Difference between revisions of "CyberMath Academy"
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− | CyberMath | + | CyberMath Academy’s Summer Math Camp in Boston, MA is a selective summer program for students who would like to sharpen their math skills in the inspiring and motivating atmosphere of an Ivy League College. Our math camp provides a challenging environment in summer for students in which they master mathematics with the participation of brilliant students from all over the globe. |
+ | ==Locations and Dates== | ||
+ | Boston: Harvard University - July 17-28, 2023 | ||
− | == | + | ==Ages== |
+ | Recommended Ages: 11-18 for residential students, 9-18 for day students. For younger students, please email [mailto:info@cybermath.academy info@cybermath.academy] | ||
− | + | ==Courses== | |
− | === | + | ===Advanced Middle School Math=== |
− | + | This course covers the main topics in middle school math. Students master these topics while solving challenging problems, puzzles, and ciphers, and learn topics outside the traditional school curriculum. | |
− | + | Recommended Grade Level: Although this course is typically recommended for students in grades 4-8, and anyone in 8th grade or below may enroll, younger students can participate as well. | |
− | + | Course Description: This course familiarizes students with essential concepts and techniques in Prealgebra, Algebra I, Geometry, Number Theory and Combinatorics, having a specific emphasis on problem solving where the students will constantly be challenged to think creatively. | |
+ | |||
+ | ===Advanced High School Math=== | ||
− | + | This course covers topics in trigonometry, advanced algebra, precalculus and advanced geometry, but excludes calculus. Our curriculum also includes some additional challenging and brain-stimulating topics outside of the traditional school curriculum. | |
− | + | Recommended Grade Level: Although we do not limit students by grade level, this course is typically recommended for advanced 7th and 8th graders and high school students. | |
− | + | Course Description: This course familiarizes students with essential concepts and techniques in Algebra II, Precalculus, Combinatorics, Number Theory, and Geometry, having a specific emphasis on problem solving where the students will constantly be challenged to think creatively. | |
+ | ==Daily Schedule== | ||
+ | {| class="wikitable" | ||
+ | |- | ||
+ | ! Time | ||
+ | ! Activity | ||
+ | ! Notes | ||
+ | |- | ||
+ | | 7:15 am – 8:15 am | ||
+ | | Breakfast | ||
+ | | Residential Students Only | ||
+ | |- | ||
+ | | 8:15 am – 8:45 am | ||
+ | | Day students arrive | ||
+ | | | ||
+ | |- | ||
+ | | 9:00 am – 1:00 pm | ||
+ | | Morning classes | ||
+ | | | ||
+ | |- | ||
+ | | 1:00 pm – 2:00 pm | ||
+ | | Lunch and Activity time | ||
+ | | Conversation with teachers/counselors | ||
+ | |- | ||
+ | | 2:00 pm – 4:00 pm | ||
+ | | Afternoon Activities | ||
+ | | Tests, Competitions, Activities, Trips | ||
+ | |- | ||
+ | | 4:30 pm – 5:00 pm | ||
+ | | Day students depart | ||
+ | | | ||
+ | |- | ||
+ | | 5:00 pm – 6:00 pm | ||
+ | | Free time | ||
+ | | Residential Students Only | ||
+ | |- | ||
+ | | 6:00 pm – 7:15 pm | ||
+ | | Dinner | ||
+ | | Residential Students Only | ||
+ | |- | ||
+ | | 7:30 pm – 9:00 pm | ||
+ | | Study time | ||
+ | | Residential Students Only | ||
+ | |- | ||
+ | | 9:00 pm – 10:30 pm | ||
+ | | Free time | ||
+ | | Residential Students Only | ||
+ | |- | ||
+ | | 10:45 pm | ||
+ | | Lights out | ||
+ | | Residential Students Only | ||
+ | |} | ||
− | + | ==Instructors== | |
− | - | + | Below are some former and current instructors. |
+ | * Anna Blanchfield: Studied Chemical and Physical Biology at Harvard University. She is an IB Diploma recipient and received a score of 7 on both the Math SL exam and the Physics SL exam. | ||
