$ Curriculum vitae · Updated October 2026
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Vikash Singh

Cleveland, OH 44106

+1 (216) 463-5254vikash@case.eduvikash-singh.me

linkedin.com/in/vikash-singh-johngithub.com/vicky157Google Scholar

Publications

[1] Beyond Solver Verdicts: Generative Reward Models for Autoformalization
Under review · ACL Rolling Review • September 2026
  • Vikash Singh, Debargha Ganguly, Aman Goel, Ali Torkamani, Xiaoxue Han, Joseph Lilien, Ferhat Erata, Vipin Chaudhary
  • [arXiv] [OpenReview]
[2] StochBench: A Domain-Specific Benchmark for Stochastic Processes in Lean
NeurIPS 2026 Workshop MATH-AI • December 2026
  • Idan Davidovich, Debargha Ganguly, Vikash Singh, Vipin Chaudhary
  • [arXiv] [Workshop]
[3] Auditing Cross-Lingual Fairness in Language Model Watermarking
NeurIPS 2026 Evaluations and Datasets Track • December 2026
  • Alexander Nemecek, Osama Zafar, Debargha Ganguly, Vikash Singh, Vipin Chaudhary, Erman Ayday
  • [Preprint]
[4] Imagining Recovery: Inference-Time Counterfactual Realignment for Vision-Language-Action Models
Preprint • August 2026
  • Yanyan Zhang, Disheng Liu, Kai Ye, Chaoda Song, Xinpeng Li, Mohsen Hariri, Vikash Singh, Yu Yin, Vipin Chaudhary
  • [Preprint]
[5] Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility
Preprint • August 2026
  • Mohsen Hariri, Weicong Chen, Nahal Shahini, Vikash Singh, Kai Ye, Amirhossein Samandar, Debargha Ganguly, Sreehari Sankar, Yanyan Zhang, Shouren Wang, Jerry Peng, Biyao Zhang, Michael Hinczewski, Vipin Chaudhary
  • [Preprint]
[6] K4-Serve: Robust Streaming Log Anomaly Detection for HPC & AI Infrastructure
PEARC 2026 • July 2026
  • Weicong Chen, Vikash Singh, Zahra Rahmani, Debargha Ganguly, Mohsen Hariri, Sean Maxwell, Sanjaya Gajurel, Hadrian Djohari, Vipin Chaudhary
  • [Paper]
[7] Sequent-Prover: Training Agents for Formal, Checkable SMT-based Reasoning
Preprint • 2026
  • D. Ganguly, W. Chen, M. Hariri, Vikash Singh, S. Sankar, S. Wang, Y. Yang, B. Zhang, C. Song, A. Nemecek, K. Ye, O. Zafar, E. Ayday, J. Stubbs, S. Iyengar, V. Chaudhary
  • [Preprint]
[8] CausalGuard: Conformal Inference under Graph Uncertainty
Preprint • May 2026
  • Vikash Singh, Weicong Chen, Debargha Ganguly, Yanyan Zhang, Nengbo Wang, Sreehari Sankar, Mohsen Hariri, Alexander Nemecek, Chaoda Song, Shouren Wang, Biyao Zhang, Van Yang, Erman Ayday, Jing Ma, Vipin Chaudhary
  • [arXiv]
[9] Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation
IEEE TPS 2026
  • Osama Zafar, Alexander Nemecek, Yiqian Zhang, Wenbiao Li, Debargha Ganguly, Vikash Singh, Vipin Chaudhary, Erman Ayday
  • [arXiv]
[10] Reliability-Gated Source Anchoring for Continual Test-Time Adaptation
Preprint • May 2026
  • Vikash Singh, Debargha Ganguly, Weicong Chen, Sabyasachi Sahoo, Sreehari Sankar, Biyao Zhang, Mohsen Hariri, Shouren Wang, Osama Zafar, Christian Gagné, Vipin Chaudhary
  • [arXiv]
[11] Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models
Preprint • May 2026
  • Yanyan Zhang, Chaoda Song, Vikash Singh, Xinpeng Li, Kai Ye, Zhe Hu, Zhongzhu Pu, Yu Yin, Vipin Chaudhary
  • [arXiv]
[12] A Survey on Agent Skills for LLMs: A Lifecycle Perspective from Construction to Ecosystems
SSRN Preprint • May 2026
  • Wang Yang, Chaoda Song, Xinpeng Li, Shouren Wang, Nengbo Wang, Yanyan Zhang, Chuang Ma, Debargha Ganguly, Vikash Singh, Shuai Xu, Jing Ma, Yu Yin, Vipin Chaudhary, Xiaotian Han
  • [SSRN]
[13] Path-Lock Expert: Separating Reasoning Mode in Hybrid Thinking via Architecture-Level Separation
Preprint • April 2026
  • Shouren Wang, Wang Yang, Chuang Ma, Debargha Ganguly, Vikash Singh, Chaoda Song, Xinpeng Li, Xianxuan Long, Vipin Chaudhary, Xiaotian Han
  • [arXiv]
[14] Toward Guarantees for Clinical Reasoning in Vision Language Models via Formal Verification
NeurIPS 2026 Workshop Med-Reasoner • December 2026
  • Vikash Singh, Debargha Ganguly, Haotian Yu, Chengwei Zhou, Prerna Singh, Brandon Lee, Vipin Chaudhary, Gourav Datta
  • [Preprint] [Workshop]
[15] CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG
ICML 2026
  • Nengbo Wang, Tuo Liang, Vikash Singh, Chaoda Song, Van Yang, Yu Yin, Jing Ma, Jagdip Singh, Vipin Chaudhary
  • [Preprint]
[16] Trust The Typical
ICLR 2026
  • Debargha Ganguly, Sreehari Sankar, Biyao Zhang, Vikash Singh, Kanan Gupta, Harshini Kavuru, A. Luo, Weicong Chen, Warren Morningstar, R. Machiraju, Vipin Chaudhary
  • [Preprint]
[17] VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning
EMNLP Findings 2026
  • Vikash Singh, Darion Cassel, Nathaniel Weir, Nick Feng, Sam Bayless
  • [Preprint]
[18] Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers
Findings of ACL 2026
  • Van Yang, Shouren Wang, Debargha Ganguly, Xinpeng Li, Chaoda Song, Vikash Singh, Vipin Chaudhary, Xiaotian Han
  • [ACL Anthology] [Preprint]
[19] Efficient Fine-Grained GPU Performance Modeling for Distributed Deep Learning of LLM
HiPC 2025 • September 2025
  • Biyao Zhang, Mingkai Zheng, Debargha Ganguly, Xuecen Zhang, Vikash Singh, Vipin Chaudhary, Zhao Zhang
  • [HTML] [arXiv]
[20] K4: Online Log Anomaly Detection Via Unsupervised Typicality Learning
HiPC 2025 • July 2025
  • Weicong Chen, Vikash Singh, Zahra Rahmani, Debargha Ganguly, Mohsen Hariri, Vipin Chaudhary
  • [HTML] [arXiv] [Code]
[21] Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks
NeurIPS 2025 • May 2025
  • Debargha Ganguly, Vikash Singh, Sreehari Sankar, Biyao Zhang, Xuecen Zhang, Srinivasan Iyengar, Xiaotian Han, Amit Sharma, S. Kalyanaraman, Vipin Chaudhary
  • [HTML] [arXiv] [Code]

