mentors_old_style.qmd

---
title: "Meet Our Team Mentors"
format:
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---

Meet our talented team mentors! They will be mentoring the participant teams competing in the event.

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</style>

## Super Mentors {#super-mentors}

### Moses Chan {#moses-chan .mentor-anchor}

::: {.guest-card .super-mentor .right}
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![](images/moses.jpg){alt="Moses Chan"}
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<div class="guest-label">Super Mentor</div>

<div class="guest-name">Moses Chan</div>

<div class="guest-role">Assistant Professor of Instruction, IEMS, Northwestern University</div>

Moses co-directs the Minor in Machine Learning & Data Science. His research focuses on developing efficient algorithms at the intersection of statistical theory, computer modeling, and the physical sciences, with particular emphasis on Bayesian computation and data science education in engineering.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

He holds a Ph.D. in Industrial Engineering and Management Sciences from Northwestern University. He is the recipient of the 2025/26 Searle Fellowship.

Chan is an active contributor to the NSF CSSI Framework for Bayesian Analysis of Nuclear Dynamics, developing and maintaining the open-source packages surmise and LCGP. In Summer 2025, he collaborated as a Visiting Researcher on projects quantifying parameter importance in numerical physics models at Chalmers University of Technology in Gothenburg, Sweden.

**Mentorship Style:** Chan believes progress matters more than perfection. He works closely with students to build a genuine understanding of their data problems — encouraging them to question assumptions, communicate findings clearly, and think critically at every step. His goal is to make sure students feel supported as they tackle real-world challenges together.

</div>
</details>
:::

### Shengbin Ye {#shengbin-ye .mentor-anchor}

::: {.guest-card .super-mentor .left}
::: {.guest-photo}
![](images/shengbin.jpg){alt="Shengbin Ye"}
:::

<div class="guest-label">Super Mentor</div>

<div class="guest-name">Shengbin Ye</div>

<div class="guest-role">Assistant Professor of Instruction, Department of Statistics and Data Science, Northwestern University</div>

Shengbin co-instructs the undergraduate data science curriculum and co-advises the MS program in Statistics and Data Science. He is passionate about making complex data easy to understand. His research focuses on symbolic regression—a way of teaching computers to find simple, human-readable math equations that explain patterns in data. By combining statistical theory with efficient algorithms, he helps turn "black box" models into transparent insights that anyone can interpret.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

Shengbin holds a Ph.D. in Statistics from Rice University. He joined the Department of Statistics and Data Science in September 2025. His research background includes work on high-dimensional regression and nonparametric variable selection. He is an advocate for open-source software and reproducible research, frequently working with R and Python to solve complex data challenges.

**Mentorship Style:** Shengbin believes in the iterative nature of data science. He encourages students to view model building as a process of continuous refinement rather than a single destination. He is an active listener who helps students think critically about their evidence, guiding them to bridge the gap between complex statistical results and persuasive, high-level narratives.

</div>
</details>
:::

### Shreeya Behera {#shreeya-behera .mentor-anchor}

::: {.guest-card .super-mentor .right}
::: {.guest-photo}
![](images/shreeya.jpg){alt="Shreeya Behera"}
:::

<div class="guest-label">Super Mentor</div>

<div class="guest-name">Shreeya Behera</div>

<div class="guest-role">Assistant Professor of Instruction, Department of Statistics and Data Science, Northwestern University</div>

Before joining Northwestern, Shreeya was a Data Scientist at Pandora Bio. She is also a passionate educator and deeply interested in using data science to improve education and student mental health.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

Shreeya received her PhD in Mathematics and a minor in Computer Science from The Ohio State University in 2024. Her research spans combinatorics, graph theory, and machine learning. At Pandora Bio, she built machine learning models for early detection of stress and anxiety triggers in college students, contributing to work at the intersection of data science, mental health, and education.

**Mentorship Style:** She is a careful listener who takes the time to understand exactly where a student is struggling before offering guidance. She focuses on strengthening fundamentals and explaining concepts in a way that is clear, approachable, and tailored to each student’s level of experience.

</div>
</details>
:::

## Mentors {#mentors}

### Karthik Prabhu {#karthik-prabhu .mentor-anchor}

::: {.guest-card .left}
::: {.guest-photo}
![](images/karthik.jpg){alt="Karthik Prabhu"}
:::

<div class="guest-label">Mentor</div>

<div class="guest-name">Karthik Prabhu</div>

<div class="guest-role">PhD graduate, UC Davis</div>

Karthik is a recent PhD graduate in Physics from UC Davis, where his work focused on cosmology, machine learning, and statistical modeling. He has experience applying machine learning techniques to real-world data, and currently works in fraud analytics, building models for detection and risk assessment.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

Karthik is an AI enthusiast and enjoys keeping up with breakthroughs in foundational models. He has worked on topics ranging from Bayesian inference, image processing, time-series analysis, anomaly detection, and generative AI.

**Mentorship Style:** Karthik encourages curiosity-driven learning and is passionate about helping others grow in their data science and machine learning journey. He asks questions to help the mentees think through the problems and build confidence in their problem-solving skills.

