Category Archives: Computer Science
16 Pitt students will research electrical grid sustainability through SHURE-Grid – University of Pittsburgh
This summer, 16 University of Pittsburgh students from a variety of disciplines will perform research focused on improving electrical grid sustainability, developing verified vignettes and creating new knowledge building on cyber-informed engineering through SHURE-Grid.
The program is a collaborative partnership between the David C. Frederick Honors College, Swanson School of Engineering, Pitts Office of Research and the Idaho National Laboratory (INL) that provides students with experience solving real-world problems while engaging with one of the 17 national U.S. Department of Energy labs.
Its among 90 Frederick Honors College summer fellowship and internship awards including the prestigious Brackenridge Fellowship as well as opportunities in community research, creative arts, health sciences research and public service. Students from across all disciplines can apply by proposing a research topic, finding a faculty sponsor and committing to completing and presenting their research by the end of summer.
The sixteen SHURE-Grid participants are:
Originally posted here:
Master’s student capstone spotlight: AI-Assisted Frontline Negotiation – Harvard School of Engineering and Applied Sciences
Data science and computational science and engineering masters students at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) take AC297R: Computational Science and Engineering Capstone Project. Taught by Weiwei Pan, Assistant Director for Graduate Studies in Data Science, the course groups students together for semester-long research projects in which they work with client organizations to tackle real-world challenges.
AI-Assisted Frontline Negotiation
Susannah Su (AB/SM 25), Nathan Zhao (AB/SM 24)
Client: Frontline Associates
What real-world challenge does this project address?
Negotiators usually have to read through hundreds of pages of documents, extract and synthesize useful information to form their arguments and agenda for negotiations. In frontline or crisis negotiation, time is the key. Hence, how to process and analyze a large amount of documents very quickly becomes an important question that negotiators care about. This project aims to provide a solution to this question. Using the three tools that we developed empowered by ChatGPT, negotiators will be able to reduce the time needed to go through and analyze all the documents from days to just minutes.
How does this research attempt to solve that real-world challenge?
We made use of existing negotiation preparation frameworks to develop instructions for our customized GPT bot, then tested the instructions to improve the quality of the responses through prompt engineering. We found that our tools generate stable responses and very similar responses to actual human practitioners. On top of that, we also developed a crisis negotiation simulator that will help train practitioners by simulating a real life scenario. The negotiator trainer can use the voice-to-voice function in ChatGPT to actually practice negotiating with different stakeholders in the simulated scenario. We interviewed actual practitioners to get their opinions on using AI in assisting negotiations, and presented at the Berlin Moot Conference for peacemaking to other negotiators.
How did you apply the skills you learned at SEAS to your project?
We used a lot of the natural language processing and language model techniques we learned in class, as well as a technical mindset and problem solving skills that we have built at SEAS.
What part of the project proved the most challenging?
The most challenging part was working with partners that are not technical. As engineers, we talk in engineers languages. But to solve real-life problems, oftentimes our partners come from non-technical backgrounds. It is hard but impactful to be able to translate the needs of non-technical partners into a technical problem, then communicate our progress and concerns in languages that non-technical people can understand.
What part of the project did you enjoy the most?
We really enjoyed the day when we interviewed the experienced crisis negotiator Kirk Kinnell. We let him try the crisis negotiation simulator, and just seeing him getting so excited about AI and actually negotiating with the language model was super satisfying and fun.
What did you learn, or skills did you gain, through this project?
This project actually made us start thinking about doing research in the future. The most important lesson we have learned is that college is what you make of it. Our group included first-generation college students who never thought about studying STEM in high school, not to mention doing a concurrent master in STEM and even considering a Ph.D. We started interacting with more of the research community here because of this project, and we found it very exciting to have the opportunity to tackle problems that you really care about using the skills we have. There are so many opportunities here and so many people who are willing to mentor and help you. You have to be proactive enough to make the most out of these opportunities. We are very grateful to all of the people who have helped and guided me in the past, and now we are in a position doing something that we never thought was possible.
More here:
QS ranks MIT the world’s No. 1 university for 2024-25 – MIT News
MIT has again been named the worlds top university by the QS World University Rankings, which were announced today. This is the 13th year in a row MIT has received this distinction.
The full 2025 edition of the rankings published by Quacquarelli Symonds, an organization specializing in education and study abroad can be found at TopUniversities.com. The QS rankings are based on factors including academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students.
