A mechanical engineering grad student who builds things, breaks things, and troubleshoots what went wrong — Aaron brings that same hands-on diagnostic process to science topics like forces, energy, properties of matter, and experimental design. His 1530 SAT confirms the analytical horsepower, and his 5.0 rating suggests he explains the reasoning behind results in a way that actually lands.

Mimi's Masters in Education from Harvard focused on inquiry-based and object-based learning — an approach that turns science into something students can observe, question, and test rather than just read about in a textbook. Her integrated arts background means she often teaches concepts like ecosystems or states of matter through hands-on exploration and visual models, which tends to stick with students who struggle to learn from lectures alone. She's especially strong with younger and middle school learners building their first real science habits.

A neurobiology-focused biology degree from Northwestern means Nina didn't just take introductory science — she studied cellular mechanisms, genetics, and brain physiology in depth. She connects textbook concepts like mitosis or enzyme kinetics to real research contexts, which tends to make the material click faster than rote memorization. Rated 5.0 by students.

Reid treats science as a way of thinking rather than a collection of facts to memorize. He walks students through how to read data tables, design controlled experiments, and connect observations to underlying principles — the same analytical habits that show up across biology, chemistry, and earth science courses.

Engineering at Yale means Charles lives at the intersection of physics, chemistry, and applied math every day — analyzing forces in a truss, modeling heat transfer, or interpreting experimental data. He brings that hands-on perspective to general science tutoring, connecting abstract formulas to physical situations students can actually picture. Whether the topic is kinematics, energy conservation, or interpreting lab results, he makes the reasoning behind each step visible.

As a mechanical engineering student at Harvard, Christopher lives at the intersection of physics and chemistry daily — calculating forces, analyzing material properties, and modeling energy systems. That applied perspective makes him especially effective at showing students why scientific concepts matter beyond the textbook, turning abstract formulas into concrete, intuitive ideas.

Sociology research at Harvard meant Solange spent years designing surveys, analyzing datasets, and defending conclusions in front of professors who demanded airtight reasoning — all of which is applied scientific method, even if the subject matter was social rather than physical. She's especially effective at teaching students to distinguish correlation from causation and to read charts and graphs with a critical eye, since those skills were daily requirements in her coursework. Her 34 ACT confirms she can handle the quantitative side of science just as comfortably as the conceptual.

Running a tutoring program at a charter middle school meant Liz wasn't just teaching science content — she was figuring out how to make vocabulary-heavy units on cells, ecosystems, and states of matter land for students with dyslexia, ADHD, and other learning differences. Her special education master's gave her a toolkit of concrete strategies for breaking down dense nonfiction text and multi-step processes, which is where most science students actually get stuck. She holds a 4.7 rating across her subjects.

A biochemistry degree from Rice and a current M.D. program at Baylor mean Michelle lives at the intersection of biology and chemistry every day. She unpacks concepts like cellular respiration, acid-base equilibria, and molecular genetics by tying them to how the body actually works — turning dense textbook material into something students can visualize and retain.

A PhD in Computational Mathematics from the University of Chicago means Justin doesn't just know science — he understands the quantitative reasoning that ties physics, chemistry, and earth science together. He breaks down concepts like energy conservation, wave behavior, and data analysis by connecting them to real-world phenomena, from climate modeling to how lenses form images. Rated 5.0 by students.

Daniel's sociology degree means he spent years learning to design surveys, analyze demographic data, and apply the scientific method to real human behavior — skills that translate naturally when teaching students how to form hypotheses, control variables, and interpret results in a general science context. He's especially comfortable helping students who freeze up at graphs and data tables, since reading quantitative evidence was a daily requirement in his coursework. Holds a 5.0 rating.

Andrew holds a BS in Physics and a PhD in Biomedical Engineering, which means he's spent over a decade thinking scientifically — designing experiments, interpreting data, and connecting abstract principles to measurable outcomes. He unpacks concepts in mechanics, electricity, and biology-adjacent topics like biomechanics with the kind of depth that comes from genuine research experience. Students get explanations rooted in understanding, not just memorized definitions.

Henry's Harvard thesis on John Dewey's philosophy of education was fundamentally about how people learn through inquiry and experimentation — the same cycle of questioning, testing, and revising that sits at the heart of the scientific method. He teaches science by grounding abstract concepts in that inquiry process, pushing students to ask why an experiment is designed a certain way before worrying about memorizing the outcome. His 1530 SAT confirms he can handle the quantitative and analytical reasoning science coursework demands.

