An Informal Introduction.
I’m Sergius Nyah, a pre-final year Computer Science student at University of Buea, Cameroon. ( If you’re familiar with Banff, Alberta, Canada, you should appreciate the stunning scenery of Buea as well.)
I first encountered the term “Geometry” in 9th grade (Form 4), in our Math class, and had no idea by then of its true significance.
Late 2022 was a peculiar period for me. My very special friend and past SGI fellow introduced me to the Summer Geometry Initiative. From then my immediate reaction was to research on it, connect with past fellows via LinkedIn, and bookmark it for applications, with only very little knowledge on the topic itself, apart from math theories and coding knowledge acquired in the classroom.
What the SGI means to me.
Permit me re-define what the SGI is in two ways. First from the perspective of a prospective applicant, and second as a fellow 🙂
As an applicant, the SGI is a six-week paid summer research program introducing undergraduate and graduate students to the field of geometry processing.
For current or former fellows, the SGI is an intense period of reading research papers engaged around Geometry, listening to talks you may find interesting, learning math for those without a strong math background, acquiring coding skills for students new to programming, and using this knowledge to solve problems on a daily basis, all while learning from Rock-star professors and brilliant students from around the world. Makes sense ? (Without forgetting the generous stipend 🙌🏿 and swag pack 🙂
My Experience so far!
July 8th was the much-anticipated day. That serene evening, we were officially welcomed to the Summer Geometry Initiative 2024 by Professor Justin Solomon, SGI chairman and organizer. My heart boggled with joy as I finally met him and other fellows (now friends 🙂 like Megan Grosse, Aniket Rajnish, Johan Azambou, Charuka Bandra, and a few others, with whom I had been chatting with. Proff Justin opened the floor for the tutorial week and provided us with a brief overview of what the upcoming weeks would entail.
The Tutorial week was a perfect blend of fun and fast-paced learning. Right after Prof. Justin’s welcoming, we had our first tutor for Day 1 — the “Marvelous” Professor Oded Stein, a Computer Science professor from the University of Southern California and tutorial week chair for SGI ’24. Prof. Oded introduced us to Geometry Processing (GP) and its significance to various groups, from artists to programmers. He also taught on surfaces, meshes, explaining how to represent them using triangles and faces, and how to store them using object-lists and face-lists. Additionally, we explored the different types of curvatures (normal curvature, Mean curvature, Principle curvature, Gaussian curvature, and Discrete Gaussian curvature). Next was a session on visualizing 3D data, led by Qingnan Zhou, an Engineer from Adobe Research.
On Day 2, led by Richard Liu, PhD student at the University of Chicago, we focused on parameterization and its vast potential in related fields such as computer graphics. Right after launch/exercise/siesta/rest/fun/ break 😊, we welcomed Dale Decatur, still a PhD student at the University of Chicago, who shared valuable insights on the technical know-how that would be beneficial during our research weeks.
Silvia Sellán, a pre-postdoctoral fellow at MIT and an incoming Professor at the University of Columbia, was in charge of Day 3. She spoke on the various methods of representing shapes, exploring the advantages and disadvantages of each method with regards to computer resources such as memory and processing power. The day ended with an interactive presentation from Towaki Takikawa, a PhD student at the University of Toronto, who focused on Neural Fields.
Day 4, led by Derek Liu, a research scientist at Roblox, taught on Mesh Simplification and Level of Detail (LOD). He mentioned that there are three types of Mesh simplifications: Static Simplification, which includes creating separate level of detail (LOD) models before rendering, Dynamic Simplification which provides a continuous spectrum of LOD models instead of a few discrete models, and View-Dependent Simplification where the level of detail varies within the model. Later on, Eris Zhang – a Stanford PhD student delved deeper into more technical concepts that proved to be highly beneficial for both the day’s exercises and the upcoming research weeks.
On Day 5, Dr. Nicholas Sharp, a research scientist at NVIDIA and inventor of Polyscope, a highly beneficial software tool in the GP community, led the session, marking the conclusion of the tutorial week. Dr. Nick discussed good and bad surface meshes (data), and the process of remeshing ( which involves turning a bad mesh into a good one). Additionally, we hosted a complementary session featuring guest speaker Zachary Ferguson, a postdoc researcher at MIT, who discussed handling floating points in collision detection.
In summary, Research Week 1 was led by Dr. Nicholas Sharp, research scientist at NVIDIA (A.K.A The G.O.A.T – Greatest Of All Time 🙌🏿). Our research topic focused on how “Well” various surfaces can approximate deforming meshes. I learned about chamfer distances, the Gromov-Hausdorff distance (the largest of all minimum (Chamfer) distances along two curves), and the polyline algorithm. We concluded the week with our first group article on How to Match the Wiggleness of Two Shapes, published by Artur Bogayo.
During Research Week 2, my team mates — Nicolas Pigadas and Champ – and I, led by Dr. Karthik Gopinath from Harvard Medical School explored a nouvel way of parcellating cortical meshes as 2D segments via the process of Pseudo-Rendering.
To conclude this post, I’d like to share the biggest lessons I’ve learned from the first four weeks of the SGI.
- Lesson 1: Always request a helping hand when you can’t figure things out. There’s no benefit struggling with a problem when others are just a step away. Don’t hesitate to ask for help!
- Lesson 2: Learn to adapt fast to changes. The SGI, like life in general, is fast-paced. Adapting to new research projects and working with different mentors and colleagues is a valuable skill that will significantly boost productivity.
- Lesson 3: Cultivate Self-discipline! Learning new concepts takes time. Sitting on that reading table for hours could be tiring, but please, persevere! The juice is definitely worth the squeeze!
- Lesson 4: Be transparent with your mentors/supervisors. They may be able to figure things out, but being honest about your situation demonstrates integrity and builds trust. Being honest with what went wrong is a quality people value in long-term collaborators. Don’t sugarcoat things. Tell them what went wrong. They might bite you, but won’t eat you! 😄
- Lesson 5: Do what needs doing, regardless. I started writing this blog many days ago, but only got to finish today due to a weeks-long (ongoing) power outages. And here I am now, in the dim light of a local bar at an odd hour, exposed to thieves and weird stuff (like who knows?). So do what you should do! Excuses might seem valid at the moment, but will totally seem completely irrelevant in the future.
As the SGI winds down, I’m filled with so much gratitude for this once-in-a-lifetime opportunity. I brace myself with resilience, dedication, and an insane collaboration towards the rest of our projects, with a full focus on making the most out of this tremendous initiative I’m blessed to have taken part in. A huge thank you to all my mentors, fellows-turned-friends, and everyone for making this year’s SGI what it already is and soon would be!
A luta continua!