MIT was also ranked the worlds top university in 11 of the subject areas ranked by QS, as announced in April of this year.
The Institute received a No. 1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research.
MIT also placed second in five subject areas: Accounting and Finance; Architecture/Built Environment; Biological Sciences; Chemistry; and Economics and Econometrics.
QS has also released a ranking of specialized masters programs in business. MIT ranked first for its program in supply chain management and second for its program in business analytics.
View post:
QS ranks MIT the world's No. 1 university for 2024-25 - MIT News
UMass Amherst to join $90M US National Science Foundation large-scale research infrastructure for education – EurekAlert
image:
Andrew Lan, University of Massachusetts Amherst
Credit: UMass Amherst
June 4, 2024
UMass Amherst to Join $90M US National Science Foundation large-scale research infrastructure for education
Platform brings together institutions, digital learning and a world-class team to enable research studies to inform efficacy, improvement and innovation in teaching and learning
AMHERST, Mass. The Manning College of Information and Computer Sciences at the University of Massachusetts Amherst has joined thenewly announcedU.S. National Science Foundations (NSF) SafeInsights, a five-year, $90 million research and development infrastructure for inclusive education research. Led by OpenStax-Rice University, SafeInsights is a large-scale education research hub that will safely connect digital learning platforms and educational institutions to learn about learning.This initiative represents the NSFs largest single investment in R&D infrastructure for education at a national scale, and will be the first national infrastructure of its kind.
My specialty is analyzing educational data, extracting insights from it and determining what kinds of interventions lead to the best, most equitable learning outcomes, says Andrew Lan, assistant professor of computer science at UMass Amherst and the UMass lead for SafeInsights. One day, as I was looking at a batch of data from one particular learning platform, I thought: what about all the other platforms, classes and apps a student will use during their day? If were only looking at isolated snapshots of data, then were not really getting a clear picture. Getting that clearer picture is why we need SafeInsights.
SafeInsights includes a multidisciplinary network of 80 collaborating institutions and partners, including major digital learning platforms that currently serve tens ofmillions of students. Lan and UMass Amherst will join together with researchers and large-scale, digital learning platforms to enable privacy-preserving research studies to better understand student learning.
According to nationalpollsconducted by the Data Quality Campaign, 86% of teachers recognize the importance of research in effective teaching. However, the majority of teachers must individually piece together research-informed teaching and learning strategies, often with limited resources.
SafeInsights will enable research studies that help researchers understand how students learn best, no matter who they are, what they are learning, or how they are learning. The insights gained can lead to the development of better, research-informed teaching tools and practices, promoting educational equity.
We know research-informed teaching and learning works. Yet, its still too hard to conduct large-scale, reliable research and then apply the results for more personalized experiences when students need it most, said Richard Baraniuk, C. Sidney Burrus Professor at Rice University, OpenStax founder and SafeInsights project lead. SafeInsights will safely accelerate affordable, rapid-cycle studies across multiple digital learning platforms, leading to more effective tools, practices and next-level innovations.
SafeInsights stringently protects learner privacy.It uses a unique technique called secure data enclaves,which unlocks valuable insights without revealing any student information to researchers or moving student information from the learning tools that it safely lives in today.
Ill be leading the artificial intelligence portion of SafeInsights, says Lan. Our goal is to enable researchers to jointly analyze data from multiple digital platforms in a secure and private way, without actually seeing any data. We need to figure out how to let researchers ask questions of the data, such as how will a particular learning outcome vary by different student demographics, without leaking sensitive information.
There are so many potential advances to be made if researchers can see the whole picture of a student, says Lan. We can really help transform education so that it is more equitable and effective.
Contacts: Andrew Lan, andrewlan@cs.umass.edu
Daegan Miller, drmiller@umass.edu
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
See the original post here:
Ten with MIT connections win 2024 Hertz Foundation Fellowships – MIT News
The Fannie and John Hertz Foundationannounced that it has awarded fellowships to 10 PhD students with ties to MIT. The prestigious award provides each recipient with five years of doctoral-level research funding (up to a total of $250,000), which allows them the flexibility and autonomy to pursue their own innovative ideas.
Fellows also receive lifelong access to Hertz Foundation programs, such as events, mentoring, and networking. They join the ranks ofover 1,300 former Hertz Fellows who are leaders and scholars in a range of fields in science, engineering, and technology. Connections among fellows over the years have sparked collaborations in startups, research, and technology commercialization.
