The Research Experience Universities are Looking For
University admissions offices (especially for STEM programs) increasingly expect applicants to demonstrate genuine research experience, not just test scores and extracurriculars. Immersion gives your child exactly that: a documented, reproducible research project with a real faculty problem, a live GitHub repository, and a publication-quality technical report.
Every deliverable is built in the student's own voice, with their own code, using real data. It's the kind of credential that differentiates an application, and the kind of experience that builds lasting confidence in research and technical work.
Free Info & Orientation Session on May 1st! This is open to prospective students and parents. We walk through the program structure, weekly schedule, and what to expect, and answer every question before the application deadline.
80%
Target Completion Rate
6/10
Portfolio-Ready Projects Target
4
Faculty Research Partners
Publication-Quality Technical Report
Analysis-based projects will be prepared for TRB conference submission (August 1 deadline). Tool-focused projects follow SoftwareX format. Built week by week alongside a live GitHub repository.
Real Transportation AI Challenge
Each student works on their own faculty-generated problem with a real dataset. 10 students, 10 unique problems, and no shared projects.
Letter of Distinction + Portfolio Page
Top performers receive a Letter of Distinction. Every student leaves with a live Coltie portfolio URL.
The Research Experience Universities are Looking For
University admissions offices (especially for STEM programs) increasingly expect applicants to demonstrate genuine research experience, not just test scores and extracurriculars. Immersion gives your child exactly that: a documented, reproducible research project with a real faculty problem, a live GitHub repository, and a publication-quality technical report.
Every deliverable is built in the student's own voice, with their own code, using real data. It's the kind of credential that differentiates an application, and the kind of experience that builds lasting confidence in research and technical work.
Parent Orientation Session on May 12th! This is open to prospective students and parents. We walk through the program structure, weekly schedule, and what to expect, and answer every question before the application deadline.
80%
Target Completion Rate
6/10
Portfolio-Ready Projects Target
4
Faculty Research Partners
Research Output
Publication-Quality Technical Report
Analysis-based projects will be prepared for TRB conference submission (August 1 deadline). Tool-focused projects follow SoftwareX format. Built week by week alongside a live GitHub repository.
Faculty Problem
Real Transportation AI Challenge
Each student works on their own faculty-generated problem with a real dataset. 10 students, 10 unique problems, and no shared projects.
Recognition
Letter of Distinction + Portfolio Page
Top performers receive a Letter of Distinction. Every student leaves with a live Coltie portfolio URL.
GutHub Repository
Every project published as open-source code on GitHub under an MIT license: live, forkable, and can be linked on every university application the student submits.
Technical Report
Analysis-based projects prepared for TRB conference submission (Aug 1 deadline); tool-focused projects in SoftwareX format. Built section by section over 9 weeks.
Demo Video
3–5 minute recorded presentation showcased on Demo Day.
Coltie Profile Page
A permanent public URL featuring all outputs — linked on every application.
GitHub Repository
Every project published as open-source code on GitHub under an MIT license: live, forkable, and can be linked on every university application the student submits.
Technical Report
Analysis-based projects prepared for TRB conference submission (Aug 1 deadline); tool-focused projects in SoftwareX format. Built section by section over 9 weeks.
Demo Video + Coltie Profile Page
3–5 minute recorded presentation showcased on Demo Day.
A permanent public URL featuring all outputs — linked on every application.
Who Grow Is For
STEM Highschool Students ages 15-18
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Planning university applications for 2026–27.
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Prior Python experience and basic data science familiarity
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Intellectual curiosity and a high tolerance for working through hard problems matter more than prior research experience.
Early Undergraduates for Research Experience
First or second year students who want hands-on research before joining a formal lab. Immersion builds the foundational skills (Python, EDA, ML baselines, technical writing) that faculty look for.
Students Targeting Competitive STEM Programs
Applying to top engineering, CS, or data science programs in the US, UK, Canada, or Singapore. Immersion produces the kind of documented, reproducible research that admissions offices for these programs specifically look for.
The 8-10 Week Journey
Every student follows the same research arc on their own unique problem: problem framing → literature review → exploratory analysis → baseline models → improvement → showcase.
Each week has a defined deliverable, so progress is always visible and nothing is left to the last minute.
Week 1: Intensive Bootcamp
90 min daily class Mon–Fri. Python, data handling, visualization, and introductory ML. Every Thursday, students join the Coltie Grow guest speaker session. This grind serves as the foundation for every week that follows.
Weeks 5-6: Baseline Models
Implement ≥3 baseline models.
Build a rigorous comparison table of evaluation metrics. This is your scientific baseline! Everything in weeks 7–8 is measured against it.
Week 2: Problem Selection
Watch faculty videos, live Q&A, and rank your top choices.
