Members Of AI4Business Lab
Professor Huangfu received her Ph.D. from the University of Arizona. Her areas of research expertise include business analytics, public health, machine learning, and data mining. Her research has been published in a list of conference proceedings and journals, including IEEE Transactions on Cybernetics, Journal of Medical Internet Research, IEEE Signal Processing Letters, Pacific Asia Journal of the Association for Information Systems (PAJAIS), Pattern Recognition Letters, etc., with more than 100 citations.
She serves as a reviewer for IEEE Intelligent Systems, Information & Management, Information Systems Frontiers, Annual Meeting of the Association for Computational Linguistics (ACL), Empirical Methods in Natural Language Processing (EMNLP), etc.
She is a GREW Fellow and received several grants from National Institution of Health (NIH), National Security Agency (NSA), Department of Energy (DOE), etc.
Professor Huang received his BEng and PhD degrees both from Chongqing University, Chongqing, P.R.China, in 2010 and 2015 respectively. He was also a visiting PhD student at the department of computer science, Rutgers University, New Brunswick, NJ, USA, from 2012 to 2014. He is currently an associate professor at the school of Big Data and Software Engineering, Chongqing University, and also affiliated with the Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society. He has authored/coauthored more than 40 scientific papers in venues, such as CVPR, AAAI, TIP, TIFS, TMI and TCSVT. His research interests include computer vision, machine learning, image processing and artificial intelligent applications.
Aradhya has completed his undergraduate degree in computer science and is currently a graduate student at San Diego State University. He has been working on various projects and one of his research projects on opinion analysis of electric vehicles was published in IRAJ International Research and Journals. Apart from that, he has also done two internships during his undergraduate, one at Codenscious.ai where he was a machine learning intern, and the second at Kirloskar Brothers Limited. He wants to work in the field of research and development, which could help society to improve.
Devon began attending SDSU in 2020 and graduated in 2022 with a bachelors in Computer Science with honors as summa cum laude. His interests have evolved over his time pursuing his degree but he is passionate about machine learning, computer vision, deep learning, and autonomous vehicles. He worked on several projects with Dr. Huangfu since 2021 and is co-author of a paper titled Kernel Inversed Pyramidal Resizing Network for Efficient Pavement Distress Recognition. His other work with Dr. Huangfu included a sentiment analysis infused stock prediction model utilizing BERT and Transformer models as its architecture. After graduation, Devon has gained employment as a Machine Learning Engineer working with autonomous vehicles.
Dylan is a master student at San Diego State University. He aims to use machine learning to help solve some of the world challenging problems. He graduated from Michigan State University. He enjoys applying data science skills to the medical and financial fields. He is currently working on a research project regarding how the war in Ukraine is impacting the predictably of the energy sector of the US stock market and how to identify companies with sustainable business strategies who are likely to be successful in the long term.
Fadi is an undergraduate student at SDSU, majoring in computer science and minoring in mathematics. His interests are machine learning, data analysis, and web development. Fadi is looking forward to working as a software engineer upon graduating from college.
Faiz is currently pursuing his master’s degree at San Diego State University. He is an enterprising, enthusiastic, and results-driven business analyst, who enjoys fast-paced and dynamic working environments. His 4+ years of combined experience in change management, leadership, and software development roles has prepared him to continually take on new and more complex challenges with additional responsibilities and interesting problems to solve.
Kayla has a San Diego State University bachelor’s degree in Management Information Systems and a minor in Computer Science. Her interests are UI/UX, web development, and data analytics. She has been working with Professor Huangfu for two semesters, during which she has utilized Repl.it and Google Colab for Python. In addition, she and Professor Huangfu worked on a project regarding COVID-19 vaccines.
Karina is pursuing a bachelor’s degree at San Diego State University in Management Information Systems with minors in Interdisciplinary Studies and Women’s Studies. Her interests are data analytics, cyber security, and database development. She has experience working with Python and SQL through various MIS courses, and she also worked on a semester-long project building the back end and front end framework for a business concept, culminating in a formal presentation to leaders in the MIS industry. Additionally, this summer, she worked for Segment and gained knowledge about how companies utilize customer data. She is grateful for this opportunity to learn from the many exceptional researchers in the Business Lab.
Patrick has a San Diego State University bachelor’s degree in Management Information Systems and a minor in Computer Science. His interests are data mining, sentiment analysis, and deep learning models. He worked on several projects. Some of the tasks which he was involved with include sentiment analysis, convolutional and recurrent neural networks, and gathering large data sets. Most recently, he and Dr. Huangfu co-authored a paper titled CURVE4COVID: Comprehensive Understanding via Representative Variable Exploration for COVID-19. The paper seeks to uncover the human and non-human factors that may lead to the increase of the rate of COVID-19 infection. This paper was published in Americas Conference on Information Systems (AMCIS) 2021 and won an award for being in the top 25% of papers accepted.
Fengtao is currently a PhD student at the Department of Computer Science and Engineering (CSE), Hong Kong University of Science and Technology (HKUST). He received the bachelor’s degree and master’s degree from Chongqing University (CQU) in 2019 and 2022. His research interests include medical image analysis, artificial intelligence, machine learning, and computer vision. He has co-authored a top-tier IJCAI paper named “Boosting multi-Label Image Classification with Complementary Parallel Self-Distillation” with Dr. Huangfu.
Guixin is currently working at Global Function and Technology department of Citigroup as a backend developer. He obtained his master’s degree in software engineering from Chongqing University in 2021. His research fields mainly focus on image recognition and processing. He has co-authored a paper named "Weakly Supervised Patch Label Inference Network with Image Pyramid for Pavement Diseases Recognition in the Wild" with Dr. Huangfu.