Experience

Amazon Web Services May 2026 – Aug 2026
Applied Scientist Intern (Returning) New York City, NY
Amazon Web Services Aug 2025 – Nov 2025
Applied Scientist Intern New York City, NY
  • Authored VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning, pairing LLM reasoning with SMT solvers and verification-guided refinement. EMNLP Findings 2026.
  • Improved logical reasoning of LLMs using formal verification methods, including automated reasoning checks.
  • Enhanced the performance of several large language models by over 40% through agentic reasoning frameworks.
  • Manager: Darion Cassel, Sr. Applied Scientist, AWS
MGenio Jun 2024 – Aug 2024
Machine Learning Internship Cleveland, OH
  • Led self-driven research on machine learning models and their integration on IoT platforms.
  • Developed an efficient platform to manage data flow and monitor machine learning model training.
  • Designed a pipeline flow and automated data preprocessing system for machine learning models to feed directly into IoT Systems.
  • Manager: Satish Ramade, CEO, MGenio
DRDO, Ministry of Defence Jan 2022 – Sep 2022
Ml/DL Internship Chandigarh, India
  • Developed a sophisticated approach to enhance precision in satellite imagery analysis by employing segmentation, labeling, and training methods using Variational Autoencoders (VAEs), resulting in 83% accuracy.
  • Advisor: Dr. MK Kalra, Scientist G, Defence Geoinformatics Research Establishment (DGRE), DRDO
Hatchmarine Consultants Dec 2021 – Feb 2022
Research Intern Delhi, India
  • Developed machine learning models to predict river scour depth in Taiwan, informing strategic resource allocation.
  • Fine-tuned predictive models using Python (Scikit-Learn) to achieve high accuracy and meet project requirements.
  • Advisor: Dr. Karan Gupta, Technical Director and Founder
Case Western Reserve University Jan 2024 – Present
Teaching Assistant (Computational Perception) Cleveland, OH
  • Efficiently grade assignments, ensuring accuracy and providing constructive feedback.
  • Deliver engaging lectures on specialized topics, fostering student understanding and conduct effective office hours.
  • Professor: Dr. Michael Lewicki, Professor, Dept. of Computer Science & Engineering, CWRU
Indian Institute of Technology Mandi Feb 2021 – Aug 2022
Teaching Assistant (Data Science I, II, & III) HP, India
  • Conducted engaging lectures and facilitated Python hands-on lab sessions, enhancing students’ practical skills.
  • Assessed student understanding through various evaluation methods, including assignment grading and in-person viva sessions.
  • Professors: Dr. Deelip AD, Dr. Varun Dutt, Dr. Manoj Thakur, Professors, IIT Mandi