The 10 MIT recipients are among a total of 18 Hertz Foundation Fellows scholars selected this year from across the country. Five of them received their undergraduate degrees at the Institute and will pursue their PhDs at other schools. Two are current MIT graduate students, and four will begin their studies here in the fall.
For more than 60 years, Hertz Fellows have led scientific and technical innovation in national security, applied biological sciences, materials research, artificial intelligence, space exploration, and more. Their contributions have been essential in advancing U.S. competitiveness, says Stephen Fantone, chair of the Hertz Foundation board of directors and founder and president of Optikos Corp. Im excited to watch our newest Hertz Fellows as they pursue challenging research and continue the strong tradition of applying their work for the greater good.
This years MIT-affiliated awardees are:
Owen Dugan 24 graduated from MIT in just two-and-a-half years with a degree in physics, and he plans to pursue a PhD in computer science at Stanford University. His research interests lie at the intersection of AI and physics. As an undergraduate, he conducted research in a broad range of areas, including using physics concepts to enhance the speed of large language models and developing machine learning algorithms that automatically discover scientific theories. He was recognized with MITs Outstanding Undergraduate Research Award and is a U.S. Presidential Scholar, a Neo Scholar, and a Knight-Hennessy Scholar. Dugan holds multiple patents, co-developed an app to reduce food waste, and co-founded a startup that builds tools to verify the authenticity of digital images.
Kaylie Hausknecht will begin her physics doctorate at MIT in the fall, having completing her undergraduate degree in physics and astrophysics at Harvard University. While there, her undergraduate research focused on developingnew machine learning techniques to solve problems in a range of fields, such as fluid dynamics, astrophysics, and condensed matter physics.She received the Hoopes Prize for her senior thesis, was inducted into Phi Beta Kappa as a junior, and won two major writing awards. In addition, she completed five NASA internships. As an intern, she helped identify 301 new exoplanets using archival data from the Kepler Space Telescope. Hausknecht served as the co-president of Harvards chapter of Science Club for Girls, which works to encourage girls from underrepresented backgrounds to pursue STEM.
Elijah Lew-Smith majored in physics at Brown University and plans to pursue a doctoral degree in physics at MIT. He is a theoretical physicist with broad intellectual interests in effective field theory (EFT), which is the study of systems with many interacting degrees of freedom. EFT reveals how to extract the relevant, long-distance behavior from complicated microscopic rules. In 2023, he received a national award to work on applying EFT systematically to non-equilibrium and active systems such as fluctuating hydrodynamics or flocking birds. In addition, Lew-Smith received a scholarship from the U.S. State Department to live for a year in Dakar, Senegal, and later studied at cole Polytechnique in Paris, France.
Rupert Li 24 earned his bachelors and masters degrees at MIT in mathematics as well as computer science, data science, and economics, with a minor in business analytics.He was named a 2024 Marshall Scholar and will study abroad for a year at Cambridge University before matriculating at Stanford University for a mathematics doctorate. As an undergraduate, Li authored 12 math research articles, primarily in combinatorics, but also including discrete geometry, probability, and harmonic analysis. He was recognized for his work with a Barry Goldwater Scholarship and an honorable mention for the Morgan Prize, one of the highest undergraduate honors in mathematics.
Amani Maina-Kilaas is a first-year doctoral student at MIT in the Department of Brain and Cognitive Sciences, where he studies computational psycholinguistics. In particular, he is interested in using artificial intelligence as a scientific tool to study how the mind works, and using what we know about the mind to develop more cognitively realistic models. Maina-Kilaas earned his bachelors degree in computer science and mathematics from Harvey Mudd College. There, he conducted research regarding intention perception and theoretical machine learning, earning the Astronaut Scholarship and Computing Research Associations Outstanding Undergraduate Researcher Award.
Zo Marschner 23 is a doctoral student at Carnegie Mellon University working on geometry processing, a subfield of computer graphics focused on how to represent and work with geometric data digitally; in her research, she aims to make these representations capable of enabling fundamentally better algorithms for solving geometric problems across science and engineering. As an undergraduate at MIT, she earned a bachelors degree in computer science and math and pursued research in geometry processing, including repairing hexahedral meshes and detecting intersections between high-order surfaces. She also interned at Walt Disney Animation Studios, where she worked on collision detection algorithms for simulation. Marschner is a recipient of the National Science Foundations Graduate Research Fellowship and the Goldwater Scholarship.
