My Profile
I’m your SUPER TUTOR and dedicated mentor as you explore the world of mathematics. Equipped with a Stanford Bachelor’s degree in Mathematics and Economics, my love of numbers has motivated me to seek a Ph.D. in Economics at the same university. My academic journey has equipped me with a profound understanding of mathematical concepts making me a highly sought-after private math tutor.
I’m dedicated to helping students understand and appreciate math, especially those who love economics but find the subject difficult. My approach to tutoring is centered on providing students with individualized supervision and adjusting lessons to meet their unique requirements and learning preferences. Whether you’re attempting to navigate the complexities of statistics, calculus, or algebra, my expertise guarantees a thorough understanding of each subject.
I am not just a tutor; I am a mentor committed to helping my pupils develop their mathematical skills and gain confidence. I make tutoring a dynamic, exploratory experience by focusing on real-world applications and facilitating interactive sessions. Come along with me as we pursue mathematical excellence, where success becomes the norm and learning is an exciting experience.
I frequently work with ultra-high-net-worth families who need the best tutoring money can buy with absolute discretion. I only work with one or two pupils at a time.
If you are looking for the best math tutor who has a tremendous amount of experience teaching, you should reach out to me.
What do I teach?
High School
If you are a high school student, I can help you with
✔️Geometry
✔️Algebra
✔️Trigonometry
✔️Precalculus
✔️Statistics
College
If you are a math, statistics, or econ major at Stanford, UPenn, or Harvard, here is a list of courses I can expertly teach:
Stanford
Mathematics
- MATH 18 – Foundations for Calculus
- MATH 19 – Calculus
- MATH 19ACE – Calculus, ACE
- MATH 20 – Calculus
- MATH 20ACE – Calculus, ACE
- MATH 21 – Calculus
- MATH 21ACE – Calculus, ACE
- MATH 51 – Linear Algebra, Multivariable Calculus, and Modern Applications
- MATH 51ACE – Linear Algebra, Multivariable Calculus, and Modern Applications, ACE
- MATH 52 – Integral Calculus of Several Variables
- MATH 53 – Differential Equations with Linear Algebra, Fourier Methods, and Modern Applications
- MATH 56 – Proofs and Modern Mathematics
- MATH 61CM – Modern Mathematics: Continuous Methods
- MATH 62CM – Modern Mathematics: Continuous Methods
- MATH 62DM – Modern Mathematics: Discrete Methods
- MATH 63CM – Modern Mathematics: Continuous Methods
- MATH 63DM – Modern Mathematics: Discrete Methods
- MATH 75SI – Learn to Give a Math Talk
- MATH 77Q – Probability and gambling
- MATH 87Q – Mathematics of Knots, Braids, Links, and Tangles
- MATH 104 – Applied Matrix Theory
- MATH 107 – Graph Theory
- MATH 108 – Introduction to Combinatorics and Its Applications
- MATH 109 – Groups and Symmetry
- MATH 110 – Number Theory for Cryptography
- MATH 113 – Linear Algebra and Matrix Theory
- MATH 115 – Functions of a Real Variable
- MATH 116 – Complex Analysis
- MATH 117 – Advanced Complex Analysis
- MATH 118 – Mathematics of Computation
- MATH 120 – Groups and Rings
- MATH 121 – Galois Theory
- MATH 122 – Modules and Group Representations
- MATH 131P – Partial Differential Equations
- MATH 136 – Stochastic Processes (STATS 219)
- MATH 143 – Differential Geometry
- MATH 144 – Introduction to Topology and Geometry
- MATH 145 – Algebraic Geometry
- MATH 147 – Differential Topology
- MATH 148 – Algebraic Topology
- MATH 151 – Introduction to Probability Theory
- MATH 152 – Elementary Theory of Numbers
