Mayesha’s research focuses on human-AI interaction, AI-supported decision-making, user behavior, trust, educational technology, NLP, and the real-world evaluation of intelligent systems.
Full-time English teacher at Maple Inc. Independent research, product work, and MASc applications for Fall 2027. Earlier: research assistant under Professor Parag Kulkarni (November 2023 — March 2026).
BSc in Digital Business and Innovation with a concentration in Data Science and AI from Tokyo International University. Full-tuition scholarship, April 2022 — March 2026.
Bachelor of Science with a concentration in Data Science and AI. Full-tuition scholarship.
Recipient of TIU’s 100% tuition-reduction scholarship for the undergraduate degree (2022–2026).
Also received the Monbukagakusho Honors Scholarship for privately-financed international students (JASSO), April 2022.
Studied digital business, data science, artificial intelligence, machine learning, and product development.
Research assistant under Professor Parag Kulkarni (November 2023 — March 2026).
Teaching assistant / student assistant for Foundations of Python and IT Project Management (August 2024 — July 2025).
Founded the TIU Data Science and Analytics community and the Bangladesh Student Association.
Full-tuition scholarshipData ScienceAIDigital Business
Professional Certificate in Data Science
HarvardX / edX
Completed the nine-course Data Science Professional Certificate (credential issued November 2025).
Statistics, R, and machine learning coursework later used in research design and product decisions.
HarvardXData ScienceStatistics
Secondary and higher secondary education
Viqarunnisa Noon School and College
Science background before undergraduate study in Japan. This period also included early student leadership and education-community work.
ScienceBangladesh
Current status
After completing her bachelor’s degree in March 2026, Mayesha has been teaching English in Saitama while continuing independent research, academic writing, and product work through The Abroad Company. She is preparing MASc applications for Fall 2027.
Research Interests
Mayesha’s research experience began with applied NLP and machine-learning research under Professor Parag Kulkarni at Tokyo International University. Her work included text summarization, knowledge graphs, human-resource text analysis, patent summarization, low-resource NLP, and machine-learning applications. Her current research direction extends from technical AI development toward human-AI interaction and real-world evaluation. She is interested in how people interpret, trust, and respond to AI-supported decision systems, and whether those systems improve task completion, user behavior, and meaningful outcomes.
Human-AI interaction and decision-making
How people interpret, trust, and act on AI-generated guidance when the decision is consequential.
Human-AI InteractionTrustDecision Support
Real-world evaluation of intelligent systems
Whether AI systems improve decisions, task completion, trust, and access to opportunity — not only benchmark scores.
EvaluationUser BehaviorEducational Technology
Language models and educational NLP
Writing assessment, retrieval-augmented generation, knowledge-graph applications, and personalized language-based tools.
NLPLLMsAESKnowledge Graphs
Research methods
Methods Mayesha has used in papers and product research. Product observation is not listed as a formal human-subjects study.
Controlled feature isolation
Shuffled-label controls
Random-boundary controls
Random-feature controls
Bootstrap confidence intervals
Ablation
Human evaluation
Surveys
Interviews
Usability testing
User studies
Post-use feedback
Randomized feature experiments
Research experience
Research assistant
Professor Parag Kulkarni’s Research Lab
Undergraduate research assistant in natural language processing, text mining, machine learning, knowledge graphs, and applied artificial intelligence.
Conducted undergraduate research under Professor Parag Kulkarni in natural language processing, text mining, machine learning, knowledge graphs, and applied artificial intelligence.
Participated in weekly research meetings, research planning, idea development, study design, and academic writing.
Contributed to research on extractive and abstractive summarization, sentiment analysis, trend analysis, knowledge graphs, and NLP for low-resource languages.
Co-authored published research on graph-based text summarization for human resource management tasks.
Co-authored research on augmenting patent summarization with large language models and knowledge graphs, evaluated using automatic metrics and human assessment.
Developed independent research experience by initiating and leading an automated essay-scoring project during the final year of the degree.