An MIT math degree and a PhD track in operations research at Georgia Tech mean Isabella has spent years inside labs and classrooms where the scientific method isn't a textbook concept — it's a daily practice of modeling real systems, testing assumptions, and interpreting results. She's especially strong on the quantitative backbone of science: reading data tables, understanding units, and translating observations into precise claims. Rated 5.0 by students.

Having studied biology and chemistry alongside her political science degree at the University of Chicago, Asta can walk students through core science concepts — from cell structure to chemical reactions — with genuine content knowledge rather than just test-taking tricks. Her 35 ACT confirms she handled the Science section's rapid-fire data interpretation at a near-perfect level, and she brings that same ability to teach students how to read graphs, pull patterns from tables, and connect evidence to conclusions. Rated 5.0 by students.

Undergraduate research in Northwestern's John Rogers Lab and a biomedical engineering curriculum gave Ingrid hands-on experience with biology, chemistry, physics, and thermodynamics. She explains scientific concepts by connecting them to real applications — like how drug delivery systems depend on diffusion or why cells respond to mechanical forces — which makes abstract ideas stick.

A philosophy grad student at UNM with a 34 ACT, Justin treats science the way he treats an argument in formal logic — isolating each claim, checking whether the evidence actually supports it, and identifying where the reasoning breaks down. That approach is especially useful when students need to evaluate hypotheses, interpret graphs, or explain why an experiment's results do or don't match a prediction. His 5.0 rating suggests the method lands.

A chemistry major headed to Columbia Medical School, James treats science tutoring as an exercise in building intuition — understanding why a reaction proceeds a certain way or how energy flows through a biological system, not just memorizing diagrams. He's especially sharp at bridging the gap between introductory courses and the more rigorous thinking that AP or IB-level science demands.

Applied math and computer science at Johns Hopkins means Sabira spends her days quantifying patterns and testing models — the same core loop students encounter in science when they're asked to measure, predict, and explain. She's particularly strong on the computational side of science: reading data tables, graphing relationships, and working through the math embedded in physics or chemistry problems. Holds a 5.0 rating.

As a curriculum developer building courses for middle and high schoolers, Elena knows exactly how to make dense material click — including the scientific vocabulary, classification systems, and cause-and-effect reasoning that science coursework demands. Her Religious Studies training at McGill involved rigorous textual analysis and structured argumentation, skills she now channels into teaching students how to read scientific texts carefully, interpret what an experiment actually shows, and explain their reasoning clearly.

While science isn't Keith's primary academic background, his analytical training in political science and law makes him effective at teaching students how to read data, interpret experiments, and reason through cause-and-effect relationships. He's particularly useful for students who struggle with the reading-heavy side of science — understanding what a question is really asking and pulling the right information from charts and passages.

A social sciences master's degree means Lauren spent years doing what science coursework actually asks of students — reading studies, questioning methodology, and pulling defensible conclusions from messy data. She's particularly good at walking through how to set up a controlled experiment and explain results in plain language, since her own graduate research required exactly that. Rated 5.0 by students.

Comparative literature might seem worlds away from science, but Brittney's Princeton training in close reading and textual analysis translates surprisingly well to parsing dense lab instructions, extracting meaning from data tables, and interpreting the kind of evidence-based passages that show up across science coursework. She's strongest with students who can grasp the concepts but struggle to articulate their reasoning in writing — lab reports, short-answer explanations, and constructing arguments from observations. Rated 5.0 by students.

A PhD program in Spanish and Iberian Studies might not scream 'science,' but Renee's doctoral training drilled the same core skills science coursework requires — forming a thesis from evidence, analyzing patterns in complex material, and defending conclusions under scrutiny. She's particularly useful for students who struggle with the literacy-heavy side of science: parsing dense textbook passages, interpreting diagrams, and writing clear lab reports that actually explain what happened and why.

Doctoral work in clinical psychology at Duke means Shelley designs and analyzes research studies regularly — controlling variables, interpreting statistical output, and defending conclusions in front of faculty who pick apart every methodological choice. That daily practice with the scientific method gives her a practical fluency she brings to teaching concepts like experimental design, data analysis, and hypothesis testing. Her 5.0 rating suggests she makes that rigor accessible rather than intimidating.

Ben's science tutoring draws on his IB Chemistry background and the quantitative rigor of his Penn math training, which means he's especially effective when science gets mathematical — balancing equations, interpreting rate laws, or working through stoichiometry. He teaches students to translate word-heavy science problems into clean mathematical setups they can actually solve.

