We envision the new generation of chatbots to be self-learnable through interaction with customers. The self-learning ability can be specified as the clarifying ability, the inference capability, and the self-adaptation ability. For the clarifying ability, we will train the chatbot to ask clarifying or follow-up questions if there is confusion or uncertainty during the conversation flow, just like how humans try to solve new problems. For the inference capability, when we ask the chatbot some health or finance suggestions or let it make planning for some tasks, we not only want the answer but also need the explanation for that decision and suggestion. To achieve this goal, we will introduce explanations into our chatbot system.
Yu Yu - Team leader
Yu is a PhD at Stevens Institute of Technology under the supervision of prof. Jia Xu. Yu's research interest lies in robustness and generalization of natural language processing, with a focus on machine translation and dialogue generation. Yu has experience in sentiment analysis, named entity recognition and language modeling tasks, and has published two papers in COLING about robustness and data selection for generalization using reinforcement learning.
Girish Budhrani
Budhrani is a master student in computer science. Budhrani appreciates applying his knowledge to the fascinating technical advancements that take place at Stevens Institute of Technology every day, and has previously competed in a WMT 22 competition won. Budhrani received his bachelor's degree from K.C. College in India.
Preet Jhanglani
Jhanglani is a masters student in computer science at Stevens Institute of Technology. Jhanglani has an interest towards data science and machine learning, and is currently learning image processing. He has experience in data science and machine learning from an internship, and has used this experience to contribute towards the WMT 22 competition representing Stevens.
Hrishikesh Kanade
Kanade is an inventor and engineer with experience in electronics, robotics, software development and machine learning. He has won multiple electronics and robotics competitions and was a finalist in Texas Instruments India Innovation Challenge 2015 and a quarter finalist in the same competition in 2016. He is an expert advisor on the Texas Instruments Expert Advisory panel. He has patent grants in India and the US. He's currently a member of the SIT NMT team, which won a shared subtask in WMT 2022 machine translation competition. Kanade has in-depth knowledge of data acquisition systems having worked with Larsen and Toubro and Mindtree Ltd for 2.5 years on internet of things projects.
Md Kowsher
Kowsher is a second-year PhD student at Stevens Institute of Technology. He has the ambition to participate in higher learning by taking part in various research works and also by involving practical & theoretical education for increasing my knowledge and innovation capabilities. Kowsher is passionate about real-life problem-solving through technology, and has a strong thirst for knowledge about theoretical and real life generates a passion for technology.
João Luís Lins Rodrigues Cruz
Lins Rodrigues Crus is masters student in machine learning at Stevens Institute of Technology. He's curious and a data/AI enthusiast, and began studying machine learning and python on his own before moving to the US. Now, he's eager to put all this preparation into practice and generate value with the scalable potential that technology holds.
Xuting Tang
Tang is a PhD student at Stevens Institute of Technology. His research interests are natural language processing, explainable AI, reinforcement learning, and deep learning. He has published a paper at the IJCAI 2022 conference.
Mengjiao Zhang
Zhang is PhD student at Stevens Institute of Technology. Zhang's research interests are NLP, federated learning, and privacy and security in machine learning. Zhang has several papers published in these areas at top-tier conferences, including ICML and COLING.
Jia Xu - Faculty advisor
Xu is an assistant professor at the Stevens Institute of Technology. Previously, she was an associate professor at the Chinese Academy of Sciences and a faculty member and Ph.D. advisor at Tsinghua University. As a graduate student supervised by Hermann Ney from RWTH Aachen, she had fruitful visits to IBM in Watson and the NLP group in Microsoft Research (MSR) Redmond. Her current research interests are in Machine Learning, with a focus on highly competitive machine translation systems. Lately, she has developed an interest in devising techniques that explore the underlying metric and geometric properties of machine translation systems. She is publishing in mainstream venues in computational linguistics and machine learning (e.g., AAAI, ICML, ACL).
