/ Project Description:

NASA is building a plan to "put boots on the Moon" by as early as 2024, and eventually, to establish the first permanent American presence and infrastructure on the Moon. A key component is learning to be able to characterize and use in situ resources, in particular, lunar regolith, to develop infrastructure that can support human exploration activities. This project aims to improve our understanding of lunar regolith simulants and their interactions with drilling tools for in situ characterization and resource utilization.


The research interns will work as a team and work closely with the faculty mentor and graduate student. The interns will (1) gain an in-depth understanding of and be able to explain scientific challenges facing current and future NASA Moon exploration missions, as related to the in situ characterization and use of lunar regolith; (2) learn and be able to use computer simulation software to study the mechanisms of lunar regolith-drilling tool interactions; (3) process and analyze computer data; (4) improve technical reading, oral, and written skills through literature survey, project presentations and reports.

Opportunities:

There are two ways for students to participate in continuous involvement in this research: 1) through the faculty mentor's creative inquiry project (#1016 Martian and Lunar Soil Simulants - Characterizations and Feasibility as Building Blocks); 2) through the fellowship and paid internship opportunities offered annually by NASA SC Space consortium (https://scspacegrant.cofc.edu/scholarships-and-fellowships).

Required Skills:

Students should be familiar with Microsoft Office suites, which will be used for research reports and presentations, data processing, and visualization as well as be able to learn new computer simulation software.

Additional Equipment Required: Computer software (e.g., RockyDEM, Trelis, DigitizeIT) provided by faculty


Project Title: Robots Mentor: Dr. Yongqiang Wang, Assistant Professor Department: Electrical and Computer Engineering Project/Faculty URL: http://www.clemson.edu/cecas/departments/ece/faculty_staff/faculty/ywang.html Project Description:

Biologically-inspired swarm robotics communication/control strategy will be developed. Neurons can achieve synchronized firing with amazing robustness and scalability via exchanging simple identical pulses. Using a similar mechanism fireflies can achieve synchronized flashing. Our group has systematically studied the cooperation mechanism of interacting neurons and designed a bio-inspired cooperation mechanism for networked robotics. Based on the developed mechanism, students will use ground robots to implement control and communication algorithms.


Students will use ground robots sent to their home to work with communication and control. Opportunities:

At the conclusion of the project, students will be allowed to continue do research in the lab. Required Skills:

There is no requirement for specific skills. We will teach the intern the skills they need to complete their project. Additional Equipment Required: A Roomba robot will be mailed to student's home by faculty


Project Title: Assessing Carbon Emissions of Timber Harvesting Operations Mentor: Dr. Patrick Hiesl, Assistant Professor of Forest Operations Department: Forestry and Environmental Conservation Project/Faculty URL: https://www.clemson.edu/cafls/faculty_staff/profiles/PHIESL Project Description:

The goal of this project is work towards a better understanding of the fuel consumption and associated carbon emissions of common timber harvesting operations in the US and beyond. An intensive literature review will have to be done to collect published fuel consumption information from across the nation and oversees to account for different harvesting systems used. Fuel consumption values will then be grouped based on harvesting systems and forest types they operated in. The last step will be to link fuel consumption to carbon emission values to estimate total carbon emission for the different harvesting systems.


The intern will review global literature to find information about fuel consumption of different harvesting systems. The web-interface of the Clemson library will be used to search for literature. Reported fuel consumption will be entered into a spreadsheet with appropriate information of harvesting system and stand conditions. The intern will analyze fuel consumption of harvesting equipment and link it with carbon emission values.

Opportunities:

The successful intern may be able to stay on as a technician to continue helping with the project. The intern may possibly be a co-author for a journal article.

Required Skills:

Students should have good Excel skills, be detail oriented, and some knowledge of harvesting operations preferable. Additional Equipment Required: Reference Manager such as Mendeley and membership to professional societies for access to journal articles provided by faculty


Project Title: Crop Genetic Engineering for Enhanced Tolerance to Various Abiotic Stresses Mentor: Dr. Hong Luo, Professor Department: Genetics and Biochemistry Project/Faculty URL: http://www.clemson.edu/cafls/faculty_staff/profiles/hluo Project Description:

Environmental stress is one of the most important factors impacting agriculture production. Development of novel molecular strategies to genetically engineer important crops will lead to new cultivars with beneficial new traits, enhancing crop yield. This project focuses on manipulation of expression of several stress-related candidate genes in transgenic rice and turfgrass plants to achieve enhanced plant performance under adverse environmental conditions such as drought and salt stress, improving agriculture production and economy. A series of online PowerPoint presentations and literature reading and discussion sessions will be organized thoroughly introducing to the students the principles of gene cloning, biotechnology approaches for plant genetic engineering and transgenic analysis to evaluate improved crop performance under adverse environmental conditions.