- MATH 155 – Analytic Number Theory
- MATH 158 – Probability and Stochastic Differential Equations for Applications (CME 298)
- MATH 159 – Discrete Probabilistic Methods
- MATH 171 – Fundamental Concepts of Analysis
- MATH 172 – Lebesgue Integration and Fourier Analysis
- MATH 173 – Theory of Partial Differential Equations
- MATH 175 – Elementary Functional Analysis
- MATH 205A – Real Analysis
- MATH 205C – Topics in Harmonic Analysis
- MATH 210A – Modern Algebra I
- MATH 210B – Modern Algebra II
- MATH 210C – Lie Theory
- MATH 215A – Algebraic Topology
- MATH 215B – Differential Topology
- MATH 215C – Differential Geometry
- MATH 216A – Introduction to Algebraic Geometry
- MATH 220A – Partial Differential Equations of Applied Mathematics (CME 303)
- MATH 220B – Computational Methods of Applied Mathematics (CME 306)
- MATH 221B – Mathematical Methods of Imaging
- MATH 228 – Stochastic Methods in Engineering (CME 308, MS&E 324)
- MATH 230A – Theory of Probability I (STATS 310A)
- MATH 230B – Theory of Probability II (STATS 310B)
- MATH 230C – Theory of Probability III (STATS 310C)
- MATH 232 – Topics in Probability
- MATH 233A – Topics in Combinatorics
- MATH 235 – Modern Markov Chains (STATS 318)
- MATH 236 – Introduction to Stochastic Differential Equations
- MATH 238 – Mathematical Finance (STATS 250)
Statistics
- STATS 32 – Introduction to R for Undergraduates
- STATS 60 – Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160)
- STATS 100 – Mathematics of Sports
- STATS 110 – Statistical Methods in Engineering and the Physical Sciences
- STATS 116 – Theory of Probability
- STATS 117 – Theory of Probability I
- STATS 118 – Theory of Probability II
- STATS 141 – Biostatistics (BIO 141)
- STATS 160 – Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60)
- STATS 191 – Introduction to Applied Statistics
- STATS 195 – Introduction to R
- STATS 199 – Independent Study
- STATS 200 – Introduction to Statistical Inference
- STATS 202 – Data Mining and Analysis
- STATS 203 – Introduction to Regression Models and Analysis of Variance
- STATS 205 – Introduction to Nonparametric Statistics
- STATS 206 – Applied Multivariate Analysis (BIODS 206)
- STATS 207 – Introduction to Time Series Analysis (STATS 307)
- STATS 208 – Bootstrap, Cross-Validation, and Sample Re-use
- STATS 209 – Introduction to Causal Inference
- STATS 211 – Meta-research: Appraising Research Findings, Bias, and Meta-analysis (CHPR 206, EPI 206, MED 206)
- STATS 214 – Machine Learning Theory (CS 229M)
- STATS 216 – Introduction to Statistical Learning
- STATS 217 – Introduction to Stochastic Processes I
- STATS 218 – Introduction to Stochastic Processes II
- STATS 219 – Stochastic Processes (MATH 136)
- STATS 223 – Sequential Analysis (STATS 323)
- STATS 229 – Machine Learning (CS 229)
- STATS 232 – Machine Learning for Sequence Modeling (CS 229B)
- STATS 242 – NeuroTech Training Seminar (NSUR 239)
- STATS 249 – Experimental Immersion in Neuroscience (NSUR 249)
- STATS 250 – Mathematical Finance (MATH 238)
- STATS 251 – Clinical Trial Design in the Age of Precision Medicine (BIODS 250)
- STATS 256 – Modern Statistics for Modern Biology (BIOS 221, STATS 366)
- STATS 260A – Workshop in Biostatistics (BIODS 260A)
- STATS 300A – Theory of Statistics I
- STATS 300B – Theory of Statistics II
- STATS 300C – Theory of Statistics III
- STATS 305A – Applied Statistics I
- STATS 305B – Applied Statistics II
- STATS 305C – Applied Statistics III
- STATS 307 – Introduction to Time Series Analysis (STATS 207)
- STATS 310A – Theory of Probability I (MATH 230A)
- STATS 310B – Theory of Probability II (MATH 230B)
- STATS 310C – Theory of Probability III (MATH 230C)
