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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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gallery
media
2022 Texas Motor Speedway 2nd Place
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Teaser-Reel Highlights from our 2nd place finish at the 2022 Texas Motor Speedway autonomous racing competition 
BBC News Feature on Autonomous Racing
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Interview with BBC News, February 2024, trackside at CES2024.
Right On Track: Indy Autonomous Challenge
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As Team Manager and Simulation Lead for AI Racing Tech, I gave an interview for ADAS & Autonomous Vehicle International’s Spring 2024 cover story.
PRI Magazine Report on Autonomous Racing
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Interview in Performance Racing Industry magazine, April 2024.The interview was part of PRI’s ongoing coverage of emerging motorsport technologies 
portfolio
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publications
Layered MPC Distillation for High-Speed Sim-to-Real Adaptation
Published in *PENDING APRIL SUBMISSION* , 2025
Layered MPC Distillation uses real and simulated data for MPC-guided policy distillation, enabling adaptive learning beyond traditional MPC in an online neurosymbolic framework. Further details redacted pending April CoRL submission.
Recommended citation:
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Approximate KV Cacheing for Accelerating Transformers in Sequential Decision Making
Published in *PENDING MAY SUBMISSION* , 2025
Preliminary results reveal notable improvements in efficiency and performance under challenging learning scenarios. Further methodology and detailed findings are redacted pending a May NeurIPS submission.
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TBD
Published in , 2025
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talks
ROS by the Bay: AI Racing Tech at MTV Google Headquarters
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I presented at ROS by the Bay, a bay area robotics event hosted by Open Robotics, alongside Siddharth Saha, Senior Technical Lead at AI Racing Tech. Our talk covered building extreme-performance autonomous systems using ROS and AI edge computing for high performance safety critical autonomy applications.
DARPA ANSR PI Meeting
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Presented our team’s recent progress on neurosymbolic methods research as part of the DARPA Assured Neurosymbolic Learning and Reasoning (ANSR) program. We discussed our advancements in combining neural networks with symbolic reasoning techniques to enhance system robustness and assurability. 
Speakers left to right: Shankar Sastry, Sergey Levine, C.K. Wolfe, and Somil Bansal 
CES 2024: AI Driver Training from SIM to REAL
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CES 2024 in Las Vegas, NV, Jan. 29, 2024 – Hosted by Paul Mitchell, the IAC panel featured esteemed panelists C.K. Wolfe of AI Racing Tech, Program Manager at University of California, Berkeley, Alvaro Velasquez, Program Manager at DARPA, and Tino Schulze, Executive Vice President Automated Driving & Software Solutions at dSPACE. The CES panel focused on several critical aspects of AI driver training and the transition from simulation to real-world applications. 
CES 2024: Watch the full Talk on AI Driver Training from SIM to REAL Panel
teaching
Teaching Assistant - EE361 Electromagnetic Fields (Fall 2020)
Teaching, UWM College of Engineering & Applied Science, EE361: Electromagnetic Fields, 2020
Undergraduate course covering principles of electrostatics and electromagnetics, laws of fields, resistance, inductance, capacitance, dielectrics, energy storage, and Maxwell’s field equation.
Teaching Assistant - EE361 Electromagnetic Fields (Spring 2021)
Teaching, UWM College of Engineering & Applied Science, EE361: Electromagnetic Fields, 2021
Undergraduate course covering principles of electrostatics and electromagnetics, laws of fields, resistance, inductance, capacitance, dielectrics, energy storage, and Maxwell’s field equation. Created a YouTube tutorial channel for additional study resources. During Spring 2021, I served as a Teaching Assistant for ELECENG 361, supporting students in this advanced electromagnetics course. My responsibilities included leading discussion sections, assisting in laboratory activities, and guiding problem-solving related to Maxwell’s field equations. For more information, visit the current course offerings.
Graduate Student Instructor - PHYSICS 8A Introductory Physics (Fall 2021)
Teaching, UC Berkeley, Physics Department, 2021
Introductory course in physics focusing on forces, kinetics, equilibria, fluids, waves, and heat. This course presents concepts and methodologies for understanding physical phenomena. During Fall 2021, I served as a Graduate Student Instructor for Physics 8A, supporting students in this foundational physics course. My responsibilities included leading lab sections, guiding experimental work, and helping students develop core skills in applying physical principles to real-world scenarios. For more information, visit the official Physics 8A course page.
Graduate Student Instructor - PHYSICS 8A Introductory Physics (Fall 2021)
Teaching, UC Berkeley, Physics Department, 2021
Introductory course in physics focusing on forces, kinetics, equilibria, fluids, waves, and heat. This course presents concepts and methodologies for understanding physical phenomena, and is particularly useful preparation for upper division study in biology and architecture. In this semester I recieved the Outstanding GSI Award (top ~5% of Berkeley GSI’s). During Fall 2021, I served as a Graduate Student Instructor for Physics 8A, supporting students in this foundational physics course. My responsibilities included leading lab sections, guiding experimental work, and helping students develop core skills in applying physical principles to real-world scenarios. For more information, visit the official Physics 8A course page.
Graduate Student Instructor - PHYSICS 77 Computational Physics (Summer 2022)
Teaching, UC Berkeley, Physics Department, 2022
Introductory scientific programming in Python with examples from physics. Topics include: visualization, statistics and probability, regression, numerical integration, simulation, data modeling, function approximation, and algebraic systems. During Summer 2022, I served as a Graduate Student Instructor for Physics 77, supporting students in this introductory computational course. My responsibilities included leading course components, providing assistance with Python programming, and helping students build foundational skills in applying computational techniques to physics problems. I also created supplemental material and discussion sections tailored for the summer session. For more details, visit the official Physics 77 course page, or explore the unlisted course content playlist I created in the summer of 2022 on YouTube.
Head Graduate Student Instructor - PHYSICS 8A Introductory Physics (Fall 2022)
Teaching, UC Berkeley, Physics Department, 2022
As the Head Graduate Student Instructor for Physics 8A: Introductory Physics at UC Berkeley during Fall 2022, I led a team of 15 GSIs supporting a combined section taught by 2 instructors and enrolling over 600 students.