Hi, I'm Protik Bose Pranto.

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"Everything is theoretically possible, until it is done" - Robert Anson Heinlein
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About

I am a PhD student in the Department of Computer Science at Arizona State University. Additionally, I serve as a Graduate Student Assistant at the ShaDE Lab., advised by Dr. Ariane Middel.

My research focuses on Urban Climate Informatics, Remote Sensing, and Machine Learning to advance urban and environmental sustainability. I apply statistical analyses, geospatial analysis and AI-driven models to develop urban mapping systems, assess the impacts of extreme heat, and analyze vegetation dynamics. I am also passionate about exploring various Machine Learning topics and leveraging my skills to solve complex and intriguing problems. I am also enthusiastic about developing innovative solutions and advanced programs that address real-world challenges and make a meaningful impact on a global scale.

I have received my B.Sc (Engg.) in Computer Science and Engineering from Bangladesh University of Engineering and Technology(BUET). I completed my undergraduate thesis under the supervision of Professor Dr. Md. Saidur Rahman on Graph Theory and Algorithms.

Recent News

    • April 2025: Received CAP LTER Grad Grant 2025.

      • March 2025: Secured runners-up at SpaceHACK for Sustainability Hackathon. [Letter]

        • Feb 2025: Awarded 3rd place at UCRC Poster Event.

          • Oct 2024: Paper on differentiating between satire and fake news got accepted at ICECCME'24.

            • July 2023: Awarded USENIX Security Student Grant.

              • June 2023: Poster on Targeted Disinformation got accepted in SOUPS'23.

                Past Experiences

                Start Network

                Here, I work as a consultant. On their Forecast-based, Warning, Analysis, and Response Network (FOREWARN) project, I conduct a Data Science program. I also work with the team and provide technical assistance in the pursuit of a peer-reviewed publication.
                March 2022 - July 2022 | Dhaka, Bangladesh

                Graph Drawing Research Group

                I worked as an undergraduate researcher under the supervision of Professor Dr. Md. Saidur Rahman. My undergraduate research was mostly concerned with graph theory and algorithm design.
                • We developed a polynomial-time algorithm for assigning transmitter frequencies in a tower network that minimizes overlapping signals and optimizes the frequency spectrum.
                • Additionally, we worked on another research project in which we studied a type of graph that is used to rebuild evolutionary relationships between organisms. This particular graph is referred to as the Pairwise Compatibility Graph (PCG, for short). It has been proven that not every graph is a PCG. But, we have found that grid graphs and a subclass of 3D grid graphs are 2-interval PCGs.
                October 2019 - March 2022 | Dhaka, Bangladesh

                Chaldal Tech

                  Customer Experience Team
                • Managed their website, mobile app, order APIs, search catalog and other user-facing services.
                • Prepared the app for localization. The app's texts are available in both English and Bengali.
                • Tools: TypeScript, React, React Native
                  EggShell Team
                • EggShell is a front-end technology stack. It combines several technologies, including React, Fable, ReactXP, RenderDSL, and StyleDSL, to create a common framework for both web and android.
                • In the EggShell framework, I created a new and advanced button library called ChoiceList. Depending on the user's preferences, this button can serve the function of a radio button or a checkbox.
                • Using the Eggshell framework, I assisted the team in creating Cookups, an online food delivery platform.
                • Tools: F#, Fable, React
                March 2021 - February 2022 | Dhaka, Bangladesh

                Publication

                • Protik Bose Pranto, Waqar Hassan Khan, and Ariane Middel. Poster: Systematic Literature Review on Urban Climate Informatics. Urban Climate Research Center Poster Event (UCRC 2025). [poster]

                  • Protik Bose Pranto. Paper: Satire or Fake News? Machine Learning-Based Approaches to Resolve the Dilemma. International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2024). [paper]

