1^st lesson free

Aadirupa

Rate €26
Response 2h
Students
Number of students Aadirupa has accompanied since arriving at Superprof
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Number of students Aadirupa has accompanied since arriving at Superprof

€26/h

1^st lesson free

Maths
Algebra
Arithmetic
Statistics
Algorithms

From Confused to Confident — Basic Math Tutoring to master ML/AI basics by a PhD Professor

Maths
Algebra
Arithmetic
Statistics
Algorithms

Lesson location

- online

About Aadirupa

Aadirupa Saha has been an Assistant Professor in the Department of Computer Science at the University of Illinois Chicago (UIC) since Fall 2025. She is a member of the UIC CS Theory group, as well as IDEAL Institute. Prior to this, she was a Research Scientist at Apple MLR, working on Machine Learning theory. She completed her postdoctoral research at Microsoft Research (NYC) and earned her PhD from the Indian Institute of Science (IISc), Bangalore.

Saha's primary research focuses on AI alignment through Reinforcement Learning with Human Feedback (RLHF), with applications in language models, assistive robotics, autonomous systems, and personalized AI. At a high level, her work aims to develop robust and scalable AI models for designing prediction systems under uncertain and partial feedback.

[Optional] Specifically, Saha is deeply motivated by the tremendous potential of AI to democratize learning—reshaping our current education system into a truly adaptive, accessible, and personalized experience for every learner! Driven by this transformative power of generative AI and language models, she envisions building the foundations for equitable, intelligent education systems that turn this vision into reality. Her research focuses on developing futuristic educational models by leveraging her expertise in AI alignment with human feedback, alongside tools from Machine Learning (Online Learning, Bandits, and RL theory), Optimization, Federated Learning, Differential Privacy, and Mechanism Design.

[Optional] Saha has been a part of several organizational efforts and tutorials over the last few years. Notably, she serves as the communication chair for RLC, 2026. Besides her community services include a keynote talk at DA2PL Conference, [NeurIPS, 2023] tutorial on Preference Learning, [UAI, 2023] tutorial on Federated Optimization, two tutorials at [ECML, 2022], [ACML, 2021], three ICML workshops [ICML, 2024], [ICML, 2023], [ICML, 2022], an IDEAL special program workshop, and two TTIC workshops [TTIC, 2023], [TTIC, 2022]. In addition, Saha has also served in several panel discussions and senior reviewing committees for major ML conferences.

About the lesson

TEACHING METHOD & TECHNIQUES
I believe math is not about memorizing formulas — it is about building intuition. My teaching approach is rooted in how I was trained as a researcher: understand the why before the how.
My core techniques: Concept-first teaching — I never start with formulas, I start with the idea behind them. Visual reasoning — I use diagrams, graphs, and geometric intuition to make abstract concepts tangible. Socratic questioning — I ask guiding questions so you arrive at the answer yourself, making it stick longer. Error analysis — I turn your mistakes into the most powerful learning moments. Real-world anchoring — I connect every topic to real applications such as statistics in data science, calculus in physics, and probability in AI.

A TYPICAL LESSON
First 5 minutes: I ask 2-3 quick questions to find exactly where your understanding breaks down. No wasted time.
Next 15 minutes: I re-explain the concept from scratch, the right way. Clean, simple, no jargon.
Next 20 minutes: We solve problems together. I do not solve for you — I guide you step by step until you can do it alone.
Last 10 minutes: You solve a problem independently while I watch. This is where real learning gets confirmed.
End of session: I tell you exactly what to practice before next session and what to expect next.

WHAT SETS ME APART
I am an Assistant Professor of Computer Science at the University of Illinois Chicago (UIC). I hold a PhD in Computer Science from the Indian Institute of Science (IISc) Bangalore, one of Asia's top research institutions. I was previously a Research Scientist at Apple Machine Learning Research and a Postdoc at Microsoft Research New York.
I have taught and mentored students at every level — undergraduate, masters, and PhD. My entire research career is built on mathematical rigor — probability, optimization, statistics, and linear algebra. This is my native language. I do not just teach math. I teach you how to think mathematically.

WHO THESE LESSONS ARE FOR
These lessons are perfect for you if you are a high school student struggling with algebra, trigonometry, or pre-calculus. A college freshman or sophomore taking Calculus I, II, or III. An engineering, science, or computer science student whose math foundations feel shaky. A data science or AI student needing to strengthen probability, statistics, or linear algebra. A graduate student brushing up on mathematical foundations. Someone self-studying math for a career switch into data science or AI.
Subjects I cover: Arithmetic, Pre-Algebra, Algebra I and II, Trigonometry, Pre-Calculus, Calculus I through III, Probability and Statistics, Linear Algebra, Discrete Mathematics, and Mathematical Foundations of ML and AI.
I am not the right fit if you want someone to do your homework for you, or if you are looking for quick answers without understanding. I am here for students who genuinely want to learn.

BIO
I am an Assistant Professor at the University of Illinois Chicago and a PhD graduate of IISc Bangalore, with prior experience as a Research Scientist at Apple and Postdoc at Microsoft Research. I specialize in making advanced math — calculus, statistics, probability, and linear algebra — clear, intuitive, and genuinely understandable for every type of learner. If you want to stop memorizing and start truly understanding math, I am the tutor for you.

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5 h: €130
10 h: €260

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This first lesson offered with Aadirupa will allow you to get to know each other and clearly specify your needs for your next lessons.

From Confused to Confident — Basic Math Tutoring to master ML/AI basics by a PhD Professor

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From Confused to Confident — Basic Math Tutoring to master ML/AI basics by a PhD Professor

Lesson location

About Aadirupa

About the lesson

Rates

Rate

Pack rates

online

free lessons

Aadirupa's Video

Other tutors in Maths

George

Denise

Kirsty

Teacher Antony

Rishabh

Muluye

Matthew

Richard

Riza Lyn

Chanelle

Zaid

Abdullahi

Fariha

Rita

Sneha

Julia

Ibukun

Mohammad Imran

Nicoletta

Emmanuel Sesugh

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