Biomedical engineering trained Sam to move fluidly between biology, chemistry, and physics — the same integration students need when tackling science coursework. He unpacks concepts like cellular respiration or circuit analysis by tying them back to the underlying math, which turns abstract diagrams into something students can actually reason through.

Having earned a 1530 SAT — which leans heavily on interpreting data, reading graphs, and evaluating evidence-based claims — Matt brings sharp analytical skills to science material even though his degrees are in finance. He's particularly useful for the quantitative side of science: setting up calculations, converting units, and making sense of numerical relationships in lab work or textbook problems.

Emily's undergraduate degree in Molecular, Cellular, and Developmental Biology and her MPH in Epidemiology give her deep fluency in both life sciences and the quantitative reasoning that underpins them. She unpacks topics like cell division, genetics, and experimental design by tying abstract concepts to real-world examples from public health research. Rated 5.0 by students.

Speech-language pathology graduate training at Columbia is surprisingly science-heavy — anatomy, neuroscience, research design — and Sherry brings that clinical lens to teaching students how biological systems work and how experiments should be structured. Her UChicago psychology and linguistics background also means she's comfortable with everything from statistical reasoning to breaking apart dense scientific terminology using morphological roots. Rated 5.0 by students.

Chemistry is Sung's home discipline, which means he teaches science the way a working scientist thinks about it: grounding every concept in evidence, units, and careful reasoning. Whether a student is balancing equations, interpreting lab data, or connecting molecular structure to physical properties, Sung ties abstract ideas back to observable, concrete examples.

Pre-health coursework at the University of Pennsylvania means Shayan has lived the full gauntlet — biology, biochemistry, physiology, pharmacology, and anatomy — and knows how to connect those disciplines into a coherent picture. He teaches science by grounding every concept in a concrete example, whether that's explaining cellular respiration through energy metabolism or walking through organ systems one function at a time.

A statistics and machine learning certificate at Princeton means Julie spends her coursework building models, testing hypotheses against real data, and evaluating whether results are statistically meaningful — all of which is applied scientific reasoning. She brings that quantitative rigor to science tutoring, especially when students need to move from memorizing definitions to actually interpreting experiments, reading graphs, and explaining what their data means. Her 4.9 rating suggests the approach lands.

Legal training is essentially argument construction from evidence — and Emily applies that same framework when teaching students to work through hypotheses, evaluate experimental outcomes, and explain what data actually supports versus what it doesn't. Her philosophy degree from Northwestern also built the formal logic skills that underpin scientific reasoning, from identifying control variables to spotting flawed conclusions in a lab report.

Kevin's Philosophy, Politics, and Economics major at Penn requires him to constantly evaluate claims against evidence — the same core skill students need when forming hypotheses, interpreting lab data, and explaining why an experiment turned out the way it did. His 34 ACT confirms he can handle the quantitative and reading-heavy demands of science material, and his statistics background means he's comfortable walking students through graphing relationships and drawing conclusions from data sets.

Growing up in Malaysia before studying at Penn and completing a Master's in Education at Harvard, Yu picked up science through multiple educational systems — which means she's seen the same concepts taught in very different ways and knows which explanations actually land. She leans on that cross-cultural perspective to teach topics like the scientific method, experimental reasoning, and data interpretation by reframing them until they click. Her chemistry background also lets her go deeper when students hit the quantitative side of science.

A Yale education heavy on critical reading and analytical writing gave Maya the tools to tackle science from the comprehension side — parsing dense passages, extracting key claims from lab descriptions, and explaining results in clear, organized language. She's particularly useful for students who understand the concepts but freeze when asked to write up an experiment or interpret what a data table is actually saying. Holds a 5.0 rating.

Journalism is fundamentally about investigation — gathering evidence, verifying claims, and explaining complex topics to a general audience — and Meghan applies that same discipline when walking students through scientific concepts like experimental design and data interpretation. Her Northwestern training emphasized rigorous sourcing and logical structure, which translates naturally to teaching students how to read a graph, evaluate a hypothesis, or write up lab results that actually say something clear. Rated 5.0 by students.

Between her biomedical engineering major, pre-med coursework, and active autism research at the Yale School of Medicine, Ellie covers biology, chemistry, and physics with the depth of someone who uses all three daily. She unpacks tricky concepts — enzyme kinetics, circuit analysis, stoichiometry — by linking them to real experiments and clinical applications that make the material stick.

As someone who also teaches GED Science, Frances approaches science by treating it as a reading and reasoning exercise first. She teaches students to interpret data tables, understand experimental design, and connect vocabulary to the underlying concepts in biology, earth science, or physical science.