NLPMachine learningKnowledge graphsUndergraduate research
Independent researcher
Human-AI interaction and real-world evaluation
Continues independent research on how people use AI-enabled tools in real products.
Asks whether recommendations, explanations, personalization, and human support change decisions, trust, and task completion.
Does not treat product observation as a completed formal human-subjects study unless ethics procedures are later documented.
Human-AI interactionEvaluationNLP
Ongoing Research
Ongoing Research
Evaluating AI support inside study-abroad products
A research direction on whether recommendations, explanations, personalization, and human support change how people decide, trust a tool, finish a task, or ask for help. Her current thesis work designs a context-aware personalization framework for AI agents: short- and long-term memory, a planner that suggests the next step, and memory viewers users can see and edit. This is work in design and observation, not a completed formal human-subjects study.
Role
Independent researcher
Current stage
Active reading, question-forming, and experiment design
Automated Essay Scoring with Availability Signals and Genetic Algorithms: The RubriQ Framework
Combines DeBERTa-v3-base, availability-inspired essay signals, and genetic-algorithm fusion. The genetic algorithm improved mean held-out QWK from 0.7545 to 0.7635 and beat the baseline on all six prompts.
Role
Lead researcher and first author
Methods
DeBERTa-v3 · Genetic algorithms · Availability features · QWK
What Makes Essay Structure Useful for Automated Scoring? A Document-Engineering Study of Boundary Geometry and Rhetorical Transitions
A predictive isolation study of whether discourse-derived document structure adds value beyond essay text, surface features, and component counts on PERSUADE 2.0. The complete structural model improved held-out QWK from 0.8361 to 0.8488. The study used controlled feature isolation, shuffled-label controls, random-boundary controls, random-feature controls, and bootstrap confidence intervals. This is not a causal study.
Survey of Graph-Based Text Summarization for HRM Tasks
Reviews graph-based text summarization methods for human resource management tasks and synthesizes the main approaches, applications, and research directions.
NLPIR 2024 · Proceedings of the 8th International Conference on Natural Language Processing and Information Retrieval · pp. 380–387
Role
Co-author
Methods
Literature Review · Graph-Based Summarization · NLP · HRM
Augmenting Patent Summarization Using a Large Language Model with a Knowledge Graph
Combines LLaMA 3 with patent knowledge graphs and evaluates the generated summaries through ROUGE and human assessment. Human evaluators preferred the knowledge-graph summaries in most tested patent cases, although the baseline achieved higher ROUGE scores.
LKM@IJCAI 2024 · First International OpenKG Workshop: Large Knowledge-Enhanced Models · pp. 1–13
Mayesha’s public writing includes beginner-friendly essays on artificial intelligence and an evolving research notebook where she records papers, questions, experiment ideas, and reflections.
Published Essays
LEARNING IN PUBLIC
Short Blogs on AI & Technology
These essays document how Mayesha learned technical ideas by explaining them in simple language and connecting them to tools, experiments, and products she was building. Together, they trace a path from foundational data science concepts to neural networks, language models, and applied AI systems.
Supported undergraduate courses in Foundations of Python, IT Project Management, and related information-technology coursework.
Assisted classes of up to 150 students from more than 120 countries.
Helped students with programming exercises, presentations, attendance, class activities, and course-related questions.
Adapted explanations to different levels of technical knowledge, communication styles, and learning needs.
Supported students in understanding Python fundamentals, project-management concepts, and practical technology applications.
TeachingAcademic supportPython
Product and professional experience
Full-time English teacher
Maple Inc.
Teaches English full-time to Japanese professionals and Japanese children.
Plans, delivers, and revises monthly lessons based on learner progress and classroom observation.
Uses games, activities, and adaptive instruction to support different ages, attention spans, proficiency levels, and learning styles.
Adjusts teaching methods based on student engagement and observed learning needs.
