Raihanul Alam Hridoy ☕️
Raihanul Alam Hridoy

Graduate Teaching Assistant

University of Iowa – Dept. of Computer Science
Tekarsh / MarginEdge

About Me

  • Follow my research Google Scholar (Citations 200+)
  • Best Paper Honorable Mention at CHI’21 (Paper)
  • Read my recent work FogSense
  • Strong foundation in software engineering, machine learning, and health informatics; passionate about designing data-driven systems
View CV
Interests
  • AI & Machine Learning
  • Human-Centered Computing
  • Software Engineering & Security
Education

  • Computer Science

    University of Iowa (UIOWA)

  • BSc in Computer Science and Engineering

    Bangladesh University of Engineering and Technology (BUET)

Featured Publications
FocalLens: Visualizing Narratives through Focalization
Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors
A Heuristic for Maximum Greedy Consensus Tree Problem
Understanding the social determinants of mental health of undergraduate students in Bangladesh: interview study
‘Unmochon’: A Tool to Combat Online Sexual Harassment over Facebook Messenger
HCI

‘Unmochon’: A Tool to Combat Online Sexual Harassment over Facebook Messenger

Women in the global south often seek justice to their online harassment through unveiling the harassers and the screenshots of their sent harassment texts and visual contents before the relevant authorities. Nevertheless, such evidence is often challenged for their authenticity. Our survey (n=91) and interview (n=43) with Bangladeshi online gender harassment victims revealed the depth of the problem, and we set design goals to collect evidence from Facebook Messenger with ensured authenticity. Building on the ‘shame-based model’ of gender justice [12], we designed ‘Unmochon’, a tool that captures authentic evidence and shares with victims’ intended group. Our user-study (n=48) revealed that diminishing authenticity problem may still leave the victim and online gender justice entangled with mob-sentiment, hegemonic legal consciousness, and several privacy aspects. Our findings open up a new discussion on how HCI-design should address online gender justice in such a complex social setting.

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Projects
FocalLens - Visualizing Narratives through Focalization
Federated Gradient Inversion Attack
Sleeper Agent: Hidden Trigger Backdoors in Neural Networks
Adversarial Machine Learning

Sleeper Agent: Hidden Trigger Backdoors in Neural Networks

View Project Sleeper Agent is a scalable clean-label data poisoning attack that implants hidden trigger backdoors into neural networks trained from scratch. Unlike traditional backdoor attacks that rely on visible triggers or label flipping, Sleeper Agent introduces only imperceptible perturbations during training while preserving correct labels. The backdoor activates only at test time when a visible trigger patch is added. The attack demonstrates that modern deep learning models can be maliciously controlled even when: Training is performed from random initialization, The attacker has no access to the victim model architecture (black-box), Only a very small fraction of the training data is poisoned. The core insight is that by aligning gradients of poisoned training samples with those of a patched target image, the attacker can steer the model toward learning a hidden association between a trigger and a target class, without sacrificing clean accuracy.

Context-Aware Cognitive Reframing for Mental Wellbeing
Mental Health

Context-Aware Cognitive Reframing for Mental Wellbeing

View Project This project explores cognitive reframing for mental health using context awareness and multi‑modal sensing. Instead of relying on static journaling or manual prompts, the system detects moments of stress or negative self‑talk and delivers timely, personalized reframing cues in daily life. The goal is to help people notice unhelpful interpretations and shift toward more balanced, compassionate perspectives. The approach is designed for real‑world conditions where: Emotional state fluctuates across situations and routines, Users may not recognize cognitive distortions in the moment, Minimal effort and interruption are essential for sustained engagement. The core idea is to combine passive sensing (physiological and behavioral) with context inference (location, activity, social setting) to trigger micro‑interventions that fit the user’s current situation without feeling intrusive.