Himali began the Master of Information Systems program at San Diego State University's Fowler College of Business. She has an Electronics and Telecommunications Engineering bachelor's degree, as well as a Post Graduate Diploma in Advanced Computing. She has worked in software quality assurance for more than 4.5 years, and has also created automation scripts in Java and Selenium. Additionally, proficient with MS Excel and Confluence for project management. Predictive models, sentiment analysis, and data mining are three topics that she is interested in.
Himani has completed her undergraduate degree in Computer Engineering from Pune University, India. She has work experience of around 3 years as a Software Engineer at Accenture. She has worked in salesforce technology and has experience in the development and quality assurance of cloud applications using the Salesforce CRM platform. She has a certified Salesforce Developer and Salesforce Certified Administrator; this professional experience has not only helped her grow technically but also given her deep insights into sales processes in a business.
Huanhuan has completed her graduate degree in software engineering in 2022. She has been working on various projects and one of her research projects on vehicle matching, which belongs to the field of computer vision. She aims to use machine learning to help solve some of the challenging problems, and wants to work in the field of research and development. She has co-authored a Wiley journal paper named "ASDFL: An Adaptive Super-pixel Discriminative Feature-selective Learning for Vehicle Matching" with Dr. Huangfu.
Jiazhi is a master student and has a bachelor’s degree in Chongqing University, Chongqing, P.R.China. His main interests are image classification, object detection and their application. He pays attention to the usability of deep learning algorithms, and searches for the suitable optimization for current approaches. He is currently working as an intern in a computer vision company and learning the industrial deployment of deep learning methods. He believes the excellent algorithm with the convenient deployment has maximum value.
Lei is a master student at the school of Big Data and Software Engineering, Chongqing University, Chongqing, P.R.China. He received his BEng degree from Chongqing University. His interests are computer vision and deep learning models. He enjoys applying machine learning and deep learning to the multi-label classification and out-of-distribution detection tasks. He is currently working on a research project that how to detect the out-of-distribution inputs when the classification models are trained on multi-label datasets.
Lili is an exchange student at San Diego State University from the University of Pecs, Hungary where she is pursuing her bachelor’s degree in Computer Science and Engineering. Her interests are data analytics, machine learning, and deep learning models. She worked on a project regarding the interpretability of neural networks and researched ways to improve them. Her most recent research project involves distributed object detection of mobile autonomous devices that execute on commodity hardware.
Luis is a master student at San Diego State University. His areas of interest are Machine Learning, Data Science, Deep Learning and UI/UX. He co-authored three papers which have been reviewed by academic conferences. The first paper is titled Redefining Education in the Digital Economy: The Role of Social Innovation based Learning in Information Systems Education, this paper was published in AMCIS 2020 and the second paper Toward a Theory of Digital Mindfulness: A Case of Smartphone-Based Self-monitoring was accepted at HCII 2021. He was also the lead author for the third paper titled Service Failure Recovery in the Sharing Economy: A Case Study of Airbnb, which has been published to HICSS 2021. He considers himself a long-life learner who is enthusiastic about learning new technologies.
Mengran is studying at San Diego State University and pursuing her bachelor’s degree in Accounting. She has interests in Accounting information systems, programming and machine learning. She joins AI4 Business Lab to work with Dr. Huangfu in Fall 2022. She will work on projects related to collecting data from the public's discussion and attitudes toward crisis topics.
Pooja is a Master's student at San Diego State University, majoring in Computer Science. Her interest lies in Data Science and Machine Learning, and have a strong background in data analysis. She did her bachelor's in Computer Engineering from the University of Mumbai in India. She believes in using her knowledge and skills to help people and give back to the community.
Rong is a undergraduate student at Chongqing University. He is committed to using computer vision technology and machine learning to solve application problems and develop intelligent software. He is currently working on a research project researching effective graphical API recommendation and how to reduce the key information loss of megapixel image during resizing so as to better use them without splitting the original high resolution image into patches and processing them separately. He has already published several papers under Dr. Huangfu's guidance and continues to work on research projects with Dr. Huangfu.
Sheetal is a Software Engineer, having professional experience in business process management software development. Her background is with backend development to bring the best of system for a splendid user experience. She has completed her Bachelor’s degree in Information Technology from Pune University in India. She is enrolled in Master’s program, majoring in Computer Science at San Diego State University. She considers herself a ‘forever student’, eager to build a strong base for herself in Machine Learning and Data Engineering fields.
Wenhao is a master student at Chongqing University. His interests are computer vision, intelligent transportation systems, and image processing. He and Dr. Huangfu have co-authored several papers in the field of intelligent transportation, published in IEEE Transactions on Intelligent Transportation Systems and Electronics Letters. Most recently, he and Dr. Huangfu co-authored a paper titled PicT: A Slim Weakly Supervised Vision Transformer for Pavement Distress Classification. The paper is the first to apply the visual Transformer to the field of pavement distress classification, which substantially improves the efficiency and performance of disease classification. This paper has been accepted by ACM Multimedia (ACM MM) 2022.
Yi received the B.S. degree from Chongqing Normal University, China, in 2016. He is currently pursuing the Ph.D. degree with the School of Big Data and Software Engineering, Chongqing University. His research interests include pattern recognition, image processing, and few-shot learning.
Zeyu is a master student at the School of Big Data and Software in Chongqing University. She has researched the issue of graphic API recommendation with Professor Huangfu in the field of software engineering and has published papers at international conferences. The recommendation algorithms proposed in these papers help users save time and improve work efficiency.