</div>
</details>
:::

### Harvey Wang {#harvey-wang .mentor-anchor}

::: {.guest-card .right}
::: {.guest-photo}
![](images/harvey.png){alt="Harvey Wang"}
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<div class="guest-label">Mentor</div>

<div class="guest-name">Harvey Wang</div>

<div class="guest-role">Corporate Strategy and Development Analyst, Molex</div>

Harvey is a recent graduate of Northwestern with majors in Data Science and Economics and a minor in Comparative Literature. He builds internal data tools and designs go-to-market strategies for AI-driven data center infrastructure.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

He has also participated in a Northwestern ML research team where he trained neural networks to classify ocular cancer. Additionally, Harvey has worked with Chicagoland nonprofits to manage large-scale donor data and identify high-impact retention tactics. He is experienced in data structures, statistical modeling, and market sizing. Harvey is passionate about discussing ML concepts and helping teams bridge the gap between technical analysis and executive-level strategy.

**Mentorship Style:** Harvey is creative, communicative, and evidence-driven, focusing on impactful modeling and clear data storytelling. He is an active listener who enjoys helping teams translate complex outputs into persuasive, high-level narratives that drive decision-making.

</div>
</details>
:::

### Jeffrey Yuan {#jeffrey-yuan .mentor-anchor}

::: {.guest-card .left}
::: {.guest-photo}
![](images/jeffrey.jpg){alt="Jeffrey Yuan"}
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<div class="guest-label">Mentor</div>

<div class="guest-name">Jeffrey Yuan</div>

<div class="guest-role">Fourth-year BS/MS Student in Statistics and Data Science, Northwestern University</div>

Jeffrey is passionate about data science, machine learning, and AI, and currently works as a Data Scientist at CME Group. His work has explored topics such as graph neural networks, recommendation systems, LLM chain-of-thought reasoning, and agentic AI tools for complex data workflows.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

On campus, Jeffrey’s research focuses on applying statistical and machine learning methods to problems in drug discovery and medical AI, including improving reasoning and counterfactual analysis in large language models. He also enjoys teaching and mentoring students in statistics and data science and has served as a teaching assistant for Northwestern’s Data Science sequence and Advanced Machine Learning courses. Outside of data science, he enjoys playing basketball, swimming, and exploring new food spots around Chicago.

**Mentorship Style:** At DataFest, Jeffrey is excited to collaborate with different teams, dive into new datasets, and uncover the interesting stories hidden in data.

</div>
</details>
:::

### Jake Miller {#jake-miller .mentor-anchor}

::: {.guest-card .right}
::: {.guest-photo}
![](images/jake.jpg){alt="Jake Miller"}
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<div class="guest-label">Mentor</div>

<div class="guest-name">Jake Miller</div>

<div class="guest-role">Data Science Senior, Northwestern University</div>

Throughout his college career, Jake has taken many classes in the Statistics department and has especially enjoyed his coursework in machine learning techniques.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

Some projects he has worked on include building and quantizing a CNN model to create a lightweight word detection model and building a dashboard to help break down call data for a non-profit law firm. Though he started full-time work in September, he is currently working on a personal project to build an NBA salary cap manager application.

**Mentorship Style:** As a mentor, Jake hopes to be a great sounding board for his mentees to bounce ideas off of. Jake also loves to talk more about his school and career path to give insights in any way and place that he can.

</div>
</details>
:::

### Kyle Williams {#kyle-williams .mentor-anchor}

::: {.guest-card .left}
::: {.guest-photo}
![](images/kyle.jpg){alt="Kyle Williams"}
:::

<div class="guest-label">Mentor</div>

<div class="guest-name">Kyle Williams</div>

<div class="guest-role">Software Engineer, Lakeview Investment Group</div>

Kyle earned his BS in Computer Science with a Minor in Data Science in June 2023, followed by an MS in Computer Science in June 2024. While he took a majority of his courseload in the CS Department, it is the application of math, statistics, and science through code that is the most interesting to him.

<details class="guest-details">
<summary>Read more</summary>

<div class="details-content">

Kyle has always been drawn to Machine Learning and Data Analysis. Being able to understand and communicate about data makes him feel powerful and responsible.

As a part of his master’s, Kyle completed a Thesis on LLMs (Large Language Models), where he augmented the attention mechanism to use Euclidean distance instead of dot-product to improve the performance of small models on OpenBookQA by 14%. Currently, Kyle is helping build high-speed, real-time dashboards and trading systems to display important statistics and execute orders when certain triggers are reached.

**Mentorship Style:** Kyle’s greatest strength as a mentor is his patience. As a triplet, Kyle had to share everything – even a birthday – and it’s made him a great listener, effective mediator and strong communicator. Kyle loves talking about code, and he hopes to be a resource for any student who wants to learn more about what it means to be a Computer Scientist in industry. Outside of tech, Kyle’s also a big fan of wrestling and football—and always happy to connect over either!

</div>
</details>
:::