Zijian (William) Niu will start a doctoral program in computational and systems biology at MIT in the fall. He has a particular interest in developing new methods for imaging proteins and other biomolecules in their native cellular environments and using those data to build computational models for predicting their dynamics and molecular interactions. Niu received his bachelors degree in biochemistry, biophysics, and physics from the University of Pennsylvania. His undergraduate research involved developing novel computational methods for biological image analysis. He was awarded the Barry M. Goldwater Scholarship for creating a deep-learning algorithm for accurately detecting tiny diffraction-limited spots in fluorescence microscopy images that outperformed existing methods in quantifying spatial transcriptomics data.
James Roney received his bachelors and masters degrees from Harvard University in computer science and statistics, respectively. He is currently working as a machine learning research engineer at D.E. Shaw Research. His past research has focused on interpreting the internal workings of AlphaFold and modeling cancer evolution. Roney plans to pursue a PhD in computational biology at MIT, with a specific interest in developing computational models of protein structure, function, and evolution and using those models to engineer novel proteins for applications in biotechnology.
Anna Sappington 19 is a student in the Harvard University-MIT MD-PhD Program, currently in the first year of her doctoral program at MIT in electrical engineering and computer science. She is interested in building methods to predict evolutionary events, especially connections among machine learning, biology, and chemistry to develop reinforcement learning models inspired by evolutionary biology. Sappington graduated from MIT with a bachelors degree in computer science and molecular biology. As an undergraduate, she was awarded a 2018 Barry M. Goldwater Scholarship and selected as a Burchard Scholar and an Amgen Scholar. After graduating, she earned a masters degree in genomic medicine from the University of Cambridge, where she studied as a Marshall Scholar, as well as a masters degree in machine learning from University College London.
Jason Yang 22received his bachelors degree in biology with a minor in computer science from MIT and is currently a doctoral student in genetics at Stanford University. He is interested in understanding the biological processes that underlie human health and disease. At MIT, and subsequently at Massachusetts General Hospital, Yang worked on the mechanisms involved in neurodegeneration in repeat expansion diseases, uncovering a novel molecular consequence of repeat protein aggregation.
View post:
Ten with MIT connections win 2024 Hertz Foundation Fellowships - MIT News
Faculty Position in Computer Science job with KIMEP University | 37661552 – The Chronicle of Higher Education
KIMEP University
Computer Science Faculty Position Advertisement
KIMEP University invites applications for faculty positions (Assistant/Associate/Full Professor) in Computer Science. The position will be housed in the Department of Computer Science in the School of Computer Science and Mathematics. KIMEP University is Kazakhstan and Central Asia's most prestigious and dynamic university, serving approximately 3000 students in a variety of undergraduate and graduate degree programs. The Department of Computer Science houses the Bachelor of Science in Computer Science and the Bachelor of Information Systems degree programs.
Qualifications
Applicants must have earned a PhD in computer science or a related discipline from an accredited institution and a minimum of three years of teaching experience. Student teaching counts towards this requirement.
KIMEP University
KIMEP University is Central Asia's leading American-style, internationally accredited, English-language academic institution. The university provides a world-class academic experience and a unique international environment to all its students and faculty. All academic programs are ranked among the top in Kazakhstan.
Almaty, Kazakhstan
The city of Almaty is a beautiful, modern, and vibrant city situated at the base of the majestic Tien Shan Mountains in Southeast Kazakhstan. With a population of 2 million people, it is the financial and cultural capital of Kazakhstan. Kazakhstan is located in Eurasia's heart, with important commercial inroads bridging Asia and Europe. Its dynamically changing economic, social, educational, and cultural environment provides incredible opportunities for significant and original research.
Compensation
Rank and salary are competitive and commensurate with experience and qualifications. Compensation after-tax compares favorably with net salaries in Western countries. Combined with a low cost of living, the salary becomes even more competitive in real terms.
Limited on-campus housing is available to rent. In addition to salary, a benefits package includes basic healthcare, reduced tuition rates for KIMEP courses, and a relocation allowance subsidy. Summer paid teaching is typically available. The salary will be subject to a deduction of 10% income tax.
Application Process
Please submit the following documents to the KIMEP University HR portal: https://hr.kimep.kz/en-US/Home/Vacancy/60
Address any questions to recruitment@kimep.kz
Closing dates for submission of applications: June 15th, 2024
Applications will be evaluated on an ongoing basis and will continue until the position is filled. Only shortlisted candidates will be informed and invited for interviews by the search committee.