The students will read and discuss related research papers on plant molecular biology, plant genetic engineering and molecular mechanisms of plant-environment interaction. They will participate in all the online presentations and discussions, and actively interact with myself, graduate students and post-doc researcher to become familiar with the basics about scientific research, gene cloning, gene functional characterization and chimeric gene construction as well as plant genetic transformation and transgenic analysis.

Opportunities:

The students could continue their research in the lab and gain more hands-on research experience and have opportunities to present research data in professional meetings and publish their discoveries.

Required Skills:

No specific skills are required for the students to be involved in this online project. Knowledge learnt from their high school biology course will be good enough to participate in the project. The students will be trained in the lab and learn basic molecular and cell biology techniques including DNA RNA extraction, DNA cloning, plasmid construction, polymerase chain reaction (PCR), plant tissue culture and plant genetic transformation.



Project Title: AI in Biomedicine: Prediction of Novel Human Disease Genes by Genomic Data Mining Mentor: Dr. Liangjiang Wang, Associate Professor Department: Genetics and Biochemistry Project/Faculty URL: https://www.clemson.edu/science/departments/genetics-biochemistry/people/profiles/liangjw Project Description:

In the human genome, most genes actually do not encode proteins; they are non-coding RNA genes. The largest class of non-coding genes is known as long non-coding RNAs (lncRNAs), which are transcripts greater in length than 200 nucleotides, but with no protein-coding capacity. While some lncRNAs have been demonstrated to be key regulators of gene expression and 3D genome organization, most lncRNAs are still uncharacterized. We have thus been developing artificial intelligence (AI) and machine learning approaches for the functional annotation of human lncRNAs through mining the vast amount of genetic and genomic data ("biological big data"). Our recent studies demonstrate that genomic data mining can give insights into RNA functions and provide valuable information for experimental studies of candidate lncRNAs. This research project will focus on the identification and functional analysis of novel candidate lncRNAs associated with human diseases, including intellectual disability (ID) and autism spectrum disorders (ASD). ID and ASD are clinically and genetically heterogeneous complex disorders, affecting up to 3% and 1% of the human population, respectively. ID is characterized by diminished intellectual capacity and adaptive reasoning, whereas ASD is recognized by impaired social communications and restrictive or repetitive behavior. Both disorders originate in early childhood, and involve a large number of genes essential for normal brain development and function. However, in most cases of ID or ASD, the specific genetic factors of the disorders are still unable to be determined. Until recently, only protein-coding genes were studied for their involvement in ID and ASD. It is thus likely that many of these disease-causing genetic factors may reside in lncRNAs, which are enriched in the brain. The research interns will learn how to build machine learning models for candidate disease gene prediction, and then utilize publicly available genetic and genomic data to further characterize and prioritize the candidate lncRNAs. The high-priority candidates identified in this project can not only provide new insight into the roles of lncRNAs in genetic brain disorders, but may also be further developed as biomarkers.


Research interns will be directly involved in the project. Each intern student, under the supervision of a graduate student, will learn how to build a machine learning model for candidate disease gene prediction and prioritization. They will also contribute to the further evaluation and curation of novel candidate lncRNAs associated with genetic brain disorders.

Opportunities:

The data analysis skills learned through this project can be useful for future careers in bioinformatics, genomics, human genetics, and precision medicine.


Required Skills: Research interns are expected to have good computer skills and understand the basic concepts of genetics. Although prior experience with computational research is not required, the interns are expected to be willing to learn computer programming and basic machine learning techniques used in genomic data mining.

Additional Equipment Required: Computer software for programming and data analysis (free for students)


Project Title: Characterization of Mutated DNA Repair Genes Mentor: Dr. Michael Sehorn, Associate Professor Department: Genetics and Biochemistry Project/Faculty URL: https://www.clemson.edu/science/departments/genetics-biochemistry/people/profiles/msehorn Project Description:

The project is to learn about new DNA repair genes and plan the construction of bacterial expression plasmids and mutations of the DNA repair genes to be made. This is an important aspect of research to ensure the process makes logistical sense prior doing the benchwork. Each intern is given at least one DNA repair gene. For each gene the intern will design bacterial expression plasmids that will be used to express the protein encoded by the DNA repair gene. The intern will research the gene to determine important secondary structural elements of the protein encoded by the gene that might contribute to the activity of the protein. The student will then design mutations to introduce into the gene to alter the structural element in the gene. The student will familiarize themselves with techniques that will be used to insert into the bacterial expression plasmids they design. The student will propose how to optimize bacterial expression and make a diagram of what the expected result would be. The student will familiarize themselves with protein purification and propose a strategy to attempt to purify the protein they are constructing.


