جستجوی استاد راهنمای دانشگاهی

• Human-Computer Interaction
• Human-AI Interaction
• Accessibility
• +۴ مورد دیگر

Jeffrey P. Bigham is the Philip Guo Endowed Professor of HCI at the Human-Computer Interaction Institute, Carnegie Mellon University, with a joint appointment in the Language Technologies Institute. His research focuses on accessibility, human-AI interaction, dialog systems, and crowdsourcing. School: School of Computer Science Institute: Human-Computer Interaction Institute His research spans creating accessible technologies for blind users, improving speech recognition for people with disabilities, and developing human-AI collaboration frameworks. Key projects include VizWiz accessibility tools, Scribe captioning systems, and Chorus conversational AI. Recent work emphasizes UI understanding (WebUI dataset, UICoder), generative AI applications (Apple Intelligence), and accessibility infrastructure (System-class Accessibility). Articles highlight intersections between computer vision, NLP, and inclusive design. NSF CAREER Award Best Paper Awards: ASSETS 2021, CHI 2021, W4A 2021 Nominations: CHI 2024, ECCV 2024, DIS 2024 He advises numerous students and postdocs across accessibility, AI, and HCI domains, with trainees now at Google, Apple, University of Michigan, and beyond. Funding comes from Apple, Google, Microsoft, NSF, and other major institutions.

Shyam Gollakotaمشاهده پروفایل

استاد

• Artificial Intelligence
• Computing + Biology
• Human-Centered Computing
• +۶ مورد دیگر

Shyam Gollakota is a Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. His research spans Artificial Intelligence, Human-Centered Computing, and Wireless Systems , with interdisciplinary collaborations in Biology and Medicine. He leads the Mobile Intelligence Lab , co-founded Sound Life Sciences (acquired by Google), and developed battery-free computing technologies. Education: Ph.D. from MIT (2013), B.Tech from IIT Madras Awards: Infosys Prize 2024, Moore Inventor Fellow, NSF CAREER, ACM Grace Murray Hopper Award His research focuses on machine learning for mobile systems, battery-free sensing, and human auditory augmentation . Recent work includes proactive in-ear assistants (ACL 2025), spatial speech translation (CHI 2025), and sound bubbles for personalized audio (Nature Electronics 2024) . Publications span Human-Computer Interaction, Wireless Networking, and Medical AI . Scientific achievements include: Best Paper Awards: MOBICOM, SIGCOMM, UbiComp, SenSys, NSDI, CHI Breakthroughs: Battery-free phones, ambient backscatter, smartphone-based medical diagnostics His team co-developed underwater GPS (SIGCOMM 2023), AI-enabled ClearBuds (MobiSys 2022), and wireless blood clot testing (Nature Communications 2022) . Collaborations include the Washington Department of Agriculture for monitoring invasive hornets.

Ziang Xiaoمشاهده پروفایل

استادیار

• Human-Computer Interaction (HCI)
• Natural Language Processing (NLP)
• Social and Personality Psychology
• +۴ مورد دیگر

Ziang Xiao is an Assistant Professor in Computer Science at Johns Hopkins University. He holds a Ph.D. from the University of Illinois Urbana-Champaign (UIUC) and a B.S. in Psychology and Computer Science from UIUC. His research focuses on human-computer interaction (HCI), natural language processing (NLP), and social psychology, aiming to bridge human behavior, decision-making, and technology. Education : Ph.D. in Computer Science, UIUC (Advisors: Prof. Hari Sundaram & Prof. Karrie Karahalios) B.S. in Psychology and Computer Science, UIUC (Advisor: Prof. Dov Cohen) Research Interests : Xiao’s work explores AI for social science, human-centered model evaluation, and information seeking. He designs systems that leverage LLMs to study human behavior at scale, emphasizing ethical and transparent AI integration. His interdisciplinary approach combines HCI, NLP, and psychology to address challenges like bias in multilingual models and trust in AI systems. Teaching : EN.601.790: Advanced HCI: Research Methods (Spring 2025) EMNLP 2024 Tutorial: Human-Centered Evaluation of Language Technologies EN.601.490/690: Introduction to Human-Computer Interaction (Fall 2024) Key Awards : Best Paper Award at CHI 2024 for work on LLM-driven search systems Honorable Mention at ICML 2023 for rethinking model evaluation frameworks Grants & Labs : Xiao leads projects on LLM ethics, adaptive AI systems, and HCI methodologies. His lab collaborates with industry partners (e.g., Microsoft, Google) and academic institutions to advance human-AI interaction paradigms.