Read more from the original source:
Nebraska firm recommended to manage computer science ed stipends – The Union Leader
State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington Washington D.C. West Virginia Wisconsin Wyoming Puerto Rico US Virgin Islands Armed Forces Americas Armed Forces Pacific Armed Forces Europe Northern Mariana Islands Marshall Islands American Samoa Federated States of Micronesia Guam Palau Alberta, Canada British Columbia, Canada Manitoba, Canada New Brunswick, Canada Newfoundland, Canada Nova Scotia, Canada Northwest Territories, Canada Nunavut, Canada Ontario, Canada Prince Edward Island, Canada Quebec, Canada Saskatchewan, Canada Yukon Territory, Canada
Zip Code
Country United States of America US Virgin Islands United States Minor Outlying Islands Canada Mexico, United Mexican States Bahamas, Commonwealth of the Cuba, Republic of Dominican Republic Haiti, Republic of Jamaica Afghanistan Albania, People's Socialist Republic of Algeria, People's Democratic Republic of American Samoa Andorra, Principality of Angola, Republic of Anguilla Antarctica (the territory South of 60 deg S) Antigua and Barbuda Argentina, Argentine Republic Armenia Aruba Australia, Commonwealth of Austria, Republic of Azerbaijan, Republic of Bahrain, Kingdom of Bangladesh, People's Republic of Barbados Belarus Belgium, Kingdom of Belize Benin, People's Republic of Bermuda Bhutan, Kingdom of Bolivia, Republic of Bosnia and Herzegovina Botswana, Republic of Bouvet Island (Bouvetoya) Brazil, Federative Republic of British Indian Ocean Territory (Chagos Archipelago) British Virgin Islands Brunei Darussalam Bulgaria, People's Republic of Burkina Faso Burundi, Republic of Cambodia, Kingdom of Cameroon, United Republic of Cape Verde, Republic of Cayman Islands Central African Republic Chad, Republic of Chile, Republic of China, People's Republic of Christmas Island Cocos (Keeling) Islands Colombia, Republic of Comoros, Union of the Congo, Democratic Republic of Congo, People's Republic of Cook Islands Costa Rica, Republic of Cote D'Ivoire, Ivory Coast, Republic of the Cyprus, Republic of Czech Republic Denmark, Kingdom of Djibouti, Republic of Dominica, Commonwealth of Ecuador, Republic of Egypt, Arab Republic of El Salvador, Republic of Equatorial Guinea, Republic of Eritrea Estonia Ethiopia Faeroe Islands Falkland Islands (Malvinas) Fiji, Republic of the Fiji Islands Finland, Republic of France, French Republic French Guiana French Polynesia French Southern Territories Gabon, Gabonese Republic Gambia, Republic of the Georgia Germany Ghana, Republic of Gibraltar Greece, Hellenic Republic Greenland Grenada Guadaloupe Guam Guatemala, Republic of Guinea, Revolutionary People's Rep'c of Guinea-Bissau, Republic of Guyana, Republic of Heard and McDonald Islands Holy See (Vatican City State) Honduras, Republic of Hong Kong, Special Administrative Region of China Hrvatska (Croatia) Hungary, Hungarian People's Republic Iceland, Republic of India, Republic of Indonesia, Republic of Iran, Islamic Republic of Iraq, Republic of Ireland Israel, State of Italy, Italian Republic Japan Jordan, Hashemite Kingdom of Kazakhstan, Republic of Kenya, Republic of Kiribati, Republic of Korea, Democratic People's Republic of Korea, Republic of Kuwait, State of Kyrgyz Republic Lao People's Democratic Republic Latvia Lebanon, Lebanese Republic Lesotho, Kingdom of Liberia, Republic of Libyan Arab Jamahiriya Liechtenstein, Principality of Lithuania Luxembourg, Grand Duchy of Macao, Special Administrative Region of China Macedonia, the former Yugoslav Republic of Madagascar, Republic of Malawi, Republic of Malaysia Maldives, Republic of Mali, Republic of Malta, Republic of Marshall Islands Martinique Mauritania, Islamic Republic of Mauritius Mayotte Micronesia, Federated States of Moldova, Republic of Monaco, Principality of Mongolia, Mongolian People's Republic Montserrat Morocco, Kingdom of Mozambique, People's Republic of Myanmar Namibia Nauru, Republic of Nepal, Kingdom of Netherlands Antilles Netherlands, Kingdom of the New Caledonia New Zealand Nicaragua, Republic of Niger, Republic of the Nigeria, Federal Republic of Niue, Republic of Norfolk Island Northern Mariana Islands Norway, Kingdom of Oman, Sultanate of Pakistan, Islamic Republic of