+ | * Ibrahim Suat Evren: Studies Math at MIT. Gold medal at 2019 IMO, bronze medal at 2019 Balkan Math Olympiad (BMO), gold medal at 2016 Junior BMO. 800 on SAT Math Level-2, 800 on SAT Physics. | ||
+ | * Igor Ganichev: Member of Google Brain Team, working on TensorFlow. PhD from UC Berkeley, B.S. in in Mathematics and Computer Science from MIT. 1 gold, 2 silver medals at IMO (2000-2002) | ||
+ | * Bryce Hunter McLaughlin: B.S. in Mathematics from Harvey Mudd College. Studying towards PhD in Business at Stanford Univ. | ||
+ | * Nicholas Pascucci: Studied spacecraft AI verification at MIT. Deployed AI systems for NASA. | ||
+ | * Alex Toller: BA in Mathematics from UC Berkeley. CyberMath Academic Coordinator; Instructor since Summer 2019. 2014 MATHCOUNTS National Competition participant. Top 2 percent on AMC 12; 2x Putnam Exam top 500 (2019, February 2021). Member of the MATHCOUNTS Question Writing Committee. Co-author of the book Proofs in Competition Math. | ||
+ | We also have many more instructors with similar credentials. | ||
+ | ==Guest Lectures by Harvard, MIT, Stanford Researchers and Professors== | ||
− | + | Below are some former guest lectures. | |
+ | * Dr. Michael Mitzenmacher, Senior Professor, Department of Computer Science, Harvard University - "Fundamentals of Machine Learning" | ||
+ | * Dr. John W. Cain, Senior Lecturer, Department of Mathematics, Harvard University - "Current Research in Mathematics and Advice for Students" | ||
+ | * Dr. Michele Catasta – Stanford Univ., Dept. of Computer Science- "Hybrid Human-Machine Information Systems" | ||
+ | * Dr. Nuh Gedik – M.I.T., Department of Physics - "Seeing the ultrasmall, capturing the ultrafast!" | ||
+ | * Dr. Umut Eser – Cellarity, Head of Machine Learning Department, Former Researcher at Harvard Medical School - "Artificial Intelligence – Past, Present and Future" | ||
+ | * Dr. Johanna O'Day – Researcher at Stanford Bio-X Interdisciplinary Biosciences Institute - "Mechanical Engineering and Neuroscience" | ||
+ | * Dr. Darrel Deo – Researcher at Stanford Bio-X Interdisciplinary Biosciences Institute - "BioRobotics" | ||
+ | * Dr. Andrew Powers - Neurosurgeon at Beth Israel Deaconess Medical Center of Harvard University - "How to become a successful neurosurgeon" | ||
+ | * Dr. Albert Hsia - Head of Marketing at Merck, Harvard University alumnus - "Data Science Applications in medical fields" | ||
− | + | ==External links== | |
− | + | *[[//cybermath.org More information]] | |
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Latest revision as of 15:06, 18 January 2025
CyberMath Academy’s Summer Math Camp in Boston, MA is a selective summer program for students who would like to sharpen their math skills in the inspiring and motivating atmosphere of an Ivy League College. Our math camp provides a challenging environment in summer for students in which they master mathematics with the participation of brilliant students from all over the globe.
Contents
[hide]Locations and Dates
Boston: Harvard University - July 17-28, 2023
Ages
Recommended Ages: 11-18 for residential students, 9-18 for day students. For younger students, please email info@cybermath.academy
Courses
Advanced Middle School Math
This course covers the main topics in middle school math. Students master these topics while solving challenging problems, puzzles, and ciphers, and learn topics outside the traditional school curriculum.
Recommended Grade Level: Although this course is typically recommended for students in grades 4-8, and anyone in 8th grade or below may enroll, younger students can participate as well.
Course Description: This course familiarizes students with essential concepts and techniques in Prealgebra, Algebra I, Geometry, Number Theory and Combinatorics, having a specific emphasis on problem solving where the students will constantly be challenged to think creatively.