The interns will do the work described in the Project Description guided by graduate students and the Professor. The progress of the project is dependent on how much the intern puts into the project. The intern will learn about bacterial protein expression in order to design a bacterial expression plasmid. The intern will learn about secondary structure in proteins and how to identify it in a protein sequence. Using this knowledge, the intern will then design mutations to introduce into the gene to alter the structural element in the gene. The intern will learn how to purify DNA, conduct PCR, induce bacteria to express their protein and purify it. We show the intern how to do these processes. Then we observe the intern do the process, providing assistance if needed. Lastly, we let the intern do the process by themselves. They can of course ask someone for guidance should they need it. By the end of the internship, the student will be able to do these techniques without any assistance.

Opportunities:

If the student enjoys the research and gets along with the people in the lab, we will ask the student to join the lab for the entire time the student is at Clemson giving the student 4+ years of research experience.


Required Skills: There is no requirement for specific skills. We will teach the intern the skills they need to complete their project.

Additional Equipment Required: Google Docs, Word, or Pages; pdf reader


Project Title: Revised Anderson Historic District, Anderson, SC Mentor: Dr. Christa Smith, Associate Professor Department: History and Geography Project/Faculty URL: http://www.clemson.edu/caah/departments/history/people/facultyBio.html?id=538 Project Description:

The Anderson Historic District was placed on the National Register of Historic Places in 1971. Typical of district nomination documents of this vintage, the inventory of contributing properties is incomplete. It is estimated that less than half of the properties are accounted for at this time. The absence of a comprehensive inventory for this district makes it more difficult to identify contributing properties when this information is needed, for example, when an owner is interested in applying for rehabilitation tax credits.


As a team, students will create a StoryMap of the downtown Historic District using online photographs/maps/deeds/and original National Register Nomination submission.

Opportunities:

The students will have the opportunity to present the updated district visually using StoryMap software. Required Skills:

Students should have experience with GIS software to create a StoryMap of the historic district. The City of Anderson has some interactive web mapping available and any intern must be willing to learn how to navigate mapping software to create a basic map for this project.

Additional Equipment Required: Bing Maps, National Register Nomination guidelines, and ARCGIS StoryMaps


Project Title: Computational Cardiovascular Research Mentor: Dr. Ethan Kung, Assistant Professor Department: Mechanical Engineering / Bioengineering Project/Faculty URL: www.cmerl.com Project Description:

In this project students will use computational methods to help solve clinical problems related to the cardiovascular field. This may include simulations to model the cardiovascular system, potentially constructing patient-specific models, and analysis of clinical database to identify trends and regression models. The project may extend to computational modeling of related medical devices. The basic science aspect of the research may include simulations investigating the fundamental behaviors of water.


Students will learn how to use new software to perform computer simulations and data analyses to answer scientific or clinical questions. The computational models that we employ include low-order circuits models, high-order 3D finite element models, and artificial intelligence based regression modeling.

Opportunities:

Students will have the opportunity to continue related research in Creative Inquiry or summer research. Required Skills:

Students must have the ability to learn to use new engineering software, and be able to learn basic data processing and coding in Matlab. The ability to grasp new scientific concepts is also helpful.



Project Title: Climate Resilient Crops for Food Security Mentor: Dr. Sruthi Narayanan, Assistant Professor Department: Plant and Environmental Sciences Project/Faculty URL: https://www.clemson.edu/cafls/faculty_staff/profiles/skutty Project Description:

Climate models predict continued warming and increased frequency, duration, and intensity of droughts across the southeast U.S. Between 2000 and 2018, South Carolina experienced drought [Moderate (D1) - Exceptional (D4)] every year except 2014. In 2015, 35 counties in South Carolina were declared as primary disaster areas due to drought by the U.S. Department of Agriculture. Our research focuses on understanding crop response and adaptation to changing environmental conditions (water and temperature) in order to develop climate resilient crop varieties. In this summer, we will be evaluating soybean, peanut, and cotton varieties for their performance under drought and heat stress conditions. We will also evaluate the effect of cover crops (crops that provide a ground cover and improve soil organic matter content) on conserving soil water and improving soil health.


The research interns can process some microscope images to estimate peanut pollen viability. They can do literature review and participate in our lab meetings virtually. Our team can train them in some data analysis (e.g., soil volumetric water content and insitu root image analysis), if they perform the assigned tasks skillfully, we can continue involving them in data analysis. The projects will continue even after the summer; there is a possibility for the interns to continue working on the same projects in the Fall semester as well.

