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SalsaBot

The SalsaBot team consists of talented students from Ohio State University.

By Ohio State University
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Just as the name says, the team strives to build a robot that is great companion to everything and everyone. Equipped with state-of-the-art technologies from natural language processing, computer vision, and human-machine interaction, SalsaBot will assist humans to achieve more while also continuously improving itself along the way.

osu_salsabot_teamimage.jpg
Location: Columbus, Ohio
Faculty advisor: Yu Su

Chan Hee (Luke) S. — Team leader

Chan Hee is a 2nd year CS PhD student advised by Professor Yu Su in the Ohio State University. His current work focuses on developing a method for efficient and accurate completion of a long-horizon vision and language tasks. He is broadly interested in knowledge base construction/reasoning and vision-and-language navigation. Before his PhD, Chan Hee has graduated with a Bachelor of Computer Science from University of Notre Dame and has worked as a research intern in Johns Hopkins University HLTCOE.

Goonmeet B.

Goonmeet is a Computer Science and Engineering PhD student advised by Srinivasan Parthasarathy. She has been working on knowledge gap identification, detection, and resolution in Visual Question Answering (VQA) Systems and information extraction with publications at CVPR, topiCS, and PLOS One. She has interned at Nokia Bell Labs and National Library of Medicine.

Sean C.

Sean is a Ph.D. student in the Department of Computer Science and Engineering at OSU, working with Dr. Srinivasan Parthasarathy as my advisor. He completed his B.S. at the University of Arizona in May 2020 as a double major in Mathematics and Information Science and Technology. His current research focuses on machine learning applications for fluid mechanics, fair graph embedding learning, and knowledge gap detection, identification, and resolution for VQA models. His general research interests revolve around methods of incorporating prior information, knowledge, and constraints into machine learning architectures and AI systems.

Jihyung K.

Jiyhung is a Ph.D. student in the Department of Computer Science and Engineering at the Ohio State University, advised by Wei-Lun (Harry) Chao. Jiyhung is broadly interested in machine learning and its applications to Computer Vision and Natural Language Processing. Recently, Jiyhung has focused on Vision and Language, especially for Visual Question Answering, Zero-Shot Learning, and Vision Language Navigation.

Vardaan P.

Vardaan is a third year Ph.D. student in CSE at The Ohio State University. Vardaan's research focus is on knowledge base reasoning, graph representation learning and natural language processing. For this project, Vardaan will be working on knowledge bases, neuro-symbolic reasoning, and the state representation. Vardaan is also interested in scaling machine learning models to large-scale datasets.

Samuel S.

Sam is a first-year PhD student studying natural language processing under Dr Yu Su at the Ohio State University. He has experience interpreting pre-trained language models and semantic parsing, and extensive industry experience, with internships at GE Aviation, Microsoft and SpaceX.

Yu Su — Faculty advisor

Yu Su is an assistant professor in the Department of Computer Science and Engineering at the Ohio State University. Before coming to OSU, he was Senior Researcher at Microsoft Semantic Machines working on conversational AI. He got his PhD from University of California, Santa Barbara and his bachelor degree from Tsinghua University, both in Computer Science.

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Applied Scientist
ZA, Cape Town
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. We are a new team in AWS' Kumo organisation - a combination of software engineers and AI/ML experts. Kumo is the software engineering organization that scales AWS’s support capabilities. Amazon’s mission is to be earth’s most customer-centric company and this also applies when it comes to helping our own Amazon employees with their everyday IT Support needs. Our team is innovating for the Amazonian, making the interaction with IT Support as smooth as possible. We achieve this through multiple mechanisms which eliminate root causes altogether, automate issue resolution or point customers towards the optimal troubleshooting steps for their situation. We deliver the support solutions plus the end-user content with instructions to help them self-serve. 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US, NY, New York
The Automated Reasoning Group in AWS AI is looking for an Applied Scientist who will work on integrating automated reasoning and AI. You will work on capturing the semantics of various domains using mathematical logic, automating this apply it at scale. You will apply your knowledge to propose solutions, create software prototypes, and move prototypes into production systems using modern software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You will use your strong verbal and written communication skills, are self-driven and own the delivery of high quality results in a fast-paced environment. As an Applied Scientist in AWS AI, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of product features from beginning to end. You will: - Define and implement new applications of mathematical logic and logic solvers to develop accurate and scalable AI solutions to difficult problems. - Apply software engineering best practices to ensure a high standard of quality for all team deliverables - Work in an agile, startup-like development environment, where you are always working on the most important stuff - Deliver high-quality scientific artifacts - Work with the team to define new interfaces that lower the barrier of adoption for automated reasoning solvers - Work with the team to help drive business decisions Learn and Be Curious. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members. Inclusion and Diversity. Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more. Key job responsibilities Work closely with internal and external users on defining and extending application domains for integrated use of automated reasoning and AI. Automate the generation of semantic models in mathematical logic. About the team The automated reasoning group in AI is a diverse group of scientists and engineers innovating in this exciting new area. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Applied Scientist - Perception, Amazon Robotics
US, WA, Seattle
We are seeking an Applied Scientist to develop innovative perception and machine learning solutions for robot workcells in Amazon Fulfillment centers. In this role, you will leverage advanced sensor technologies to develop and implement state-of-the art ML models to for scene understanding and objection localization. Your solutions will allow Amazon to increase productivity and efficiency while prioritizing employee safety. Key job responsibilities - Design and implement advanced machine learning models for perception tasks such as object detection and scene understanding - Optimize and deploy the ML models on edge devices - Build and test prototype robotic workcell setups to validate the performance of the solution - Work with cross-functional teams to provide inputs and recommendations for the optimal sensor suite to enable a robust solution - Collaborate with Amazon's robotics engineering and operations teams to understand their requirements and develop tailored solutions - Document the architecture, performance, and validation of the final system A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
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