Each student is matched to one of 10 unique faculty-generated problems. Understanding your research challenge deeply before touching code.
Week 7: Improvement Proposal
Diagnose limitations of your baselines. Propose a targeted, justified improvement. Faculty sign-off before implementation begins.
Week 3: Literature Review
Guided reading of 3–5 curated papers. Learn how to read academic literature efficiently. Identify prior methods and gaps your project will address.
Week 8: Final model Implementation
Implement your improvement. Run rigorous comparison against baselines.
The program's highest-value academic output.
Week 4: Exploratory Data Analysis
Profile your dataset, produce visualizations, and identify data quality issues. The EDA phase anchors all future modeling decisions.
Week 9: Finalization & Demo Day
Polish report and GitHub repo, record demo video, present on Demo Day to faculty, peers, and community.
Certificates issued. Letters of Distinction awarded to top 20–25%.
WEEK 1 - BOOTCAMP
90 min daily sessions (Mon–Fri) covering Python fundamentals, pandas, matplotlib, and introductory ML. Every Thursday, students join the Coltie Grow guest speaker session, which will include industry and research guests that run throughout the full program.
You leave Week 1 with a working notebook and your first dataset analyzed.
Python, Data Handling & Visualization
WEEKS 3-4 - RESEARCH
Learn to read academic papers efficiently. Profile your dataset, produce publication-quality visualizations, and identify data quality issues before touching a model.
Literature Review & Exploratory Data Analysis
WEEKS 5-6 - BASELINE MODELS
Implement ≥3 baseline models. Linear regression, logistic classification, a simple ML method.
Build a structured comparison table. This is the scientific foundation everything else builds on.
Regression, Classification & Model Comparison
WEEKS 7-8 - IMPROVEMENT
Diagnose your baseline's limitations.
Propose and implement a targeted improvement with rigorous justification. This is the program's highest-value academic output.
Model Improvement, Innovation & Justification
ALL WEEKS - PARALLEL TRACK
Each week you write one section of your technical report. Analysis-based projects will be prepared for submission to the TRB (Transportation Research Board) annual conference. Deadline will be August 1st.
Tool-development projects follow SoftwareX format. By the final week, the report is completed, and not turned in at the final minute in panic mode.
Technical Writing, Section by Section
WEEK 9 - SHOWCASE
Polish your repo, record a 3–5 minute demo video, and present to faculty, peers, and community on Demo Day.
Top students receive a Letter of Distinction.
GitHub, Demo Video & Demo Day
The 8-10 Week Journey
Every student follows the same research arc on their own unique problem: problem framing → literature review → exploratory analysis → baseline models → improvement → showcase.
Each week has a defined deliverable, so progress is always visible and nothing is left to the last minute.
Week 1: Intensive Bootcamp
90 min daily class Mon–Fri. Python, data handling, visualization, and introductory ML. Every Thursday, students join the Coltie Grow guest speaker session. This grind serves as the foundation for every week that follows.
Week 2: Problem Selection
Watch faculty videos, live Q&A, and rank your top choices. Each student is matched to one of 10 unique faculty-generated problems. Understanding your research challenge deeply before touching code.
Week 3: Literature Review
Guided reading of 3–5 curated papers. Learn how to read academic literature efficiently. Identify prior methods and gaps your project will address.
Week 4: Exploratory Data Analysis
Profile your dataset, produce visualizations, and identify data quality issues. The EDA phase anchors all future modeling decisions.
Weeks 5-6: Baseline Models
Implement ≥3 baseline models. Build a rigorous comparison table of evaluation metrics. This is your scientific baseline! Everything in weeks 7–8 is measured against it.
Week 7: Improvement Proposal
Diagnose limitations of your baselines. Propose a targeted, justified improvement. Faculty sign-off before implementation begins.
Week 8: Final model Implementation
Implement your improvement. Run rigorous comparison against baselines. The program's highest-value academic output.
Week 9: Finalization & Demo Day
Polish report and GitHub repo, record demo video, present on Demo Day to faculty, peers, and community. Certificates issued. Letters of Distinction awarded to top 20–25%.
Weekly Session Rhythm
Week 1 is an intensive daily bootcamp. 90 minutes every day. So, students arrive at Week 2 with a working technical foundation.
From Week 2 onwards, the rhythm is two sessions per week: a 90-minute class on Tuesday led by dedicated DS support, and a 60-minute progress presentation session where every student presents their individual update.
Dedicated DS support is also available for write-up review throughout the program. Students don't just get feedback on their code, they get feedback on how they're communicating their work.
Presenting weekly is non-negotiable — scientific communication is a skill, and you leave Immersion having practiced it eight times.
Week 1: Bootcamp
Mon - Fri (90min daily)
Python fundamentals, pandas, visualization, and an intro to ML
Thursday - Guest Speaker
Shared with Coltie Grow cohort. There will be industry & research guests throughout the program.
