Publications

2026

1. UbiComp/ISWC

   

   Characterizing the Performance Gap in Human Activity Recognition for Older Adults

   Hossein Khayami, Sungjin Hwang, Eshed Ohn-Bar, David E Conroy, Amanda Lazar, and 2 more authors

   In Submitted to the 2026 ACM International Symposium on Wearable Computers, Shanghai, China, 2026
2. SIGACCESS

   

   Teachable Tracking: Supporting Older Adults in Shaping Their Own Activity Recognition Systems

   Hossein Khayami

   SIGACCESS Access. Comput., Apr 2026

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   Commercial activity trackers frequently fail to meet the needs of older adults by focusing on generic metrics (e.g., step counts) while overlooking the personally meaningful activities that they may want to track in their everyday life. This disconnect stems from a fundamental challenge: the difficulty of capturing accurate ground-truth labels for complex, real-world activities, which forces a reliance on generic, one-size-fits-all models. My doctoral research seeks to address this problem by developing a human-centered approach to recognize activities that truly matter to individual older adults, moving beyond basic posture detection to a rich, semantic understanding of daily life. My research will culminate in a framework for a "teachable" activity tracker that older adults can train themselves. Part of my completed doctoral work establishes the need for personalization by demonstrating significant variability in older adults’ movement patterns and deconstructs the challenges of collecting data "in the wild," quantifying the costs and benefits of triangulating sensor data with user-provided verbal reports. This is complemented by technical explorations into data-driven methods for optimizing on-body sensor placement. Ongoing work investigates the feasibility of older adults training their own personalized models in-situ through transfer learning. We are going to explore models capable of inferring high-level, meaningful activities (e.g., "gardening," "playing golf") from a stream of low-level sensor data. Ultimately, this thesis contributes initial steps toward a reframing of activity recognition—from an emphasis on technological capability to an emphasis on user-valued activities—thereby offering insights that could support the development of more personalized tools for older adults.

2025

1. UbiComp

   

   Personalizing Activity Tracking: Enabling Older Adults to Teach and Train Their Wearables

   Hossein Khayami

   In Companion Proceedings of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’25), Oct 2025

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   Commercial activity trackers frequently fail to meet the needs of older adults by focusing on generic metrics (e.g., step counts) while overlooking the personally meaningful activities that they may want to track in their everyday life. This disconnect stems from a fundamental challenge: the difficulty of capturing accurate ground-truth labels for complex, real-world activities, which forces a reliance on generic, one-size-fits-all models. My doctoral research confronts this problem by developing a human-centered approach to recognize activities that truly matter to individual older adults, moving beyond basic posture detection to a rich, semantic understanding of daily life. Part of my completed doctoral work establishes the need for personalization by demonstrating significant variability in older adults’ movement patterns and deconstructs the challenges of collecting data ”in the wild,” quantifying the costs and benefits of triangulating sensor data with user-provided verbal reports. This is complemented by technical explorations into data-driven methods for optimizing on-body sensor placement. Ongoing work investigates the feasibility of older adults training their own personalized models in-situ through transfer learning. My research will culminate in a framework for a ”teachable” activity tracker that older adults can train themselves, and a neuro-symbolic model capable of inferring high-level, meaningful activities (e.g., ”gardening,” ”playing golf”) from a stream of low-level sensor data. Ultimately, this thesis contributes a new paradigm for activity recognition—one that shifts the focus from what technology can track to what people want to track, enabling the creation of personalized tools that genuinely support and reflect the lives of older adults.