- STATS 311 – Information Theory and Statistics (EE 377)
- STATS 317 – Stochastic Processes
- STATS 318 – Modern Markov Chains (MATH 235)
Economics
- CS 161 – Design and Analysis of Algorithms
- CS 227B – General Game Playing
- CS 229 – Machine Learning (STATS 229)
- ECON 1 – Principles of Economics
- ECON 3 – Big Ideas: Conversations with Stanford’s Own Nobel Laureates & MacArthur “Genius” Fellows (CHEM 5, SOC 5)
- ECON 43 – Introduction to Financial Decision-Making
- ECON 50 – Economic Analysis I
- ECON 51 – Economic Analysis II
- ECON 52 – Economic Analysis III
- ECON 101 – Economic Policy Seminar
- ECON 102A – Introduction to Statistical Methods (Postcalculus) for Social Scientists
- ECON 102B – Applied Econometrics
- ECON 102C – Advanced Topics in Econometrics
- ECON 105 – Economic Forecasting
- ECON 106 – World Food Economy (EARTHSYS 106, EARTHSYS 206, ECON 206, ESS 106, ESS 206)
- ECON 108 – Data Science for Business and Economic Decisions
- ECON 109 – Economics from Outer Space
- ECON 118 – Development Economics
- ECON 125 – Economic Development, Microfinance, and Social Networks
- ECON 126 – Economics of Health and Medical Care (BIOMEDIN 156, BIOMEDIN 256, HRP 256)
- ECON 131 – The Chinese Economy
- ECON 135 – Foundations of Finance
- ECON 136 – Market Design
- ECON 137 – Decision Modeling and Information
- ECON 141 – Financial Markets
- ECON 143 – Finance, Corporations, and Society (INTLPOL 227, POLISCI 127A, PUBLPOL 143, SUSTAIN 143)
- ECON 144 – Family and Society
- ECON 146 – Economics of Education
- ECON 149 – The Modern Firm in Theory and Practice
- ECON 150 – Economic Policy Analysis (PUBLPOL 104, PUBLPOL 204)
- ECON 154 – Law and Economics (PUBLPOL 106, PUBLPOL 206)
- ECON 155 – Environmental Economics and Policy
- ECON 156 – Energy Markets and Policy (ECON 256, INTLPOL 276)
- ECON 157 – Imperfect Competition
- ECON 166 – International Trade
- ECON 167G – Game Theory and Social Behavior
- ECON 177 – Empirical Environmental Economics (SUSTAIN 130, SUSTAIN 230)
- ECON 178 – Behavioral Economics
- ECON 184 – Institutional Investment Management: Theory and Practice
- ECON 202 – Microeconomics I
- ECON 203 – Microeconomics II
- ECON 204 – Microeconomics III
- ECON 206 – World Food Economy (EARTHSYS 106, EARTHSYS 206, ECON 106, ESS 106, ESS 206)
- ECON 210 – Macroeconomics I
- ECON 211 – Macroeconomics II
- ECON 212 – Macroeconomics III
- ECON 215 – Development Economics II
- ECON 216 – Development Economics III
- ECON 220 – Political Economy I (POLISCI 460A)
- ECON 226 – Topics in US and international economic history
- ECON 270 – Intermediate Econometrics I
- ECON 271 – Intermediate Econometrics II
Harvard
Mathematics
- Math MA – Introduction to Functions and Calculus I
- Math MB – Introduction to Functions and Calculus II
- Math 1A – Introduction to Calculus
- Math 1B – Integration, Series and Differential Equations
- Math 18A – Multivariable Calculus for Social Sciences
- Math 19A – Modeling and Differential Equations for the Life Sciences
- Math 21A – Multivariable Calculus
- Math 21B – Linear Algebra and Differential Equations
- Math 22A – Vector Calculus and Linear Algebra I
- Math 22B – Vector Calculus and Linear Algebra II
- Math 25A – Theoretical Linear Algebra and Real Analysis I
- Math 25B – Theoretical Linear Algebra and Real Analysis II
- Math 55A – Studies in Algebra and Group Theory
- Math 55B – Studies in Real and Complex Analysis
- Math 60R – Reading Course for Senior Honors Candidates
- Math 101 – Sets, Groups, and Real Analysis
- Math 110 – Vector Space Methods for Differential Equations
- Math 112 – Introductory Real Analysis
- Math 113 – Complex Analysis
