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Saurabh Rai Mathematics, Physics and Computer Science
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I hold a Master’s degree in Physics and work at the intersection of physics, data science and machine learning. Currently I am doing PhD in experimental high energy physics and a member of the CERN collaboration. I offer part-time tutoring that combines strong conceptual foundations with hands-on problem solving and practical coding, aimed at school, undergraduate and early-graduate students.
What I teach
Physics: classical mechanics, electromagnetism, modern physics, and problem-solving techniques for competitive and board exams.
Mathematics: algebra, calculus, linear algebra, probability & statistics, and mathematical methods used in physics and ML.
Machine Learning & Computer Science: fundamentals (supervised/unsupervised learning, model selection), deep learning basics, practical model building with Python (PyTorch / TensorFlow / Keras), and project-level guidance (data preprocessing, training, evaluation).
How I teach
Concept first: I make sure you understand the why before the how — deriving from first principles where useful.
Active problem solving: step-by-step walkthroughs of textbook problems, exam-style questions and real datasets.
Practical coding: live coding sessions and assignments to implement algorithms and models end-to-end.
Visual explanations: intuitive diagrams and animations (where helpful) to make abstract concepts concrete.
Custom plans: lessons are tailored to your level, goals and timeline — exam prep, coursework support, or project mentorship.
What students get
Clear conceptual understanding, faster problem-solving skills and improved exam performance.
For CS students, practical experience in building and evaluating ML models, including reproducible code and debugging strategies.
Regular feedback, worked solutions and a focused roadmap to reach your goals.
Logistics
Mode: online, interactive lessons (screen sharing + problem solving + coding).
Availability: part-time / flexible scheduling.
Lesson format: single lessons, short packages, or project-oriented mentorship. Trial session available to set learning goals and a plan.
What I teach
Physics: classical mechanics, electromagnetism, modern physics, and problem-solving techniques for competitive and board exams.
Mathematics: algebra, calculus, linear algebra, probability & statistics, and mathematical methods used in physics and ML.
Machine Learning & Computer Science: fundamentals (supervised/unsupervised learning, model selection), deep learning basics, practical model building with Python (PyTorch / TensorFlow / Keras), and project-level guidance (data preprocessing, training, evaluation).
How I teach
Concept first: I make sure you understand the why before the how — deriving from first principles where useful.
Active problem solving: step-by-step walkthroughs of textbook problems, exam-style questions and real datasets.
Practical coding: live coding sessions and assignments to implement algorithms and models end-to-end.
Visual explanations: intuitive diagrams and animations (where helpful) to make abstract concepts concrete.
Custom plans: lessons are tailored to your level, goals and timeline — exam prep, coursework support, or project mentorship.
What students get
Clear conceptual understanding, faster problem-solving skills and improved exam performance.
For CS students, practical experience in building and evaluating ML models, including reproducible code and debugging strategies.
Regular feedback, worked solutions and a focused roadmap to reach your goals.
Logistics
Mode: online, interactive lessons (screen sharing + problem solving + coding).
Availability: part-time / flexible scheduling.
Lesson format: single lessons, short packages, or project-oriented mentorship. Trial session available to set learning goals and a plan.
Subjects
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Physics Grade 1-Masters/Postgraduate
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Science Grade 1-Grade 12
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Mathematics Grade 1-Bachelors/Undergraduate
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Machine Learning Beginner-Intermediate
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C++ and Data Structures Beginner-Intermediate
Experience
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Junior Research Fellow (Aug, 2024–Jul, 2025) at Indian Institute of Technology Jodhpur, RAJASTHAN
Conducted high impact research in the domain of quantum information, machine learning and experimental particle physics.
Education
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PhD in Experimental Particle Physics and Machine Learning (Jul, 2025–now) from Indian Institute of Technology Kanpur
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M. Sc. Physics (Jul, 2022–Jul, 2024) from INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI–scored 8.46/10
Fee details
₹15/hour (US$0.16/hour)
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IIT, Kalyanpur, Kanpur, Uttar Pradesh 208016, India
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Can travel:
No
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- Last login: Sep 12, 2025
- Registered: Sep 12, 2025
- Total Teaching exp: 1.0 yrs.
- Teaches online: Yes
- Online Teaching exp: 1.0 yrs.
- Teaches at student's home: No
- Homework Help: Yes
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Gender: Male
- Works as: Individual teacher
- Speaks: English, Hindi
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Fee:₹15/hour(USD 0.16/hour)
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