Weeks 2-9: Research Rhythm
Tuesday - 90min Class
Concept delivery & technical deep dive · led by dedicated DS support
Thursday - Guest Speaker
Shared with Coltie Grow cohort. Runs every week of the program.
Weekly - 60min Progress Presentations
Every student presents their individual update · Program Director feedback
Weekly Session Rhythm
Week 1 is an intensive daily bootcamp. 90 minutes every day. So, students arrive at Week 2 with a working technical foundation.
From Week 2 onwards, the rhythm is two sessions per week: a 90-minute class on Tuesday led by dedicated DS support, and a 60-minute progress presentation session where every student presents their individual update.
Dedicated DS support is also available for write-up review throughout the program. Students don't just get feedback on their code, they get feedback on how they're communicating their work.
Presenting weekly is non-negotiable — scientific communication is a skill, and you leave Immersion having practiced it eight times.
Week 1: Bootcamp
Python fundamentals, pandas, visualization, and an intro to ML
Mon - Fri (90min daily)
Thursday - Guest Speaker
Shared with Coltie Grow cohort. There will be industry & research guests throughout the program.
Weeks 2-9: Research Rhythm
Concept delivery & technical deep dive · led by dedicated DS support
Tuesday - 90min Class
Thursday - Guest Speaker
Shared with Coltie Grow cohort. Runs every week of the program.
Every project published as open-source code on GitHub under an MIT licence: live, forkable, and can be linked on every university application the student submits.
PUBLIC GITHUB REPOSITORY
3-5 MINUTE DEMO VIDEO
Every project published as open-source code on GitHub under an MIT licence: live, forkable, and can be linked on every university application the student submits.
PUBLICATION-QUALITY TECHINAL REPORT
Written section by section across 9 weeks. Analysis-based projects will be prepared for submission to the TRB Annual Conference (Transportation Research Board)
With the deadline being August 1st, this gives students a real submission target.
Tool-development projects follow SoftwareX format.
Either way: introduction, related work, methodology, experiments, results, discussion, conclusion. The real writing standard, not a school template.
A permanent, public-facing page on your Coltie profile linking to all four deliverables. Shared as a single URL on university applications, internship applications, and LinkedIn. Your research, visible to anyone who looks.
COLTIE PROFILE PAGE
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PERMANENT ALUMNI NETWORK
The community doesn't end when the program does. Your Coltie network stays with you through applications, internships, and beyond.
Your Built-In Community
Every Immersion student gets free access to the Coltie app. This is a private cohort space where you join peers going through the same process at the same time. This community is projected to be a space that you and others can collaborate, network, and get ahead on your various career paths.
INDIVIDUAL + COHORT COMMUNITY
Each student has their own project channel, plus a shared cohort space where all 10 students collaborate, share findings, and support each other across different problems.
GRAD MENTOR ACCESS
Volunteer graduate student mentors embedded in the community. These are people who have done this research and are happy to help you navigate it!
Real Outcomes for Every Student
Recognition in Immersion is based on output quality. All students receive a certificate and a live portfolio page. Top performers receive a credential that stands out in any application.
ALL STUDENTS
Certificate of Participation
A formal certificate recognizing completion of the Immersion program, co-signed by the Program Director and Faculty Partners. Shareable digitally and in print.
EXCEPTIONAL WORK
Research Collaboration Pathway
Exceptional projects may be flagged for discretionary faculty follow-up or research collaboration. Not guaranteed — but students who produce genuinely strong work sometimes find a door opening that wasn't there before.
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TOP 2-3 STUDENTS
Letter of Distinction
A formal letter from the Program Director and Faculty evaluating the quality of the research, the technical rigor, and the communication of results.
This kind of letter gets read.
INDIVIDUAL + COHORT COMMUNITY
Each student has their own project channel, plus a shared cohort space where all 10 students collaborate, share findings, and support each other across different problems.
PERMANENT ALUMNI NETWORK
The community doesn't end when the program does. Your Coltie network stays with you through applications, internships, and beyond.
GRAD MENTOR ACCESS
Volunteer graduate student mentors embedded in the community. These are people who have done this research and are happy to help you navigate it!
ALL STUDENTS
Certificate of Participation
A formal certificate recognizing completion of the Immersion program, co-signed by the Program Director and Faculty Partners.
Shareable digitally and in print.
EXCEPTIONAL WORK
Research Collaboration Pathway
Exceptional projects may be flagged for discretionary faculty follow-up or research collaboration. Not guaranteed — but students who produce genuinely strong work sometimes find a door opening that wasn't there before.
Letter of Distinction
A formal letter from the Program Director and Faculty evaluating the quality of the research, the technical rigor, and the communication of results.