Advanced High School Math
This course covers topics in trigonometry, advanced algebra, precalculus and advanced geometry, but excludes calculus. Our curriculum also includes some additional challenging and brain-stimulating topics outside of the traditional school curriculum.
Recommended Grade Level: Although we do not limit students by grade level, this course is typically recommended for advanced 7th and 8th graders and high school students.
Course Description: This course familiarizes students with essential concepts and techniques in Algebra II, Precalculus, Combinatorics, Number Theory, and Geometry, having a specific emphasis on problem solving where the students will constantly be challenged to think creatively.
Daily Schedule
Time | Activity | Notes |
---|---|---|
7:15 am – 8:15 am | Breakfast | Residential Students Only |
8:15 am – 8:45 am | Day students arrive | |
9:00 am – 1:00 pm | Morning classes | |
1:00 pm – 2:00 pm | Lunch and Activity time | Conversation with teachers/counselors |
2:00 pm – 4:00 pm | Afternoon Activities | Tests, Competitions, Activities, Trips |
4:30 pm – 5:00 pm | Day students depart | |
5:00 pm – 6:00 pm | Free time | Residential Students Only |
6:00 pm – 7:15 pm | Dinner | Residential Students Only |
7:30 pm – 9:00 pm | Study time | Residential Students Only |
9:00 pm – 10:30 pm | Free time | Residential Students Only |
10:45 pm | Lights out | Residential Students Only |
Instructors
Below are some former and current instructors.
- Anna Blanchfield: Studied Chemical and Physical Biology at Harvard University. She is an IB Diploma recipient and received a score of 7 on both the Math SL exam and the Physics SL exam.
- Ibrahim Suat Evren: Studies Math at MIT. Gold medal at 2019 IMO, bronze medal at 2019 Balkan Math Olympiad (BMO), gold medal at 2016 Junior BMO. 800 on SAT Math Level-2, 800 on SAT Physics.
- Igor Ganichev: Member of Google Brain Team, working on TensorFlow. PhD from UC Berkeley, B.S. in in Mathematics and Computer Science from MIT. 1 gold, 2 silver medals at IMO (2000-2002)
- Bryce Hunter McLaughlin: B.S. in Mathematics from Harvey Mudd College. Studying towards PhD in Business at Stanford Univ.
- Nicholas Pascucci: Studied spacecraft AI verification at MIT. Deployed AI systems for NASA.
- Alex Toller: BA in Mathematics from UC Berkeley. CyberMath Academic Coordinator; Instructor since Summer 2019. 2014 MATHCOUNTS National Competition participant. Top 2 percent on AMC 12; 2x Putnam Exam top 500 (2019, February 2021). Member of the MATHCOUNTS Question Writing Committee. Co-author of the book Proofs in Competition Math.
We also have many more instructors with similar credentials.
Guest Lectures by Harvard, MIT, Stanford Researchers and Professors
Below are some former guest lectures.
- Dr. Michael Mitzenmacher, Senior Professor, Department of Computer Science, Harvard University - "Fundamentals of Machine Learning"
- Dr. John W. Cain, Senior Lecturer, Department of Mathematics, Harvard University - "Current Research in Mathematics and Advice for Students"
- Dr. Michele Catasta – Stanford Univ., Dept. of Computer Science- "Hybrid Human-Machine Information Systems"
- Dr. Nuh Gedik – M.I.T., Department of Physics - "Seeing the ultrasmall, capturing the ultrafast!"
- Dr. Umut Eser – Cellarity, Head of Machine Learning Department, Former Researcher at Harvard Medical School - "Artificial Intelligence – Past, Present and Future"
- Dr. Johanna O'Day – Researcher at Stanford Bio-X Interdisciplinary Biosciences Institute - "Mechanical Engineering and Neuroscience"
- Dr. Darrel Deo – Researcher at Stanford Bio-X Interdisciplinary Biosciences Institute - "BioRobotics"
- Dr. Andrew Powers - Neurosurgeon at Beth Israel Deaconess Medical Center of Harvard University - "How to become a successful neurosurgeon"
- Dr. Albert Hsia - Head of Marketing at Merck, Harvard University alumnus - "Data Science Applications in medical fields"