2. AICSP

   

   Chaos-based Pseudo Random Number Generators via quasi-synchronized Chua’s circuits: a symmetric encryption perspective

   Aidin Momtaz, Ehsan Qoreishi, Sarah Amini, Hossein Khayami, Kasra Amini, and 1 more author

   Analog Integrated Circuits and Signal Processing, Dec 2025

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   Research efforts have extensively shown the significant roles of unpredictable phenomena originated in nature, such as chaos, as an inspiring discipline to generate random numbers. In the current study, focusing on encryption purposes, the main strategy is to provide a keystream using Pseudo Random Number Generators (PRNGs) derived from synchronized chaotic systems. Numerous Investigations performed on the synchronized configuration of Chua’s circuit have proven the advantage of its application as a prominent chaotic system. However, the less than ideal alignment between the core objective of the research, that is offering a secure communication optionally necessitating an arbitrary distance of the correspondents, and the standard version of synchronized Chua’s circuits not fulfilling this condition pragmatically, made the authors tackle the problem analytically by using the governing equations of the circuits and creating the so-called quasisynchronized condition between the receiving and the transmitting sides. At last, eight different mathematical schemes are designed to manipulate the numerical data provided by the Chua’s equations to generate binary sequences for encryption purposes and then the main attempt has been dedicated to the evaluation of the results and finding the optimal PRNGs by conventional standards in cryptography provided by National Institute of Standards and Technology. Finally, three of the designed schemes are chosen as the successful methods, passing randomness criteria.

3. IMWUT

   

   Enabling Older Adults to Provide High-quality Activity Labels: Unpacking Accuracy, Precision, and Granularity in Activity Labeling

   Yiwen Wang, Hossein Khayami, Bongshin Lee, Amanda Lazar, Hernisa Kacorri, and 1 more author

   Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Dec 2025

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   High-quality labels of activity data with broad representations and real-world variability are key to developing activity recognition models tailored to the needs and characteristics of older adults. However, labeling real-world data presents significant challenges, placing a heavy burden on users to provide high-quality labels while staying engaged in their activities. This paper investigates older adults’ perceptions of providing high-quality labels in the context of training their personalized activity trackers. We conducted a co-design study with 12 older adults to envision the labeling process—describing activity names and time spans—using the teachable machines paradigm as a scaffold. We unpack the contextualized definitions of accuracy, precision, and granularity through a thematic analysis of older adults’ perspectives on activity labeling. Our findings present participants’ preferred strategies for obtaining high-quality activity labels with less burden and intrusiveness, including user-initiated labeling and machine-initiated prompting. We discuss design considerations for future data labeling tools that address discrepancies between user perceptions and technical standards in training personalized activity trackers.

4. IMWUT

   

   From Verbal Reports to Personalized Activity Trackers: Understanding the Challenges of Ground Truth Data Collection with Older Adults in the Wild

   Hossein Khayami, Lining Wang, Young-Ho Kim, Bongshin Lee, David E Conroy, and 3 more authors

   Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Jun 2025

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   Tracking activities holds great potential to improve the well-being of older adults, yet the accuracy of activity trackers for this demographic remains in question. Evaluating this accuracy requires ground-truth data directly from older adults, which has largely been gathered in controlled laboratory settings or labeled by researchers. Moreover, considering the diversity in older adults’ activity engagement and tracking preferences, personalized activity tracking appears necessary. We demonstrate that older adults can benefit from personalized activity trackers by showing that cadence thresholds for stepping intensities vary within this group. However, collecting ground-truth data from older adults in real-world settings poses unique challenges. This paper examines two sources of ground-truth labels for the smartwatch Inertial Measurement Unit (IMU) data collected with older adults. Using verbal self-reports and a thigh-worn activity tracker, we assess their viability as ground-truth sources in natural settings. Additionally, we evaluate the costs and benefits of triangulating these sources as a ground-truth proxy. Our findings reveal two main costs: data shrinkage and notable effort from both contributors and data stewards. Simultaneously, we observe improved data quality and a greater ability to identify error sources when evaluating a trained model.