- Math 114 – Analysis of Function Spaces, Measure and Integration
- Math 116 – Real Analysis, Convexity, and Optimization
- Math 118R – Dynamical Systems
- Math 122 – Algebra I: Theory of Groups and Vector Spaces
- Math 123 – Algebra II: Theory of Rings and Fields
- Math 124 – Number Theory
- Math 129 – Number Fields
- Math 131 – Topological Spaces and Fundamental Group
- Math 132 – Differential Topology
- Math 136 – Differential Geometry
- Math 137 – Algebraic Geometry
- Math 145A – Set Theory I
- Math 152 – Discrete Mathematics
- Math 154 – Probability Theory
- Math 155R – Combinatorics
- Math 157 – Mathematics in the World
Statistics
- STAT 100 – Introduction to Statistics and Data Science
- STAT 102 – Introduction to Statistics for Life Sciences
- STAT 104 – Introduction to Quantitative Methods for Economics
- STAT 109A – Data Science 1
- STAT 110 – Introduction to Probability
- STAT 139 – Introduction to Linear Models
- STAT 151 – Multilevel and Longitudinal Models
- STAT 184 – Introduction to Reinforcement Learning
- STAT 185 – Introduction to Unsupervised Learning
- STAT 210 – Probability 1
- STAT 211 – Statistical Inference 1
- STAT 221 – Computational Tools for Statistical Learning: Approximation, Optimization, and Monte Carlo
- STAT 230 – Multivariate Statistical Analysis
- STAT 236 – Sparce Interference, and Network and Text Analysis
- STAT 242 – Time Series
- STAT 286 – Causal Inference with Applications
- STAT 131 – Introduction to Time Series and Prediction
- STAT 143 – Sports Analytics
- STAT 149 – Introduction to Generalized Linear Models
- STAT 171 – Introduction to Stochastic Processes
- STAT 186 – Introduction to Causal Inference
- STAT 195 – Introduction to Supervised Learning
- STAT 212 – Probability II
- STAT 213 – Statistical Inference II
- STAT 220 – Bayesian Data Analysis
Economics
- ECON 50 – Using Big Data to Solve Economic and Social Problems
- ECON 2000 – Introduction to Quantitative Economics
- ECON 2450B – Public Economics and Fiscal Policy II
- ECON 2905 – Early-Stage Research and Discussions on Economic Development
- ECON 10B – Principles of Economics (Macroeconomics)
- ECON 2010C – Economic Theory
- ECON 2081 – Topics and Methods in Economic Theory
- ECON 1420 – American Economic Policy
- ECON 1818 – Economics of Discontinuous Change
- ECON 10A – Principles of Economics (Microeconomics)
- ECON 1661 – Economics of Climate Change and Environmental Policy
- ECON 1425 – Political Economics
- ECON 980KK – Economic Growth
- ECON 2010B – Economic Theory
- ECON 1126 – Quantitative Methods in Economics
- ECON 2010A – Economic Theory
- ECON 1123 – Introduction to Econometrics
- ECON 1010B – Intermediate Macroeconomics
UPenn
Mathematics
- MATH 0030 – Introduction to Calculus Lab
- MATH 0040 – Calculus Lab I
- MATH 0100 – Calculus for Wharton Students Lab
- MATH 0140 – Calculus II Lab
- MATH 0240 – Calculus III Lab
- MATH 1070 – Mathematics of Change, Part I
- MATH 1080 – Mathematics of Change, Part II
- MATH 1100 – Calculus for Wharton Students
- MATH 1234 – Community Algebra Initiative
- MATH 1248 – Community Math Teaching Project
- MATH 1400 – Calculus, Part I
- MATH 1410 – Calculus, Part II
- MATH 1510 – Calculus, Part II with Probability and Matrices
- MATH 1610 – Honors Calculus
- MATH 1700 – Ideas in Mathematics
- MATH 2020 – Proving Things: Analysis
- MATH 2030 – Proving things: Algebra
- MATH 2100 – Mathematics in the Age of Information
- MATH 2400 – Calculus, Part III
- MATH 2410 – Calculus, Part IV
- MATH 2600 – Honors Calculus, Part II
- MATH 2800 – Entropy Math Evolution
- MATH 2900 – Undergraduate Mathematics Research Course
- MATH 2989 – Study Abroad
