Hello I'm
Valmeekam Karthik
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For a tour into my world
I am a
I was born in Hyderabad, India but I grew up in two quite opposite places (weather-wise); Addis Ababa, Ethiopia (from K.G. to 5th Std) and Ibra, Oman (5th to 10th Std).
I have always loved stories and thought of myself as a storyteller.
After my frivolous attempt at JEE, I joined Vellore Institute of Technology to learn and tell stories about Computer Science and Engineering.
During my Masters at Arizona State University, I realized that rigorously formalized ideas are great stories to tell!
Hence I opted to pursue PhD under Prof. Subbarao Kambhampati. Currently, Large Language Models (LLMs) and Planning are keeping me occupied!
In my free time, I write screenplays, dance, learn photography, play my keyboard and listen to a wide variety of music ranging from heavy metal to carnatic ragas.
Passing through the Academic Jungle
2021 - Present.
Arizona State University.
Tempe, Arizona, US.
PhD in Computer Science.
GPA* 4.0/4.0
Graduate Research Assistant at Yochan under Prof. Subbarao Kambhampati
2019-2021.
Arizona State University.
Tempe, Arizona, US.
M.S. in Computer Science.
GPA 4.0/4.0
Graduate Research Assistant at Yochan under Prof. Subbarao Kambhampati
Thesis: A Study of Explainable Decision Support for Longitudinal Sequential Decision Making
2015-2019.
Vellore Institute Of Technology.
Vellore, Tamilnadu, India.
B.Tech. in Computer Science and Engineering.
GPA 9.19/10.0
Research Aide under Prof. Anuradha J
Vice-Chair Management of Codechef-VIT
2013-2015.
Narayana Junior College.
Hyderabad, Telangana, India.
Intermediate (11th & 12th Std).
Percentage: 95.1%
2007-2013.
Learning - A continuous process
| Programming Languages | Python, C++, JavaScript, HTML/CSS, SQL, Bash, SAP-ABAP |
|---|---|
| Frameworks | HuggingFace Transformers, LoRA PEFT, Flask, Bootstrap, jQuery, D3.js, Pytorch, Tensorflow, Keras, OpenCV, ROS |
| Tools | Git, Docker, Kubernetes, AWS, GCP, Jupyter, Colab, Adobe Photoshop, Adobe Premiere Pro, Adobe Lightroom, Blender, Gazebo, Unreal Engine |
Execution - That's how dreams become reality
Publications.
*Formalizing Curiosity*
- On the Planning Abilities of Large Language Models--A Critical Investigation
Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, Subbarao Kambhampati
NeurIPS 2023 (Spotlight) (Earlier at KLR@ICML 2023) - Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
Lin Guan*, Karthik Valmeekam*, Sarath Sreedharan, Subbarao Kambhampati
NeurIPS 2023 (Earlier at KLR@ICML 2023)
*equal contribution - PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
Karthik Valmeekam, Matthew Marquez, Alberto Olmo, Sarath Sreedharan, Subbarao Kambhampati
NeurIPS 2023 (Benchmark Track) - Can Large Language Models Really Improve by Self-critiquing Their Own Plans?
Karthik Valmeekam, Matthew Marquez, Subbarao Kambhampati
FMDM@NeurIPS 2023 - Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences
Lin Guan, Karthik Valmeekam, Subbarao Kambhampati
ICLR 2023 - Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change)
Karthik Valmeekam, Alberto Olmo, Sarath Sreedharan, Subbarao Kambhampati
FMDM@NeurIPS 2022 - RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions
Karthik Valmeekam, Sarath Sreedharan, Sailik Sengupta, Subbarao Kambhampati
ICAPS 2022; AAAI 2021 Demos - Opinion Mining on Emojis using Deep Learning Techniques
Karthik Valmeekam, Dheeraj Nair, J Anuradha
Procedia Computer Science, 2018
Projects
*Get the engine started.*
- LLMs for Planning
- Reinforcement Learning for Sequence: An Imperfect Information Board Game
- High Speed Autonomous Drifting using Deep Reinforcement Learning
- Implementation and Evaluation of Nash Q Learning
- Parsing and Writing AI Planning models (represented in PDDL)
- Paws in Space - Data Visualization
- How to Open in Chess? - Data Visualization