Mohsen Moghaddam, PhD

Mohsen Moghaddam is the Gary C. Butler Family Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the George W. Woodruff School of Mechanical Engineering at Georgia Tech. His research focuses on building human-centered computational models, algorithms, and tools at the intersection of AI and spatial computing to enhance learning and creativity in various industrial use cases. Previously, he was an Assistant Professor at Northeastern University in Boston. He has also served as a Visiting Professor with the HumanTech project at Politecnico di Milano and as a Visiting Scholar at the Next Level Lab, Harvard University. Dr. Moghaddam earned his PhD in Industrial Engineering from Purdue University and completed a Postdoctoral Associate position at the GE-Purdue Partnership in Research and Innovation in Advanced Manufacturing. His research has been supported by NSF, DARPA, the U.S. Navy, and industry partners.

Shakiba Davari, PhD

Shakiba is a Postdoctoral Researcher at SAIL, led by Dr. Mohsen Moghaddam at Georgia Tech. She holds a Ph.D. in Computer Science from Virginia Tech, where she specialized in adaptive and context-aware AR/XR interfaces. Her research bridges applied machine learning and UX/UI design, focusing on developing intelligent systems that enhance usability, efficiency, and productivity. During her Ph.D., Shakiba tackled key XR challenges such as spatial layout, occlusion, and social intrusiveness, establishing design principles and frameworks for adaptive, user-centered AR/XR experiences. Shakiba has collaborated with Adobe and Microsoft Research as a Research Scientist Intern, working on context-aware XR solutions for productivity and accessibility. At SAIL, her work continues to focus on human-centered computational models and intelligent systems to augment learning, creativity, and productivity in industrial and spatial computing applications.

Sakib Reza

Sakib Reza is a PhD student specializing in computer vision and intelligent extended reality (XR), co-supervised by Dr. Octavia Camps at Northeastern University. His focuses on advancing video understanding, multimodal egocentric perception, and video-language models. His current work centers on developing multimodal egocentric perception capabilities for XR applications. Sakib’s research aims to understand user actions and activities in task-oriented scenarios, contributing to the creation of intelligent XR systems that provide context-aware guidance and enhance human capabilities across various tasks.  Before joining SAIL, Sakib completed his undergraduate degree in Computer Science and Engineering from Khulna University of Engineering & Technology, Bangladesh. He then worked as a software engineer at Samsung Research for a couple of years, contributing to innovative projects and laying the foundation for his current expertise in computer vision and XR.

Parisa Ghasemi

Parisa Ghasemi is a Ph.D. student in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, advised by Dr. Mohsen Moghaddam. Her research focuses on developing intelligent systems that enhance empathic, creative, and user-centric design by integrating design principles, generative AI, XR, and multimodal data analysis. Passionate about empowering designers to uncover latent user needs, she aims to drive breakthrough innovations. During her M.S. at Northeastern University, she advanced AI creativity by modeling abstract concepts like novelty, diversity, feasibility, and proportionality, resulting in cutting-edge systems, including a multi-agent vision-language framework and a multi-criteria-aware GAN model. Her interdisciplinary approach bridges theory and practical applications to address complex challenges. Beyond research, she is deeply interested in moral philosophy, shaping her perspective on empathic design and innovation.

Akhil Aji

Akhil Aji is a PhD student in Machine Learning at Georgia Tech, advised by Prof. Mohsen Moghaddam. His research focuses on enabling seamless communication and collaboration between humans and robots in various industrial settings. He explores multimodal interaction techniques such as gaze, gesture, and speech to enhance robot understanding of human intent in industrial tasks. His work integrates augmented reality (AR), machine learning, robotics, and IoT technologies to create intelligent systems for human-machine collaboration. Akhil holds a Master’s degree in Robotics from Northeastern University, where he gained expertise in advanced robotic systems, computer vision, and human-robot interaction. His interdisciplinary approach spans fields like robotics, computer vision, and machine learning, aiming to bridge the gap between humans and robots in dynamic, real-world environments.

Steven Yoo

Steven is a PhD student specializing in Intelligent Extended Reality (XR) and user modeling. His research focuses on human factors and ergonomics, particularly in developing multimodal expertise estimation models for XR applications. He seeks to understand novice-to-expert transitions and explore how systems can dynamically recognize and assist users based on their unique needs measured through various physiological signals, such as gaze pattern, pupil size variation, galvanic skin response (GSR), electrocardiogram (ECG), and hand/body tracking. Before joining his current lab, Steven earned an M.S. from New York University, where he contributed to research in learning sciences and educational technology. Actively involved in research and teaching, he strives to make complex topics accessible to diverse audiences. Outside academia, Steven is a coffee enthusiast ☕, always on the hunt for the perfect brew.

Mahya Qorbani

Mahya Qorbani is a PhD student in Machine Learning and a Master’s student in Computer Science, co-supervised by Dr. Kamran Paynabar and Dr. Mohsen Moghaddam. Her research interests include bridging multimodal data, natural language processing, and signal processing, with a particular focus on multimodal data integration. At SAIL, Mahya’s research focuses on user behaviors in task-driven scenarios to design advanced XR systems that provide adaptive, context-sensitive support, enhancing efficiency and effectiveness in real-world applications. Before joining SAIL, Mahya collaborated with the Department of Energy and Samsung on signal processing projects, employing methods such as Fast Fourier Transform, Denoising Autoencoders, and Regression Models. She also has experience in anomaly detection within temporal multilayer social networks, utilizing Generalized Linear Models and State-Space Models to analyze complex systems.

Chenxi (Chelsea) Yuan, PhD

Chenxi (Chelsea) Yuan is an Assistant Professor of the Department of Informatics at Ying Wu College of Computing, New Jersey Institute of Technology. Before that, she was a postdoctoral researcher mentored by Prof. Rebecca A. Hubbard and Prof. Kristin A. Linn in the Department of Biostatistics, Epidemiology, and Informatics at the Perelman School of Medicine, University of Pennsylvania. She obtained her PhD in Industrial Engineering at Northeastern University in 2022, under the supervision of Prof. Mohsen Moghaddam. Her work focuses on deep learning approaches that facilitate precision medicine and equitably improve health outcomes. She develops deep generative models to generate complete medical data, such as MRI and electronic health records, for under-represented populations. Her focus is on algorithmic fairness in machine learning models that predict prevalent public health diseases like Alzheimer’s and breast cancer.

Yi (Jade) Han, PhD

Yi (Jade) Han is a Machine Learning Scientist at Flagship Pioneering FL100, specializing in designing, developing, and evaluating NLP models. His PhD research was focused on exploring LLM-based methodologies for need finding in engineering design, specifically for language modeling, sentiment analysis, text summarization, and question answering, accelerating concept generation in engineering design. Jade believes that the future of LLMs lies in agentic systems and is currently focused on developing agentic frameworks to address issues like LLM hallucination. Jade's research lies at the intersection of Aspect-Based Sentiment Analysis (ABSA), Aspect-Guided Text Summarization (AGTS), Named Entity Recognition (NER), and latent needs identification. While computationally driven, he aims to extend their work into practical applications such as hybrid human-machine interaction systems, new product development, and implementing sustainable and resilient innovation strategies.

Casper Harteveld

Professor, College of Arts, Media, and Design, Northeastern University

Matthias Klumpp

Associate Professor, School of Management, Politecnico di Milano

Alicia Sasser Modestino

Associate Professor, Public Policy and Economics, Northeastern University

Nicholas Wilson

Director of Teaching Innovation, HILT, Harvard University