Palau Palestinian Territory, Occupied Panama, Republic of Papua New Guinea Paraguay, Republic of Peru, Republic of Philippines, Republic of the Pitcairn Island Poland, Polish People's Republic Portugal, Portuguese Republic Puerto Rico Qatar, State of Reunion Romania, Socialist Republic of Russian Federation Rwanda, Rwandese Republic Samoa, Independent State of San Marino, Republic of Sao Tome and Principe, Democratic Republic of Saudi Arabia, Kingdom of Senegal, Republic of Serbia and Montenegro Seychelles, Republic of Sierra Leone, Republic of Singapore, Republic of Slovakia (Slovak Republic) Slovenia Solomon Islands Somalia, Somali Republic South Africa, Republic of South Georgia and the South Sandwich Islands Spain, Spanish State Sri Lanka, Democratic Socialist Republic of St. Helena St. Kitts and Nevis St. Lucia St. Pierre and Miquelon St. Vincent and the Grenadines Sudan, Democratic Republic of the Suriname, Republic of Svalbard & Jan Mayen Islands Swaziland, Kingdom of Sweden, Kingdom of Switzerland, Swiss Confederation Syrian Arab Republic Taiwan, Province of China Tajikistan Tanzania, United Republic of Thailand, Kingdom of Timor-Leste, Democratic Republic of Togo, Togolese Republic Tokelau (Tokelau Islands) Tonga, Kingdom of Trinidad and Tobago, Republic of Tunisia, Republic of Turkey, Republic of Turkmenistan Turks and Caicos Islands Tuvalu Uganda, Republic of Ukraine United Arab Emirates United Kingdom of Great Britain & N. Ireland Uruguay, Eastern Republic of Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Viet Nam, Socialist Republic of Wallis and Futuna Islands Western Sahara Yemen Zambia, Republic of Zimbabwe
See the rest here:
Nebraska firm recommended to manage computer science ed stipends - The Union Leader
Detecting weeds using robotsand a cloud | Rowan Today | Rowan University – Rowan Today
Shen-Shyang Ho, Ph.D.
Computer scientist
Data mining, artificial intelligence, machine learning
Shen-Shyang Ho, Ph.D., likes to solve new problems. His work in computer science over the last 20 years has ranged from studying image data for anomalies in the manufacturing sector to analyzing satellite data tracking cyclones and hurricanes at NASAs Jet Propulsion Laboratory.
To me, the easiest problem to solve is an open one because theres no definitive answer, Ho says. No one has come up with an optimal solution yet.
Supported by the National Science Foundation and in collaboration with researchers at Stony Brook, Temple and Kettering universities, Hos lab conducts research to enable remote vehicles to make decisions efficiently. The method relies on a machine learning concept called cooperative inference.
In this solution, the deep learning model is split into two parts: one on a remote vehicle, such as a cell phone, drone or robot and the rest on a server or cloud. Powered by a limited energy source, such as a battery, the vehicle makes decisions with help from a cloud powered by a steady source of energy and minimal communication between the remote vehicle and server.
With Rowan mechanical engineering alumnus Paolo Rommel Sanchez, Ph.D., now a professor at the University of the Philippines Los Baos, Ho is testing a scenario involving precision agriculture, a farming method that uses technology to improve production results through targeted interventions.
The test uses a field robot to recognize weeds in a field of growing produce. Once weeds are identified via cooperative inference, the robot sprays herbicide on the weeds, not the crops.
More research is needed to optimize both the machine learning model (weed detection), as well as the amount of energy and time it takes for the robot to transmit and receive information from the field to the cloud where the more computationally expensive processes are executed.
The robot is far awayit is a battery-driven robot, explains Ho. We have to make sure that it can last long enough in the field. I think precision agriculture is a very realistic application for this AI technology because the robot is moving slowly, making decisions.
Additionally, Ho adds, robots handle chemicals. There is a benefit to the health of the farmer, he says. Let the robots do the dangerous stuff.
Rowan University researchers are passionate about what they do. Find more at Meet Our Researchers.