English teachingJapan
Co-founder and product lead
The Abroad Company
Co-founded The Abroad Company and leads products that support students through study-abroad and international applications. The co-founder role is dated October 2025. AbroadMates itself began earlier, in 2022.
Leads product strategy, user experience, research direction, and early-stage operations.
Launched AbroadMates, a study-abroad mentorship platform for paid 1:1 conversations.
Leads ApplicationMate, an AI-supported application-planning platform for deadlines, essays, and scholarships.
Leads an 11-person distributed team across Japan, the United States, Canada, Bangladesh, and Italy.
Co-founderProduct leadershipStudy abroad
Data analyst and content marketing intern
Guidable Inc.
Designed internal surveys, collected data, and used R for analysis.
Researched sources, drafted and edited articles, and published to WordPress with SEO settings.
InternshipData analysisContent
Human-AI product research
Mayesha studied how users navigated the products, where they became confused, when they stopped responding, when they requested human assistance, and how feature changes affected completion, bookings, subscriptions, tool usage, and feedback. She does not claim that the products improved school admissions; that outcome has not been measured here.
— Approximately 50 AbroadMates users and mentors
— 10 closed-cohort ApplicationMate applicants
— 856 chatbot participants
— Surveys
— Interviews
— Usability testing
— User studies
— Post-use feedback
— Randomized feature experiments
Users
Approximately 1,500
Booked sessions
More than 2,000
Mentors
210
Universities
Approximately 2,700
Programs
Approximately 157,000
These are current approximate figures. Booked sessions are sessions, not users.
Remote collaboration
Mayesha leads an 11-person distributed team across Japan, the United States, Canada, Bangladesh, and Italy. The team uses a shared portal, holds two meetings each week, and works primarily through asynchronous coordination.
Mayesha reviews weekly task completion, work activity, hours, and efficiency to improve the team’s systems and workflow. This is operational leadership, not a formal human-subject study.
Products & Research Platforms
Mayesha co-founded The Abroad Company and works on products that support students through study-abroad decisions. The co-founder role is dated October 2025; AbroadMates began in 2022.
These products create real-world environments for studying how human and AI support shape decisions and outcomes.
Leadership and community engagement
Founder and former president
TIU Data Science and Analytics Club
Founded a student community for data science, analytics, and AI; later the department’s student association.
Built a level-based curriculum with faculty; more than 70 students completed the pathway.
FounderData scienceStudent leadership
Founder
Bangladesh Student Association of TIU
Founded the association because no Bangladeshi student community existed on campus.
Helped incoming students and organized cultural festivals for four years.
FounderCampus community
Founder and former president
Women Opportunities
Founded a community that shared educational, professional, scholarship, and leadership opportunities with women. The work is currently paused. She may return to it later.
CommunityLeadershipWomen
Founder
Superwoman: A She Learning Platform
The e-learning initiative she started so women could learn practical business skills.
FounderLearning
Divisional coordinator
English Olympiad
Dhaka divisional coordinator, April 2017 — September 2022. Head of Sponsorship, November 2018 — January 2022.
CoordinationStudent engagement
Educational content developer
National Curriculum and Textbook Board, Bangladesh
Developed assignments for Bangladesh’s online education and evaluation during COVID-19.
CurriculumBangladesh
Project coordinator
Worldwide Organization for Charity
Volunteered, then helped plan programs including an unfinished coding initiative for children.
Community service
Awards and scholarships
Scholarships and awards.
TIU 100% Tuition Reduction Scholarship
Tokyo International University
Full-tuition undergraduate scholarship covering the Digital Business and Innovation degree.
Monbukagakusho Honors Scholarship for Privately-Financed International Students
Japan Student Services Organization (JASSO)
Honors scholarship for privately-financed international students.
Leadership Award
English Olympiad
Leadership award from the English Olympiad.
Technical skills
Research methods
How Mayesha designs and evaluates work.
Feature isolation · Control conditions · QWK evaluation · Human evaluation · Surveys and interviews · Usability testing
AI and NLP
Models and techniques she has used in papers and products.