This kind of letter gets read.
TOP 2-3 STUDENTS
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Built and Run by Researchers
Immersion is designed and led by people who do research, not people who teach about research. Every student gets dedicated DS support from Zeba, multiple bookable office hour slots per week with both Dr. Tingting Huang and Dr. Anuj Sharma, and faculty report reviews throughout to keep every project on track.
Anuj Sharma
Founder + Program Director
Anuj is the Pitt-Des Moines Inc. Professor of Civil Engineering at Iowa State University and founder of Coltie.
He holds a PhD in Transportation Engineering from Purdue University and has an H-index of 40, 150+ publications and proceedings, 3 patents, and over $29M in sponsored research.
He reviews all submitted reports to ensure the research direction is sound and holds multiple bookable office hour slots each week in which students can reserve time directly through the program portal whenever they need guidance.
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Sanjeda Akter (Zeba)
Data Science Instructor & Primary DS Support
Zeba is an MS student in Artificial Intelligence at Iowa State University (graduating May 2026), with a BS in Computer Science & Engineering from BRAC University (Highest Distinction, 3.81/4.00).
She has co-authored publications at ECAI 2025, EMNLP 2025, CVPR 2026, IEEE ITS Transactions, and ACL 2026, with research spanning agentic AI systems, trustworthy machine learning, and LLMs for transportation and computer vision.
She leads all dedicated DS support for Immersion! Weekly Tuesday sessions, hands-on technical guidance, and write-up review throughout the 9 weeks. Students working through technical blocks or struggling with their report sections work directly with Zeba.
Dr. Tingting Huang
Research Methodology Advisor
Reviews all submitted reports alongside Dr. Sharma to ensure each project is heading in the right direction.
She also holds multiple bookable office hour slots each week. Students can reserve time directly to get guidance on research approach and problem framing, interpret findings, and pressure-test whether they're asking the right questions of their data.
Faculty Partners (3-4 Professors) + University Graduate Mentors
Problem Generators & Domain Experts | Peer Researchers
Each faculty partner contributes a real transportation AI problem from their active research agenda, a verified public dataset, and two short videos (A Lab Overview and a Problem Definition). Optional live Q&A participation in Week 2. No ongoing commitment required.
Graduate students from partner universities are available as community mentors through the Coltie app. They're not required to be on every call — they're there because they want to be. That's what makes their input valuable: candid, peer-level perspective on what it actually looks like to work in a research lab, navigate grad school applications, and communicate technical work to real audiences.
For Parents
Every university admissions office in the US, UK, Canada, Australia, and Singapore now has AI-detection tools. Applications with AI-drafted personal statements are increasingly flagged or rejected outright.
Your child deserves to stand out quickly, not be passed up quickly.
Parent Orientation will be on May 12th at 2pmCST. A 60-minute orientation for all accepted students and their parents a week before the program starts. Parents who attend are significantly less likely to request refunds.
The Ultimate Skill-Builder for Your Student
In 8 Weeks, your child will jumpstart their future career, creating...
Personal Web Portfolio
AI Prompt Portfolio
College Fit Dashboard
60-Second Video Introduction
Ethical AI Usage Framework
Draft Personal Statement (SOP)
Admissions Strategy Roadmap.
TOP 2-3 STUDENTS
Letter of Distinction
A formal letter from the Program Director and Faculty evaluating the quality of the research, the technical rigor, and the communication of results.
This kind of letter gets read.
EXCEPTIONAL WORK
Research Collaboration Pathway
Exceptional projects may be flagged for discretionary faculty follow-up or research collaboration. Not guaranteed — but students who produce genuinely strong work sometimes find a door opening that wasn't there before.
Every Student Earns Something Real
Recognition in Immersion is based on output quality, not effort alone. All students receive a certificate and a live portfolio page. Top performers receive a credential that stands out in any application.
ALL STUDENTS
Certificate of Participation
A formal certificate recognizing completion of the Immersion program, co-signed by the Program Director and Faculty Partners. Shareable digitally and in print.
Program Tuition
$1,250
per student | 9 weeks
9 weeks of structured research training
Faculty-generated real-world AI problem
Week 1 intensive bootcamp (Python + ML)
Dedicated DS support — instruction, technical guidance & write-up review
Bookable office hours with Dr. Huang & Dr. Sharma every week
Faculty report reviews to keep research on track
Weekly 60 min progress presentation (every student, every week)
TRB conference submission attempt (Aug 1) or SoftwareX report
Public GitHub repository (structured)
3–5 min demo video + Demo Day presentation
COLTIE portfolio page (permanent public URL)
University graduate mentor access via Coltie app
Free Coltie profile (your permanent research identity)
Certificate of Participation
Letter of Distinction (given to the top 20–25% of students)