Markus Zankerمشاهده پروفایل

استاد

• Information Systems
• Knowledge-based Decision Support Systems
• Personalization
• +۳ مورد دیگر

Markus Zanker is a full professor at the Faculty of Computer Science , Free University of Bozen-Bolzano (Italy), where he previously served as vice dean for studies and director for study programmes. He held associate professorship at Alpen-Adria-Universitaet Klagenfurt, Austria (2011-2016). Research Focus : Knowledge-based decision support systems, personalized information filtering/retrieval, product recommendation, conversational sales advisor systems, and product configurators Current Projects : Causal discovery in recommender systems, medical recommendation systems (insulin dosing, drug combinations), explainable AI for tourism and news recommendation The 15 most recent publications (2016-2025) cover topics including: Deep reinforcement learning for medical applications Causal modeling in tourism and online decision-making Explainable recommendation frameworks Session-based news and video recommendations Evaluation of open-source recommendation libraries His work also explores user interaction patterns through studies on bimodal rating statistics, collaborative explanations, and proactive recommendation engagement.

• Artificial Intelligence
• Natural Language Processing
• Knowledge Management
• +۷ مورد دیگر

Jorjeta Jetcheva is an Assistant Professor in the Computer Engineering Department at San José State University, part of the Charles W. Davidson College of Engineering. She brings extensive industry experience from leadership roles at Accenture, Fujitsu Laboratories of America, Itron, and Firetide, where she led innovations in AI, smart grids, and wireless networking. Her research focuses on Artificial Intelligence-based Personal Assistants, Natural Language Processing, and Knowledge Management . Her work bridges human-centered AI and enterprise applications, with emphasis on intelligent agents, knowledge platforms, and ethical AI systems. She explores how AI can enhance user productivity, decision-making, and system security across domains such as healthcare, energy, and customer service. The recent publications highlight a strong trend in Natural Language Processing applied to real-world problems like fake health news detection, agent assist systems, and knowledge graph integration. Her research also spans Smart Grid analytics, cybersecurity, and AI ethics , reflecting a multidisciplinary approach grounded in both theoretical rigor and practical deployment. Scientific Awards: Best Application Paper Award at IEEE Big Data Service 2022 Best Paper Award at SmartGridComm 2014 Top 10 Finalist, Fujitsu Next Generation Product Idea Contest 2016 ('Robo Butler') CSU STEM-NET Faculty Fellow (2023) Advising and Grants: Professor Jetcheva is the Principal Investigator of a $2.5 million NSF S-STEM grant titled 'Empowering Students to Succeed in Engineering and Computer Science'. She actively mentors graduate students, including Master’s student Garima Chaphekar, with whom she co-authored an award-winning paper on fake health news detection. She serves on the SJSU AI Advisory Committee and leads the AI Research Cluster, fostering interdisciplinary collaboration and student success. Labs and Teams: She leads the AI Research Cluster at SJSU, promoting innovation in artificial intelligence across departments. Her work involves close collaboration with students, industry partners, and interdisciplinary teams focused on deploying scalable, ethical AI solutions.

• Affective Computing
• Human-Robot Interaction
• Generative AI
• +۴ مورد دیگر

Elisabeth André is a Professor at the University of Augsburg specializing in Human-Computer Interaction and Affective Computing. Her research develops cutting-edge AI systems for socially intelligent interactions, with projects spanning healthcare, environmental sensing, and conversational agents. Key research domains include: Multimodal Affect Recognition : Designing self-supervised architectures for real-world emotion analysis Human-AI Collaboration : Establishing best practices for proactive AI agents (BEHAVE AI initiative) Generative Social Agents : Creating dialogue systems for embodied AI (MeLaX project) Trust in Robotics : Investigating nonverbal cues during human-robot interactions She maintains international collaborations across Europe and Australia, contributing to large-scale challenges like REACT for facial reaction synthesis. Her work emphasizes ethical frameworks and real-world validation.