Follow this link:
Detecting weeds using robotsand a cloud | Rowan Today | Rowan University - Rowan Today
Assistant professor in computer science and software engineering elevated to Senior Member status by IEEE – Auburn Engineering
Sathyanarayanan Sathya Aakur, an assistant professor in the Department of Computer Science and Software Engineering (CSSE), has been elevated to Institute of Electrical and Electronics Engineers (IEEE) Senior Member.
This is an exclusive level achieved by only about 10 percent of IEEEs more than 450,000 members, said CSSE Chair Hari Narayanan. Earning this level is the highest professional grade of IEEE and requires extensive experience and reflects professional accomplishment and maturity.
Senior members are chosen based on professional service, leadership and significant contributions to the field and research. Aakur, who has served as an area chair and associate editor with several IEEE conferences and journals for the past five years, focuses his research interests on computer vision, natural language processing and visual understanding.
A 2022 National Science Foundation CAREER Award winner, Aakurs recent works were accepted at the IEEEs International Symposium on Biomedical Imaging and in the Journal of Biomedical and Health Informatics.
Im extremely honored to be elevated to senior member, said Aakur, who joined the Auburn Engineering faculty in Fall 2023. Researchers need to be IEEE senior members for five years to apply for IEEE fellowship positions the highest honor IEEE awards.
Earning this distinction opens further opportunities within the IEEE for me. I have been involved in organizing conferences, recently co-chaired the demo track at the Conference on Computer Vision and Pattern Recognition 2024. Being a senior member will allow me to explore leadership opportunities within IEEE and help Auburn continue to develop a culture of research and education in computer science.
Aakurs expertise in video understanding and computer vision for robotics comes in very handy, leading to publications and service in the computer vision and artificial intelligence research communities giving him the experience and prestige deserving of the IEEE senior member distinction.
We typically receive thousands of submissions to a conference, the 'around 30' papers that fall under my area are assigned to me and it's my job to make sure that each of these papers receive a fair peer review from at least three people, he said. Then I make recommendations to the program chairs, who administer the conference about the decisions on the papers that are in my batch with justification based on reviewer comments and intensive discussions.
Aakur encourages faculty peers to pursue opportunities within professional organizations. Why? Their work will be noticed.
Every day, dozens of new papers come out, he said. No matter how talented we are as researchers, our work gets lost in that. But these professional memberships allow us to showcase our work and bring more visibility to the department and the university.
Go here to read the rest:
From computer science to the alpine botanical garden – greenpeace.org
Growing up in Chinas southwestern Yunnan province, Haixian studied computer science in the early 2000s, but ended up working at the Shangri-La Alpine Botanical Garden after graduation. Speaking to researchers from Greenpeace East Asias Beijing office, she reflects on 20 years monitoring and restoring high-altitude biodiversity in the Hengduan Mountain range.
The hour-plus long interview has been edited for brevity.
Greenpeace: Why did you choose to work there? Why not a more typical job like in a factory?
Haixian: There are pretty much no factories here, and only a few service sector jobs, like hotels or restaurants. So there was an opportunity at the botanical garden, is all. There was no particular reason. Actually at the time I wasnt too familiar with the botanical garden. It was just another job.
Greenpeace: I know youre Nakhi [a minority nationality community of Indigenous People in the Hengduan Mountains]. Do Nakhi people have customs or traditions in forestry or botany?
Haixian: No special traditions. The older generations way of life was farming. My father was not Nakhi he is from Xinjiang. My mother is a real Nakhi. And I am Nakhi, but I dont know much about the specifics of Nakhi culture or customs. I am somewhat sinicized, and I cant read Naxi-Dongba characters, and I havent bothered to learn them.
GreenpeaceHow did you develop your skills in recognizing plant types?
Haixian: As of 2024 Ive been doing this for 20 years. Actually, I really have zero foundation. First I learned to identify the specimens we take. But really you cant identify plant type by using specimens, because the characteristics in shape and color change when the plant dries out. Due to the lack of equipment, we cant do identification by molecular testing. So we can only use the plants morphology. Studying this need to incorporate field work more. In field surveys, you see reds and greens that after drying will change. Even flowers will change color. So field survey and specimen identification need to be synchronized.
Greenpeace: You seem to enjoy it.
Haixian: Yes I really do. Otherwise I wouldnt have kept up with it for 20 years.
Greenpeace: When do you feel most happy doing this?
Haixian: Id rather be in the field, going out into the wilderness. Before I had children, I loved just going off into the countryside. When I was single, I didnt need to care about much and I was in good shape. Now Ive got to watch the kids. So thats that.