FOGSense
Unmochon
Phylogenetic Tree
Longest Path Problem
Blood Cell Classification
Machine Learning

Blood Cell Classification

View Project This project focuses on the application of deep learning techniques for automated blood cell classification. This is an object detection project. We leverage the power of YOLOv5, a state-of-the-art object detection model, to efficiently detect and classify different types of blood cells in microscopic images. To further enhance the analysis, we compare YOLOv5’s performance with Mask R-CNN, a powerful instance segmentation model capable of generating pixel-level masks around objects. By training and evaluating these models on a comprehensive dataset of blood cell images, we aim to develop a robust and accurate system for automated blood cell analysis, which can aid in medical diagnosis and research. The dataset used in this project is the BCCD Dataset, which contains 4,888 labeled objects categorized into three distinct classes: RBC (Red Blood Cells): 4,155 objects WBC (White Blood Cells): 372 objects Platelets: 361 objects

ParkIn: A Smart Parking App
Android Studio

ParkIn: A Smart Parking App

The number of personal vehicles usage is increasing manifold. People prefer personal vehicles to commute than depend on public transportation. Finding a parking space in most metropolitan areas, especially during the rush hours, is difficult for drivers. Due to this there is a need to provide sufficient parking places coupled with plenty of slots to help the user park his vehicle safely, also to ensure the user does not end up parking on non-parking area and cause discomfort to pedestrian.Due to this there is a need to provide sufficient parking places coupled with plenty of slots to help the user park his vehicle safely, also to ensure the user does not end up parking on non-parking area and cause discomfort to pedestrian. The idea behind our Android Application- “ParkIn” is to help the user analyse area’s where parking is available and number of slots free in that area.Additionally, the user can pre-book a slot in the area he desires for some consecutive days (along with the daily service) if it is available. This will help reduce the load on the administrator as his physical work reduces drastically and user can search the parking slot through Android Application.User can pay after completion of parking service he received. “ParkIn” Application relieves the user from the hassle of manually searching and waiting for empty slots to park the vehicle.

Paging Framework for xv6 OS
ARP Cache Poisoning
Computer Security

ARP Cache Poisoning

View Project In computer networking, ARP spoofing, ARP cache poisoning, or ARP poison routing, is a technique by which an attacker sends (spoofed) Address Resolution Protocol (ARP) messages onto a local area network. Generally, the aim is to associate the attacker’s MAC address with the IP address of another host, such as the default gateway, causing any traffic meant for that IP address to be sent to the attacker instead. ARP spoofing may allow an attacker to intercept data frames on a network, modify the traffic, or stop all traffic. Often the attack is used as an opening for other attacks, such as denial of service, man in the middle, or session hijacking attacks. The attack can only be used on networks that use ARP, and requires attacker have direct access to the local network segment to be attacked.

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Recent Publications
SM Raihanul Alam, Md Dilshadur Rahman, Md Naimul Hoque (2026). FocalLens: Visualizing Narratives through Focalization. arXiv preprint arXiv:2604.14456.
PDF Cite Project DOI arXiv PDF
Shovito Barua Soumma, SM Raihanul Alam, Rudmila Rahman, Umme Niraj Mahi, Abdullah Mamun, Sayyed Mostafa Mostafavi, Hassan Ghasemzadeh (2025). Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors.
PDF Code arXiv GitHub Repository
SM Raihanul Alam, Md Moaz Mahmud, Md Saidur Rahman (2022). A Heuristic for Maximum Greedy Consensus Tree Problem. 2022 12th International Conference on Electrical and Computer Engineering (ICECE).
PDF Cite Code Dataset Poster Slides Conference Link Undergraduate Thesis
Sharifa Sultana, Sadia Tasnuva Pritha, Rahnuma Tasnim, Anik Das, Rokeya Akter, Shaid Hasan, SM Raihanul Alam, Muhammad Ashad Kabir, Syed Ishtiaque Ahmed (2022). ‘shishushurokkha’: A transformative justice approach for combating child sexual abuse in bangladesh. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems.
Cite
Sharifa Sultana, Pratyasha Saha, Shaid Hasan, SM Raihanul Alam, Rokeya Akter, Md Mirajul Islam, Raihan Islam Arnob, AKM Najmul Islam, Mahdi Nasrullah Al-Ameen, Syed Ishtiaque Ahmed (2022). Imagined Online Communities: Communionship, Sovereignty, and Inclusiveness in Facebook Groups. Proceedings of the ACM on Human-Computer Interaction.
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Recent & Upcoming Talks
7th NSysS 2020
Blood Cell Classification using YOLOv5 and Mask R-CNN