Education

Case Western Reserve University Aug 2024 – Present
Doctor of Philosophy in Computer Science Cleveland, OH
Case Western Reserve University Aug 2023 – May 2025
Masters of Science in Computer Science (Specialisation in ML/AI) Cleveland, OH
Indian Institute of Technology Mandi Jun 2019 – May 2023
Bachelors of Technology in Civil Engineering with minor in AI & Computer Science Mandi, India

Research Work

Case Western Reserve University Jan 2024 – Jul 2024
Advancements in XAI with Specialization in Counterfactual Explanation Methods Cleveland, OH
  • Engaged in leading-edge research on Explainable AI, particularly specializing in Counterfactual Explanation methods.
  • Advisor: Dr. Jing Ma, Assistant Professor, Department of Computer Science & Engineering, CWRU
IIT Mandi Jun 2020 – Jun 2021
Analysis of Nano Particles in Environment using Deep Learning Mandi, India
  • Developed a deep multi-modal architecture for accurately predicting the behavior of nanoparticles on different species using environmental data.
  • Advisor: Dr. Tanushree Parsai, Assistant Professor, IIT Madras

Projects

Enhanced YOLOv4 using SMM on OneAPI in SYCL | Python3, SYCL, CNN, PyTorch Nov 2023
  • Developed and integrated Enhanced YOLOv4 with SYCL-Python for advanced object detection algorithms.
  • Conducted performance optimization and applied ML techniques to improve real-time data processing.
Human Activity Detector | Machine Learning, Python3 Nov 2023
  • Built models using Logistic Regression, Decision Tree, and Support Vector Classifier, achieving 96% accuracy with Logistic Regression using accelerometer and gyroscope sensor data.
Landslide Warning System | Python3, Machine Learning, DNNs Aug 2020
  • Designed a data-driven predictive system analyzing hillside landslide risk factors like weather, slope, and temperature.

Technical Skills

  • Languages: Python3, C++, Java, JavaScript
  • Developer Tools: VS Code, Google Colab, Overleaf, High-Performance Cloud, OneAPI DevCloud
  • Technologies/Frameworks: TensorFlow, PyTorch, Scikit-Learn, OpenCV, Linux, GitHub

Relevant Coursework

  • Large Language Models
  • Data Structures & Algo.
  • High-Perf. Systems for
  • AI
  • Analysis of Algorithms
  • Deep Learning
  • Machine Learning
  • Data Science I, II, III
  • Computer Vision
  • Pattern Recognition
  • Data Privacy
  • Computer Security

Professional Service

  • 2026: ICLR (Reviewer); NeurIPS (Top Reviewer).
  • 2025: ICLR (Reviewer).

Academic Achievements & Recognitions

  • Awarded the Silver Medal and Director’s Medal for academic excellence at IIT Mandi.
  • Conducted lab sessions for the ”Training Program on Machine Learning for Ocean Acoustics” at DRDO-NPOL, Kochi.
  • Won two gold medals in badminton at the Inter IIT Sports Meet (2019, 2022).
  • Secured first place in the Inter IIT Tech Meet hackathon at IIT Delhi for plant disease detection algorithm.