Greenpeace: Why do you like going into the wilderness? Its quite tiring for a lot of people, who maybe feel indoor work is more suitable.
Haixian: If youre physically exhausted, you can get over it with some rest. If youre in an office writing materials all day long, and cant get it done in a few hours, then what you need isnt rest. Field work is tough, and for physical labor you just need to rest to get better. Plus, you can travel around for free and see the scenery. Still, when its tough it is tough. If it rains or snows, or sometimes I still get lightheaded when the mountains are above 5,000 meters.
Greenpeace: When you do surveys, do you go by yourself? Or do some colleagues go with you?
Haixian: We have a team. Usually no less than 4 people. Two men and two women, which makes booking accommodation more convenient. Over the the last few years, the longest trip was a scientific expedition to the Qinghai-Tibet Plateau, going to Tibet and Sichuan for about 20 days. But the conditions were good. We didnt have to camp out in the field. When we work in northwest Yunnan, we have to camp. Weve been doing that program for about 20 years, since 2005 when I was new. We go up to 4,000 meters above sea level and need to stay in the mountains. There are three to four peaks at each site and we need to monitor the peaks and the plantlife there. We stay for five to six days.
Greenpeace: What is the significance of your restoration work?
Haixian: My work is quite crucial for ecological restoration. You first have to look at all the types of vegetation around the area, and see what plants are suitable for the area. People assume you can just bring in seedlings from outside, move them in, plant them, and watch them grow. But you have to restore it to a state close to original vegetation, but of course it wont be exactly the same. After surveying what is most suitable, we go back and pick seeds of fast-growing plants and sow them to first fix the soil. Pioneer plants grow fast and cover large areas.
Greenpeace: Can you give an example of a plant used for ecological restoration??
Haixian: Plants are sensitive to the altitude and the region. Restoration work will differ along with different altitudes and in different areas. There are two or three species that are quite good, but the main one is Evergreen laburnum (Piptanthus nepalensis, also known as Nepal laburnum). This species is suited to altitudes between 2,500 and 4,000 meters. Its evergreen and its leguminous, so its roots have a nitrogen-fixing effect on the soil. Its a shrub, so its fast-growing. So its a good candidate for seeding.
Greenpeace: Can you tell me about a time you encountered a more difficult restoration project?
Haixian: Ecological restoration at high altitudes is difficult, mainly due to environmental and climatic factors. The soil is not very good, and most areas are sand and gravel. Passion can overcome all these obstacles. Even if they cant pay our salaries, we persist.
Greenpeace: Whats the reason? Ive heard from Director Fang that in the early years, the botanical garden owed a lot of money and couldnt pay salaries.
Haixian: In 2008 or 2009, we didnt get wages for about eight months. I cant say I didnt think about quitting. But love is the main reason that I stuck with it. It is much better now. 15 years ago, there was so much construction, and I was doing more biodiversity surveys and environmental impact assessments. After 15 years, the construction is done, and now we definitely need more restoration work. In the early stage we do survey work for as commissioned by companies and the funding isnt much. Now that were doing the restoration theres more funding. The government now also attaches great importance to biodiversity. So in the past few years we have quite a lot of biodiversity survey projects.
Greenpeace: Can you share a project youre particularly proud of?
Haixian: The book Bare Land Vegetation Restoration Research in Northwest Yunnan. Not that I particularly felt fulfilled by publishing the book. But seeing it through from start to finish was fulfilling. I was involved in the initial botanical survey, the assessment of the restoration areas, and various investigations all the way until this book came out. The book started in 08 or 09 to survey the pioneer plants in northwest Yunnan.
Greenpeace: After working in the botanical gardens for many years, how has working on ecological restoration improved or tempered or changed you personally?
Haixian: Quite a big change. When I started doing it before, I felt it was an ordinary thing. But it doesnt feel ordinary, doing it. In the past I imagined like most that Id restore the slope, plant what looks good, you know, whatever to make the slope green. Looking back, I used to be so naive, even a little ridiculous. You have to do things in a professional way.
Greenpeace: And what are the differences between men and women when it comes to restoration work? What particular advantages do you think women have?
Haixian: Attentiveness in observation. Theres a lot of physical labor in ecological restoration, and then a lot of things that appear insignificant but are actually essential. When doing surveys, you have to see what species are growing and looking good. When monitoring, you have to look at both the data and the growth of the plants themselves.
Notes:
Read the rest here:
From computer science to the alpine botanical garden - greenpeace.org