Amazon and Virginia Tech Collaborate: Fellowship Opportunities and Exciting Faculty Research Grants Revealed
Introduction:
In October of last year, Amazon and Virginia Tech announced the first group of fellowship and faculty award recipients for their joint initiative focused on efficient and robust machine learning. Now, they have revealed the new class of academic fellows and faculty research award recipients for the 2023–2024 academic year.
Full News:
**Amazon and Virginia Tech Announce Next Class of Fellows and Faculty for Machine Learning Initiative**
In an exciting collaboration, Amazon and Virginia Tech have revealed the recipients of the 2023–2024 class of academic fellows and faculty research awards as part of their joint initiative for efficient and robust machine learning. The partnership, established in March of 2022, aims to support research efforts led by Virginia Tech faculty and provide opportunities for doctoral students in the College of Engineering to apply for Amazon fellowships.
The initiative has already seen significant progress and impactful research since its inception last year. Amazon’s Reza Ghanadan expressed his appreciation for Virginia Tech’s commitment to excellence in both research and education. He looks forward to continued collaborations with the esteemed faculty and students to advance their shared goal of ensuring the robustness of machine learning systems while creating impactful AI applications in various domains.
Naren Ramakrishnan, the director of the Amazon–Virginia Tech initiative, emphasized the importance of finding solutions to industry-focused problems using machine learning applications. As they move into their second year, they plan to expand into additional areas such as robust large-language-model deployment, combining large language models with reasoning capabilities, and multimodal interfaces.
The 2023–2024 class of fellows and faculty members will receive funding to conduct research projects across multiple disciplines at Virginia Tech. Let’s meet the recipients and learn about their areas of research.
**Academic Fellows: Advancing Machine Learning Knowledge**
Minsu Kim, a PhD candidate in electrical and computer engineering, is studying under the guidance of Professor Walid Saad. Kim’s current research focus is on building green, sustainable, and robust federated-learning solutions. This research aims to benefit AI-embedded products that utilize federated learning and wireless communications. Kim’s work encompasses various aspects of the federated-learning algorithm lifecycle, including data acquisition, algorithm and model design, training, and inference/retraining.
Ying Shen is another PhD candidate, pursuing a degree in computer science at Virginia Tech. Under the supervision of Assistant Professors Lifu Huang and Ismini Lourentzou, Shen is passionate about natural-language processing (NLP) and multimodal messages. Shen aims to develop more human-like interactive agents that have a better understanding, interpretation, and reasoning capability about the world around us.
**Faculty Research Award Recipients: Advancing Machine Learning Techniques**
Lifu Huang, an assistant professor in the department of computer science, is working on a project titled “Semi-parametric open domain conversation generation and evaluation with multidimensional judgments from instruction tuning.” His objective is twofold: first, to develop an innovative conversational framework that augments a large conversation generation model with a large collection of information sources, improving the adaptivity and scalability of conversational agents towards open domain topics. Secondly, Huang aims to simulate fine-grained human judgments on machine-generated responses to train a lightweight multi-dimensional conversation evaluator or provide feedback to conversation generation.
Ruoxi Jia, assistant professor in the department of electrical and computer engineering, is leading the project “Cutting to the chase: Strategic data acquisition and pruning for efficient and robust machine learning.” This project focuses on developing strategic data acquisition and pruning techniques to enhance training efficiency and address robustness against sub-optimal data quality. The goal is to optimize the data-for-AI pipeline, accelerating the development of accurate and responsible machine learning models across various applications.
Ming Jin, an assistant professor, aims to address the challenges of designing safe and aligned interactive systems through his project, “Safe reinforcement learning for interactive systems with stakeholder alignment.” This research will develop a novel framework for stakeholder alignment using reinforcement learning and game theory. The outcomes will have important implications for a range of applications, particularly in the realm of recommender systems.
Ismini Lourentzou, assistant professor in the department of computer science, is working on “Diffusion-based scene-graph enabled embodied AI agents.” The objective is to design embodied AI agents capable of tracking long-term changes in the environment and modeling how physical attributes of objects transform in response to agents’ actions. This project aims to enhance the agents’ ability to interact with the world in a natural and responsive manner.