- MATH 2990 – Undergraduate Research in Mathematics
- MATH 2999 – Transfer and Credit Away
- MATH 3120 – Linear Algebra
- MATH 3130 – Computational Linear Algebra
- MATH 3140 – Advanced Linear Algebra
- MATH 3200 – Computer Methods in Mathematical Science I
- MATH 3400 – Discrete Mathematics I
- MATH 3410 – Discrete Mathematics II
- MATH 3500 – Number Theory
- MATH 3600 – Advanced Calculus
- MATH 3700 – Algebra
- MATH 4100 – Complex Analysis
- MATH 4200 – Ordinary Differential Equations
- MATH 4250 – Partial Differential Equations
- MATH 4320 – Game Theory
- MATH 4600 – Topology
- MATH 4650 – Differential Geometry
- MATH 4800 – Topics in Modern Math
- MATH 4990 – Supervised Study
- MATH 5000 – Topology
- MATH 5010 – Differential Geometry
- MATH 5020 – Abstract Algebra
- MATH 5030 – Abstract Algebra
- MATH 5040 – Graduate Proseminar in Mathematics
- MATH 5080 – Advanced Analysis
- MATH 5120 – Advanced Linear Algebra
- MATH 5130 – Computational Linear Algebra
- MATH 5200 – Selections from Algebra
- MATH 5300 – Mathematics of Finance
- MATH 5400 – Selections from Classical and Functional Analysis
- MATH 5700 – Logic and Computability 1
- MATH 5710 – Logic and Computability 2
- MATH 5800 – Combinatorial Analysis
Statistics
- STAT 0001 – Introduction to Statistics and Data Science
- STAT 1010 – Introductory Business Statistics
- STAT 4050 – Statistical Computing with R
- STAT 4100 – Data Collection and Acquisition: Strategies and Platforms
- STAT 4220 – Predictive Analytics for Business
- STAT 4230 – Applied Machine Learning in Business
- STAT 4240 – Text Analytics
- STAT 4300 – Probability
- STAT 4310 – Statistical Inference
- STAT 4320 – Mathematical Statistics
- STAT 4330 – Stochastic Processes
- STAT 4350 – Forecasting Methods for Management
- STAT 4420 – Introduction to Bayesian Data Analysis
- STAT 4700 – Data Analytics and Statistical Computing
- STAT 4710 – Modern Data Mining
- STAT 4740 – Modern Regression for the Social, Behavioral and Biological Sciences
- STAT 4750 – Sample Survey Design
- STAT 4760 – Applied Probability Models in Marketing
- STAT 4770 – Introduction to Python for Data Science
- STAT 4800 – Advanced Statistical Computing
- STAT 4900 – Causal Inference
- STAT 5000 – Applied Regression and Analysis of Variance
- STAT 5010 – Introduction to Nonparametric Methods and Log-linear Models
- STAT 5030 – Data Analytics and Statistical Computing
- STAT 5100 – Probability
- STAT 5110 – Statistical Inference
- STAT 5120 – Mathematical Statistics
- STAT 5150 – Advanced Statistical Inference I
- STAT 5160 – Advanced Statistical Inference II
- STAT 5200 – Applied Econometrics I
- STAT 5210 – Applied Econometrics II
- STAT 5330 – Stochastic Processes
- STAT 5420 – Bayesian Methods and Computation
- STAT 5710 – Modern Data Mining
- STAT 6130 – Regression Analysis for Business
- STAT 6210 – Accelerated Regression Analysis for Business
- STAT 7050 – Statistical Computing with R
- STAT 7110 – Forecasting Methods for Management
- STAT 7220 – Predictive Analytics for Business
- STAT 7230 – Applied Machine Learning in Business
- STAT 9250 – Multivariate Analysis: Theory
- STAT 9260 – Multivariate Analysis: Methodology
- STAT 9270 – Bayesian Statistical Theory and Methods
- STAT 9280 – Statistical Learning Theory
- STAT 9300 – Probability Theory
- STAT 9310 – Stochastic Processes
- STAT 9710 – Introduction to Linear Statistical Models
Economics
- ECON 0100 – Introduction to Micro Economics
- ECON 0120 – Strategic Reasoning
- ECON 0200 – Introductory Economics: Macro
- ECON 0420 – Political Economy
- ECON 0430 – Labor Economics
- ECON 0450 – Industrial Organization
