CASPR

Our vision is to build a socialbot that can really “understand” the conversation as well as the context in which the conversation is being carried out, just like humans do.

University of Texas at Dallas - Caspr.jpg
Location: Dallas, TX, USA
Faculty advisor: Gopal Gupta

Our team CASPR, consisting of computer science Ph.D. and master’s students from The University of Texas at Dallas, brings together the experiences in question-answering, conversational agents, commonsense reasoning, logic programming, and deep learning. Our vision is to build a socialbot that can really “understand” the conversation as well as the context in which the conversation is being carried out, just like humans do. The novelty of our approach is that our work mostly relies on automated commonsense reasoning. To achieve human intelligence that includes learning and reasoning, we believe that ML and commonsense reasoning should work in tandem.

Kinjal B. - Team leader

Kinjal is a computer science PhD student working under Prof. Gopal Gupta on closed domain question-answering and commonsensereasoning. His research interest lies in Logic Programming, Natural Language Understanding and Machine Learning, and my recent papers are in the area of textual and visual question answering. Kinjal also gathered real world data science project experience while working as an intern at Intuit.During his Bachelor's in Information Technology, he worked on several NLP projects (e.g. Text Similarity) and also interned at IIT Kharagpur for NLP research. Kinjal looks forward to contributing to the team with his knowledge and experience.

Huaduo W.

Huaduo is a computer engineering PhD student in ALPS lab led by Prof. Gopal Gupta. Her current research focuses on visual and textual based QA, commonsense reasoning. Huaduo's research interest lies in logic programming, natural language processing, and understanding. Her past work and research experience were about computer systems and infrastructure systems. In her last master's, she worked on a system kernel project for my research and interned as a backend SDE at Baidu. After that, she worked as a project manager of several infrastructure systems in China CITIC bank for 3 years.

Fang L.

Fang is a Computer Science PhD candidate under Dr. Gopal Gupta. Fang's research interests are explainable AI, commonsense reasoning, answer set programming, logic programming. Fang got their Master' in Applied Mathematics & Computer Science and graduated with honor from University of Central Oklahoma. In the past few years, they got hands-on experiences on researches such as human computer interaction, IoT, autonomous vehicle, AI planning, answer set programming solver, etc. Fang has been an instructor of Programming Languages course at UTD. They participated in LOVE'S ENTREPRENEUR'S CUP (2017) as the cofounder (CTO) of company Turning Systems and won the third place prize.

Sarat Chandra V.

Sarat Chandra is a PhD student in the CS Department at UT Dallas. Sarat Chandra's research work involves automatically synthesizing concurrent programs using commonsense knowledge about concurrency. Given a sequential program for a pointer data structure (e.g., insert a node, delete a node), the goal of this research is to automatically synthesize its concurrent version, just like a human would. To accomplish this, we need to have knowledge to model concurrency, shared memory, and how pointer data structures behave. All this knowledge is represented as axioms in answer set programming and reasoning performed in the s(CASP) system to synthesize the concurrent program.

Nancy D.

Nancy is a student at UTD working towards a Master's in Computer Science with a focus on Intelligent Systems and Data Science. Nancy started developing Alexa skills in 2018 while working as a research assistant for a professor at the school of Arts & Humanities and has since published two Alexa skills. Outside of school, Nancy enjoys playing Pokemon Go and spending time with her family and pets.

Xiangci L.

Xiangci is a first year Ph.D. student at UT Dallas. His research interest is natural language processing, particularly scientific document information extraction and summarization. He obtained his master’s degree from University of Southern California in computer science, and bachelor’s degree from New York University Shanghai in computer science and neuroscience. He has industry experiences at Baidu USA and Chan Zuckerburg Initiative, as well as a year of neuroscience research experience. He has a few publications on natural language processing.

Nancy D.

I’m a student at UTD working towards my Master's in Computer Science with a focus on Intelligent Systems and Data Science. I started developing Alexa skills in 2018 while I was working as a research assistant for a professor at the school of Arts & Humanities and since have published two Alexa skills. Outside of school, I enjoy playing PokemonGo and spending time with my family & pets.

Gopal Gupta - Faculty advisor

Gopal Gupta has been a faculty member in computer science since 1992 (currently hold the Erik Jonsson endowed chair). All his degrees are in computer science (BS CS from IIT Kanpur, MS & PhD from UNC Chapel Hill). His research over his whole career is focused on building practical automated reasoning and logic programming systems. For the last 5 years, his group has extensively researched automating commonsense reasoning--key to building chatbots that can respond by "understanding" humans. Have published more than 160 papers, founded 2 companies, and built many practical software systems related to automated reasoning, many of which are available publicly through Gopal's homepage.

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US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.