2024

1. arXiv

   

   IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture

   Varun Ramani, Hossein Khayami, Yang Bai, Nakul Garg, and Nirupam Roy

   arXiv preprint arXiv:2402.08923, Jun 2024

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2. Scientia

   

   A joint encryption-encoding scheme using QC-LDPC codes based on finite geometry

   Hossein Khayami, Taraneh Eghlidos, and Mohammad Reza Aref

   Scientia Iranica, Jun 2024

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   Joint encryption encoding schemes have been released to fulfill both reliability and security desires in a single step. Using Low Density Parity-Check (LDPC) codes in joint encryption encoding schemes, as an alternative to classical linear codes, would shorten the key size as well as improving error correction capability. In this article, a joint encryption encoding scheme using Quasi-Cyclic Low Density Parity-Check (QC-LDPC) codes based on finite geometry is presented. It is observed that our proposed scheme not only outperforms its predecessors in key size and transmission rate, but also remains secure against all known cryptanalyses of code-based secret key cryptosystems. In this paper, we have proposed an idea to make QC-LDPC based cryptosystems secure against reaction attacks. It is subsequently shown that our scheme benefits from low computational complexity. By taking the advantage of QC-LDPC codes based on finite geometry, the key size of our scheme is very close to its target security level. In addition, using the proposed scheme, a wide range of desirable transmission rates are achievable. This variety of codes makes our cryptosystem suitable for a number of different communication and cryptographic standards such as wireless personal area networks (WPAN) and digital video broadcasting (DVB).

2020

1. IEEE WCNC

   

   Dynamic HARQ with Guaranteed Delay

   Mahyar Shirvanimoghaddam, Hossein Khayami, Yonghui Li, and Branka Vucetic

   In 2020 IEEE Wireless Communications and Networking Conference (WCNC), May 2020

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   In this paper, a dynamic-hybrid automatic repeat request (D-HARQ) scheme with guaranteed delay performance is proposed. As opposed to the conventional HARQ that the maximum number of re-transmissions, L, is fixed, in the proposed scheme packets can be re-transmitted more times given that the previous packet was received with less than L re-transmissions. The dynamic of the proposed scheme is analyzed using the Markov model. For delay sensitive applications, the proposed scheme shows a superior performance in terms of packet error rate compared with the conventional HARQ and Fixed retransmission schemes when the channel state information is not available at the transmitter. We further show that D-HARQ achieves a higher throughput compared with the conventional HARQ and fixed re-transmission schemes under the same reliability constraint.

2013

1. IEEE

   

   Cognitive radio ad hoc networks for smart grid communications: A disaster management approach

   Hossein Khayami, Mohsen Ghassemi, Kamyar Ardekani, Behrouz Maham, and Walid Saad

   In 2013 IEEE/CIC International Conference on Communications in China (ICCC), Aug 2013

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   The explosive growth in users’ demand in both areas of wireless communications and power generation has led to design of new key technologies that will be dominant in the near future; cognitive radio networks in communications and smart grid in power field. This paper proposes a novel scenario to marry these technologies together by using a cognitive radio ad hoc network (CRAHN) as the foundation of smart grid communications. It discusses formation and throughput of such a citywide network, the information transferred by the network, and how this structure can be relied upon in disasters, compared to the state-of-the-art.

2012

1. IEEE

   

   Smart plugs for building energy management systems

   Hamed Morsali, Seyed Mohammad Shekarabi, Kamyar Ardekani, Hossein Khayami, Alireza Fereidunian, and 2 more authors

   In Iranian Conference on Smart Grids, May 2012

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   Due to rising value of energy supplies, the need for managing electrical energy sources becomes prominent. In this paper, a smart plug device is presented; which provides features to measure energy consumption and recognizes the type of attached electrical devices. Furthermore, the proposed framework enables home controller systems to monitor and control home energy consumption efficiently. Subsequently an analysis of energy consumption of a pilot house, prior and after the installation of the smart plug, based on a hypothetical scenario, is provided. The results present positive impacts of using the smart plug on energy consumption rate; especially during peak hours.