Xuan Wang, assistant professor in the department of computer science, is researching “Fact-checking in open-domain dialogue generation through self-talk.” With growing concerns about the accuracy of information provided by open-domain dialogue generation systems, Wang’s project proposes a new fact-checking approach using language-model-based self-talk. This approach aims to automatically validate generated responses and provide supporting evidence, particularly in critical domains such as healthcare and finance.
The collaboration between Amazon and Virginia Tech continues to push the boundaries of machine learning research. The recipients of the fellowship and faculty awards for the 2023–2024 class will undoubtedly make significant contributions to the field. With their diverse areas of research, they are poised to advance the understanding and application of efficient and robust machine learning techniques.
Conclusion:
Amazon and Virginia Tech have announced the recipients of the 2023-2024 class of academic fellows and faculty research awards as part of their joint initiative for efficient and robust machine learning. The initiative, launched in 2022, aims to support research efforts led by Virginia Tech faculty members and provide opportunities for doctoral students in AI and ML research. The selected fellows and faculty members will receive funding to conduct research projects across various disciplines at Virginia Tech.
Frequently Asked Questions:
1. What are the Amazon fellowships and faculty research awards announced by Virginia Tech?
Virginia Tech has partnered with Amazon to offer fellowships and faculty research awards. These programs aim to promote collaboration between researchers at Virginia Tech and Amazon experts. The fellowships provide financial support to graduate students, while the faculty research awards fund innovative research projects led by Virginia Tech faculty members.
2. How can graduate students benefit from Amazon fellowships?
Amazon fellowships provide financial support to graduate students at Virginia Tech, allowing them to focus on their research and academic pursuits. These funds can cover tuition fees, living expenses, and research costs, relieving students of some financial burden and enabling them to devote more time to their studies and research.
3. Who is eligible to apply for Amazon fellowships?
Graduate students enrolled at Virginia Tech are eligible to apply for Amazon fellowships. Each fellowship may have specific criteria, such as the area of study or research focus, so it’s essential to review the fellowship requirements before applying.
4. How can Virginia Tech faculty members benefit from the faculty research awards?
The faculty research awards provided by Amazon offer faculty members at Virginia Tech an opportunity to secure funding for their innovative research projects. These awards can support various research expenses, such as equipment, materials, travel, and collaborations, advancing the faculty members’ research and contributing to their academic success.
5. Can faculty members from any department apply for faculty research awards?
Yes, faculty members from any department at Virginia Tech are eligible to apply for faculty research awards. Whether they are from engineering, social sciences, or any other field, as long as their research proposal aligns with the program’s guidelines, they can submit an application.
6. How can these programs foster collaboration between Virginia Tech and Amazon?
The Amazon fellowships and faculty research awards aim to foster collaboration between Virginia Tech and Amazon by bringing together researchers from both institutions. The programs encourage knowledge exchange, joint research initiatives, and mentorship opportunities, strengthening the partnership and leveraging the expertise of both organizations.
7. Are there any obligations or commitments for fellowship recipients or faculty research award recipients?
While specific obligations may vary depending on the fellowship or research award, recipients are generally expected to be actively engaged in their research and maintain satisfactory academic progress. Fellowship recipients may also be required to participate in relevant events or programs organized by Virginia Tech and Amazon to share their research findings or contribute to the academic community.
8. How can the Amazon fellowships and faculty research awards contribute to the academic reputation of Virginia Tech?
The Amazon fellowships and faculty research awards provide Virginia Tech students and faculty members with a remarkable opportunity to collaborate with a highly recognized industry leader. Such partnerships elevate the university’s reputation, attract talented individuals, and reinforce its position as a hub for innovative research and academic excellence.
9. What is the application process for Amazon fellowships and faculty research awards?
The application process for both Amazon fellowships and faculty research awards generally involves submitting a research proposal or application form that outlines the objectives and methodology of the proposed research. Additionally, applicants may need to provide supporting documents, such as academic transcripts, letters of recommendation, or a detailed budget for the research project.
10. How can I stay updated on future opportunities and announcements regarding Amazon and Virginia Tech collaborations?
To stay updated on future opportunities and announcements related to Amazon and Virginia Tech collaborations, it is advisable to regularly visit the official websites of both institutions. Additionally, subscribing to their newsletters or following their social media accounts can ensure you receive timely updates and information regarding upcoming programs, fellowships, or research opportunities.