- ECON 0460 – Economics and Theories of Fairness
- ECON 0465 – Economics and Philosophy
- ECON 0500 – International Economics
- ECON 0510 – Development Economics
- ECON 0620 – Financial Meltdown, Past and Present
- ECON 0625 – Introduction to Business, Economic and Financial History
- ECON 0630 – The Economics and Financing of Health Care Delivery
- ECON 2100 – Intermediate Microeconomics
- ECON 2200 – Intermediate Macroeconomics
- ECON 2300 – Statistics for Economists
- ECON 2310 – Econometric Methods and Models
- ECON 4100 – Game Theory
- ECON 4101 – Game Theory Honors
- ECON 4110 – Economics of Family
- ECON 4120 – Social Choice Theory
- ECON 4130 – Market Design
- ECON 4140 – Decision Making Under Uncertainty
- ECON 4160 – Behavioral Economics
- ECON 4200 – Economic Growth
- ECON 4205 – Structural changes in the modern macroeconomy
- ECON 4210 – Numerical Methods for Macroeconomists
- ECON 4220 – Monetary and Fiscal Policies
- ECON 4230 – Macro-Modeling
- ECON 4240 – Money and Banking
- ECON 4310 – Macro-Econometric Techniques and Applications
- ECON 4320 – Micro-econometric Techniques and Applications
- ECON 4330 – Econometric Machine Learning Methods and Models
- ECON 4340 – Empirical Economics of Climate Change
- ECON 4405 – Economic Program Evaluation
- ECON 4410 – Public Finance
- ECON 4420 – Political Economy
- ECON 4430 – Labor Economics
- ECON 4450 – Industrial Organization
Wharton
Mathematics
Statistics
- STAT 1010 – Intro to Business Stat
- STAT 1110 – Introductory Statistics
- STAT 4020 – Communicating Quant. Analyses
- STAT4050 – Stat Computing with R
- STAT4100 – Data Collect & Acquisition
- STAT4220 – Predictive Analytics
- STAT4230 – Machine Learning in Business
- STAT4240 – Text Analytics
- STAT4300 – Probability
- STAT4310 – Statistical Inference
- STAT4320 – Mathematical Statistics
- STAT4330 – Stochastic Processes
- STAT4350 – Forecasting Methods Mgmt
- STAT4420 – Intro Bayes Data Analysis
- STAT 4700 – Data Analytics and Statistical Computing
- STAT 4710 – Modern Data Mining
- STAT 4740 – Modern Regression
- STAT 4750 – Sample Survey Design
- STAT 4760 – Applied Probability Models in Marketing
- STAT 4770 – Introduction to Python for Data Science
- STAT 4800 – Advanced Statistical Computing
- STAT 4900 – Causal Inference
- STAT 5000 – Applied Regression and Analysis of Variance
- STAT 5010 – Introduction to Nonparametric Methods and Log-linear Models
- STAT 5030 – Data Analytics and Statistical Computing
- STAT 5100 – Probability
- STAT 5110 – Statistical Inference
- STAT 5120 – Mathematical Statistics
- STAT 5150 – Advanced Statistical Inference I
- STAT 5160 – Advanced Statistical Inference II
- STAT 5200 – Applied Econometrics I
- STAT 5210 – Applied Econometrics II
- STAT 5330 – Stochastic Processes
- STAT 5420 – Bayesian Methods and Computation
- STAT 5710 – Modern Data Mining
Economics
- BEPP1000 – Introductory Economics
- BEPP2010 – Public Finance & Policy
- BEPP2020 – Con Fin Decision Making
- BEPP2030 – Business in Global Political Environment
- BEPP2070 – Econ. For Next 100 Yrs
- BEPP2080 – Housing Markets
- BEPP2110 – Tax Policy & Practice
- BEPP2120 – Economic Analysis of Law
- BEPP2140 – Nonprofit Sector: Economy
- BEPP2200 – Behavioral Economics
- BEPP2300 – Urban Fiscal Policy
- BEPP2330 – Consumers, Firms & Market
- BEPP2360 – Int’l Housing Comparisons
- BEPP2500 – Managerial Economics
- BEPP2508 – Managerial Economics
- BEPP2650 – Economics of Diversity
- BEPP2800 – Applied Data Analysis
Call now if you need a top-tier private math tutor near you. I offer in-person and online math tutoring services at your convenience.
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