Difference between revisions of "CyberMath Academy"

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CyberMath Academy Camp in Boston, MA has been designed for high-performing students who are looking for a challenging environment in which they can master advanced topics in an environment that provides a friendly challenge with the participation of brilliant students from all over the globe.
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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===
 
===Locations and Dates===
 +
Boston: Harvard University - July 17-28, 2023
  
Boston: Harvard University    - July 15– July 27, 2019
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===Who can participate?===
 +
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===  
 
===Courses===  
  
MATH: Advanced Middle School Math with MathCounts/AMC 8-10 Problems, Advanced High School Math with AMC 10-12/AIME Problems, Advanced AIME with Proofs.
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* Advanced Middle School Math
  
CODING: Java Processing, Python Programming, C++ Programming and USACO Bronze, USACO Silver and AP Computer Science A
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This course covers the main topics in middle school math. Students will be mastering these topics while solving challenging problems. They go above and beyond Common Core standards in this brain-stimulating course. Students also solve mathematical puzzles and cyphers and learn topics that are typically not covered at traditional school settings.
  
ROBOTICS
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Recommended Grade Levels: Although this course is typically recommended for students in grades 4th-8th, and anyone in 8th grade or below may enroll, we encourage younger students to participate as well!
  
GAME DESIGN
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Course Description: This course will familiarize students with the essential concepts and techniques in Pre-Algebra, Algebra I, Geometry, Number Theory and Combinatorics. We will have a specific emphasis on problem solving where the students will constantly be challenged to think creatively.
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* Advanced High School Math
  
PHYSICS: AP Physics A and USAPhO F=m*a
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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.
  
Advanced Math Program Designed by Justin Stevens
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Recommended Grade Levels: Although we do not limit students by grade level, this course is typically recommended for advanced 7th and 8th graders and high school students.
- Author of Olympiad Number Theory Through Challenging Problems Book
 
  
Math Olympiad Program designed by Evan Chen
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Course Description: This course will familiarize students with the essential concepts and techniques in Algebra II, PreCalculus, Combinatorics, Number Theory, and Geometry. We will have a specific emphasis on problem solving where the students will constantly be challenged to think creatively.
- One of the leaders of the USA IMO Team
 
- The Main Exam Coordinator for the USA Olympiad Team Selection Tests
 
- The Assistant Academic Director of the Math Olympiad Summer Program (MOP)
 
- The Co-editor-in-chief for the USA Math Olympiad (USAMO)
 
  
 
===Daily Schedule===
 
===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 of our 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 of the former guest lectures. Similar ones to be scheduled in 2023.
 +
 +
* 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"
  
9:00 am  12:15 pm Morning classes
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* Dr. Darrel Deo Researcher at Stanford Bio-X Interdisciplinary Biosciences Institute - "BioRobotics"
12:15 pm – 1:15 pm Lunch and Activity time
 
1:15 pm  – 4:30 pm Afternoon classes
 
  
===MATH COURSES===
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* Dr. Andrew Powers - Neurosurgeon at Beth Israel Deaconess Medical Center of Harvard University - "How to become a successful neurosurgeon"
  
Morning Sessions: Combinatorics and Geometry topics will be covered.
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* Dr. Albert Hsia - Head of Marketing at Merck, Harvard University alumnus - "Data Science Applications in medical fields"
  
Afternoon Sessions: Algebra and Number Theory topics will be covered.
+
===MORE INFORMATION===
  
For more information: https://www.cybermath.org
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For more information: https://cybermath.org

Latest revision as of 19:10, 22 December 2022

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

Who can participate?

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 will be mastering these topics while solving challenging problems. They go above and beyond Common Core standards in this brain-stimulating course. Students also solve mathematical puzzles and cyphers and learn topics that are typically not covered at traditional school settings.

Recommended Grade Levels: Although this course is typically recommended for students in grades 4th-8th, and anyone in 8th grade or below may enroll, we encourage younger students to participate as well!

Course Description: This course will familiarize students with the essential concepts and techniques in Pre-Algebra, Algebra I, Geometry, Number Theory and Combinatorics. We will have 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 Levels: 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 will familiarize students with the essential concepts and techniques in Algebra II, PreCalculus, Combinatorics, Number Theory, and Geometry. We will have 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 of our 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 of the former guest lectures. Similar ones to be scheduled in 2023.

  • 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"

MORE INFORMATION

For more information: https://cybermath.org