                    • Protik Bose Pranto, Waqar Hassan Khan, Sahar Abdelnabi, Rebecca Weil, Mario Fritz and Rakibul Hasan. Poster: Understanding the Effect of Private Data in Disinformation Propagation. Nineteenth Symposium on Usable Privacy and Security (SOUPS 2023). [pdf] [poster]

                      • Waqar Hassan Khan, Protik Bose Pranto, Tianyi Yang, and Rakibul Hasan. Poster: Exploring Privacy and Security Concerns of EdTech Users: A Qualitative Analysis of User Written Reviews. Nineteenth Symposium on Usable Privacy and Security (SOUPS 2023). [pdf] [poster]

                        • Protik Bose Pranto, Waqar Hassan Khan, Sahar Abdelnabi, Rebecca Weil, Mario Fritz and Rakibul Hasan. From Bad to Worse: Using Private Data to Propagate Disinformation on Online Platforms with a Greater Efficiency. Design x Policy (CHI Workshop (2023)). [pdf]

                            • Protik Bose Pranto, Bishal Basak Papan, and Md. Saidur Rahman. k-Safe Labelings of Connected Graphs. IEEE International Conference on Telecommunications and Photonics, ICTP (2021). [pdf]

                              • Bishal Basak Papan, Protik Bose Pranto, and Md. Saidur Rahman. On 2-Interval Pairwise Compatibility Properties of Two Classes of Grid Graphs. The Computer Journal, COMPJ (2021). [pdf]

                                • Protik Bose Pranto, Syed Zami-Ul-Haque Navid, Protik Dey, Gias Uddin, and Anindya Iqbal. Are You Misinformed? A Study of Covid-Related Fake News in Bengali on Facebook. [arXiv]

                Research and Class Projects

                Bengali Covid Related Fake News Detection


                Our opinions and views of life can be shaped by how we perceive the opinions of others on social media like Facebook. This dependence has increased during COVID-19 periods when we have fewer means to connect with others. However, fake news related to COVID-19 has become a significant problem on Facebook. Bengali is the seventh most spoken language worldwide, yet we are aware of no previous research that studied the prevalence of COVID-19 related fake news in Bengali on Facebook. In this paper, we develop machine learning models to detect fake news in Bengali automatically. The best performing model is BERT, with an F1-score of 0.97. We apply BERT on all Facebook Bengali posts related to COVID-19. We find 10 topics in the COVID-19 Bengali fake news grouped into three categories: System (e.g., medical system), belief (e.g., religious rituals), and social (e.g., scientific awareness).

                Satire or Fake news? Machine Learning Based Approaches to Resolve the Dilemma

                Examined nine widely used traditional machine learning models and three transformer-based traditional models (BERT, XLM-RoBERTa, DistilBERT) to see whether they can distinguish effectively between fake and satirical news. SVM performs better on a small dataset when text preprocessing and stemming are used. However, after text augmentation, the transformer-based model (XLM-RoBERTa) outperforms all other models, achieving 97% accuracy.

                Feature-Based App Analysis

                In this experiment, I am conducting an Automated exploration of an app's features to scrutinize the data collected from network traffic using MitmProxy, Frida, and Objection. In some cases, where data is obfuscated or altered before transmission, deciphering the associated permission methods becomes challenging. To address this, I have employed Frida Hooking to identify the specific permission methods called by the app and understand their utilization.

                Violence Detection from Surveillance Videos

                • We extracted two kinds of features from videos
                • Those features entail deep representation from I3D and optical flow from OpenPose
                • We employed heirarchical Multiple Instance Learning to facilitate detection
                • We emphasized on interpretability as well as accuracy of our system
                • Keywords: Optical Flow, Heirarchical Multiple Instance Learning, Video Classification, Interpretable System

                Projects

                Vasha-Sikkha
                Vasha-Sikkha

                An application that helps you learn English in a very interactive way.