Opportunities:

They will get an opportunity to continue research in our lab (depending upon their performance in the summer). In the long run, there is a potential opportunity for a graduate research assistantship, if the student demonstrates potential for a researcher.

Required Skills:

Students should possess a passion for plant science, the ability to work as a team, and basic computer and software skills (to connect to us remotely).



Project Title: Automatic Genomic Information Extraction from Online Resources Mentor: Dr. Xia Jing, Assistant Professor Department: Public Health Sciences Project/Faculty URL: https://www.clemson.edu/cbshs/faculty-staff/profiles/xjing Project Description:

This project will explore the feasibility and challenges in building an automatic information extraction prototype. The prototype will focus on the extraction of clinically actionable genomic information from several online publicly accessible resources, e.g., PharmGKB, CliniGen, OMIM, FDA Pharmacogenomic Biomarkers. Genomics information is critical in developing individualized care plans or forming personalized clinical decisions. Clinically actionable genomics information is a critical component in realizing precision medicine. However, one bottleneck in delivering precision medicine is to provide precise and clinically relevant genomics information continuously, conveniently and in a timely manner. The ever-growing genomics knowledge resources provide a huge challenge to the current manual extraction process. An automatic information extraction tool has the potential to play a significant role in realizing precision medicine. The output of the automatic extraction tool can be utilized in broad applications in health care delivery, e.g., as a structured knowledge source for individualized clinical decision support. We have made significant progress in selecting, comparing available publicly accessible resources and extracting clinically actionable genomics knowledge manually. The student will utilize the existing manual extraction results and controlled terminologies to explore the feasibility of developing a prototype guided by the supervisor. The student needs to have proficient programming skills and experience to fulfill the role. The position will provide hands-on experience for the student to obtain experience in natural language process, terminology services, automatic information extraction and freedom to pursue creative solutions during the process.


The student will set up a routine work schedule during the project period. The specific work schedule can be discussed with the supervisor based on the student's course load. The student needs to (1) extract clinically actionable genomics terminologies via UMLS; (2) build a pipeline to extract the terminologies from UMLS automatically; (3) participate in prototype design and feasibility exploration; (4) set up development environment to build the information extraction prototype (a customized Web crawler), the extraction can start from one web page or one PDF file until to the granularities of one paragraph or relevant sentences; (5) adjust the configuration of the prototype when testing the tool in multiple resources; (6) update the prototype and possibly other tasks related to building the prototype. The student needs to be able to work from home via Internet connection and meet with the faculty mentor via Webex to report progress, ask questions if needed, and discuss to solve issues regularly. The student needs to be able to follow the work schedule without distraction and make progress on a daily basis.

Opportunities:

Students may have chances to present in professional conferences in health informatics (if the results are noticeable and the submission can be accepted). Students also have chances to be a co-author in manuscripts prepared from this project.


Required Skills:

Ideally, the candidate should be a computer science or computer engineering major. The student should have a good understanding of programming and database management and should have prior hands-on experience in applying such knowledge in real-world projects or course assignments. The student should be able to use Python, MySQL, MS Access, JavaScript, and PHP proficiently. Strongly preferred characteristics of the candidate being detail-oriented, possessing a strong work ethic, being a self-starter, be able to follow the work schedule diligently, and having the capability to solve problems.

Additional Equipment Required: Software packages (ex. Webex, Python, MySQL) that are either free or provided by faculty


Project Title: Perception of Virtual Characters or Perception of Text in VR Mentor: Dr. Sophie Joerg, Associate Professor Department: School of Computing Project/Faculty URL: https://computing.clemson.edu/vcl/people.html Project Description:

In this summer project, we want to investigate the perception of errors/changes in character animation or of text in virtual reality. Student Involvement:

The research interns will need to learn how to use the game engine Unity 3D. They will prepare a perceptual experiment, if possible, run it (potentially using Amazon Mechanical Turk) and (with help) evaluate their results. Nearly all of these tasks will be performed in teams.

Opportunities:

They are welcome to continue working with me in the Fall semester. Required Skills:

Students need to be interested in technology, programming, and visual computing. They need good problem-solving and debugging skills. They need to be able to communicate and follow a research protocol.

Additional Equipment Required: Unity 3D license, Adobe Premiere, Qualtrics, reasonibly powerful laptop or desktop PC, having an external monitor is a clear advantage, external mouse (not just a touchpad), Unity Editor system requirements (https://docs.unity3d.com/Manual/system-requirem

2020 EUREKA! 2.0 Faculty Research Proposals Project Title ... · adapting the internship into a EUREKA! 2.0 Research Option, in which case, they will be mainly working on computer

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