                Accomplishments
                • Tools: Dart, Flutter, Laravel
                • Register/login to the app(with OAuth-based Google Sign-In).
                • User can choose from a number of different lessons where each lesson contains predefined number of tasks.
                • Tasks are be assigned to the user based on difficulty level.
                • On completing a lesson, user score is updated, and he/she can view his/her ranking in the leaderboard.
                • New tasks are suggested based on previous history.
                CovidLife
                CovidLife

                This is a health related android application based on Flutter.

                Accomplishments
                • Tools: Dart, Flutter
                • Corona details of Bangladesh are shown here. Two built-in APIs are used to provide district wise and daily corona data.
                • Doctor appointment,phone call or message can be made easily.
                Gesture sensed Snake Game
                Gesture Sensed Snake

                This is a hardware project using Atmega32 and Accelerometer sensor.

                Accomplishments
                • Tools: C, C++, Makefile
                • It is a typical snake game but it is played on four 8 by 8 dot matrices.
                • Four 8 by 8 rgb dot matrices are controlled by three types of decoders.
                Hotel Management System
                Hotel Management System

                This is a Java and Oracle Database based Project.

                Accomplishments
                • Tools: Java, SQL
                • JavaFX Scene Builder is used for the UI parts.
                • In the database system, employees can be identified by their name, address, phone number, id, job title, salary, hire date etc.
                • The user can also add, delete, and edit the reservation.
                Multiplayer Online Poker
                Multiplayer Online Poker

                This is a Java-based multiplayer online card game.

                Accomplishments
                • JavaFx is used to make the UI.
                • It can be played by 2 different players connected with the game server.
                Baby's Walk
                Baby's Walk

                This is a simple iGraphics game. Here user has to balance a walking baby by left-right mouse clicking.

                Accomplishments
                • Tools: iGraphics, C
                • A toddler is learning to walk. However, it is incapable of balancing itself.
                • The user's task is to balance the child by pressing the mouse button. The left foot is moved forward by the left click, and the right foot is moved forward by the right click.
                Mancala
                Mancala

                This is a Java-based AI-based two-player game.

                Accomplishments
                • Mancala is a two-player strategy board game with a turn-based system.
                • Typically, the goal is to capture all or a subset of the opponent's pieces.
                • It is possible to play AI vs. AI or player vs. player.
                compiler
                Compiler

                Let's build a compiler from scratch.

                Accomplishments
                • Tools: C, Yacc, C++, Lex, Shell, Assembly
                • It is accomplished in four steps, beginning with a symbol table and ending with assembly code.
                • It can compile C code and find bugs in it.

                Skills

                • Languages: C, C++, Java, R, Dart, Python, HTML, Assembly(80x86), Matlab, SQL, Typescript, F#, Bash.
                • Environment: CodeBlocks, NetBeans, Emu8086, Android Studio, Visual Studio Code, Proteus.
                • Mobile Application Development: Android, Flutter, React Native.
                • Databases: Oracle, MySQL, SQLite.
                • Tools and Platforms: Git, Unity, Lucidchart, draw.io, OpenCV, Cuda, JavaFX Scene Builder, Tensorflow, Keras, PyTorch, Scikit-learn.
                • Other: QGIS, Qualtrics, Latex, Microsoft Office, Microsoft Powerpoint, Probability and Statistics, Data Structures, Unity.

                Education

                Arizona State University

                Tempe, Arizona

                Degree: Ph.D. in Computer Science and Engineering (ongoing)

                  Relevant Courseworks:

                  • Data Mining
                  • Software Security
                  • Statistical Machine Learning
                  • Knowledge Representation and Reasoning

                Bangladesh University of Engineering and Technology (BUET)

                Dhaka, Bangladesh

                Degree: Bachelor of Science in Computer Science and Engineering

                  Relevant Courseworks:

                  • Data Structures and Algorithms
                  • High Performance Database Systems
                  • Computer Security
                  • Machine Learning
                  • Computer Graphics

                Contact

                ASU School of Computing and Augmented Intelligence,

                Department of Computer Science,

                699 S Mill Ave, Tempe, AZ 85281, United States

                ppranto@asu.edu