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Prof. Aneesh Sreevallabh Chivukula

Assistant Professor,
Dept. of Computer Science and Information Systems

BITS Pilani Hyderabad Campus,  Jawahar Nagar, Secunderabad-500078.

Research Interests

Research Areas

Computational Algorithms, Deep Learning, Generative Learning, Adversarial Learning, Data Mining, Machine Learning, Supervised Learning, Game Theory, Robust Optimization, Tensor Methods, Time-Frequency Methods, Frequent Pattern Mining, Big Data Analytics, Adversarial AI, Generative AI, Robust AI, Hybrid AI, Explainable AI, Responsible AI, Augmented AI, Edge AI, Green AI, Frugal AI, Foundation Models, Learned Representations, Data Science, Bioinformatics, Computational Omics, Computational Biophysics

Ph.D. Scholars

  • Abhinav Kumar, Robust Neural Networks in Algorithmic Trading, Morgan Stanley
  • Venkatesh Natarajan, Computational Identification of Therapeutic Targets and AI-based Drug Repurposing in Parasitic Protists, AiZen Algo Pvt. Ltd.
  • Anup Bera, Robust and Scalable Multiagent Reinforcement Learning for Inventory Management, Algonatics InfoAI pvt ltd, PhD IMPACT(Industry Mentored PhD in Advanced and Cutting-edge Technologies) Programme
  • A Shivram, Bridging Robustness and Multiscale Analysis: Neural Networks and Foundation Models to Predict and Interpret Protein Mutations, PhD in Data Sciences for Global Health (jointly offered by BITS Pilani and the One Health Trust (OHT))
  • Cherukuri Satya Venkata Phani Kumar, Indic Foundation Models, IBM Software Labs
  • Vanshika Kumari, Machine Learning and Computational Biology, CDRF Fellowship in the Department of Biological Sciences

Junior Research Fellowships

  • Yasaswitha Tavva, Deep learning applications in Agriculture, BITS Pilani

Undergraduate Research Students

  • Anish Kumar Kallepalli, Fog Analytics and Deep Learning, B.E. (Hons.) Computer Science, BPHC
  • Anurag Saksena, Adversarial deep learning applications, B.E. Computer Science, BPHC
  • Gunjan Barua, Adversarial deep learning in recommendation, B.E. Computer Science and MSc. Mathematics, BPHC
  • Vishnu Sudhan, Deep Learning, B.E. (Hons.) Computer Science, BPHC
  • Rohit Yalavarthy, Recommender Systems, B.E. Electronics and Instrumentation, BPHC
  • Yuv Boghani, Foundation Models, Bachelor of Computer Science, The Pennsylvania State University
  • Swathi Reddy, Learned Representations, Integrated B.Tech and M.Tech in Information Technology, Atal Bihari Vajpayee Indian Institute of Information Technology and Management, Gwalior
  • Ananya Gomathi, Hybrid deep learning, M.Sc. Mathematics, BPHC
  • Shramadeep Debnath, Tensor Methods, BS in Data Science and Applications, Indian Institute of Technology Madras
  • Leah K John, Adversarial reinforcement learning for recommendation, Dual Degree, B.E. Computer Science & M.Sc. Mathematics, BPHC
  • Anish Devnoor, Robust Human-Robot Handovers through Adversarial Learning, B.E. Electronics & Instrumentation, BPHC
  • Pranav Chintareddy, Adversarial Reinforcement Learning, Bachelor of Science in Computer Engineering, Purdue University
  • Ankit Chakraborty, Frequent Pattern Mining, Senior AI Developer, RiskInsight Consulting Pvt Ltd.
  • Ananya Kapoor, Multi modal prediction models for endometriosis using EHR data, Dual Degree, B.E. Computer Science & M.Sc. Economics, BPHC, Off-campus Thesis at Perelman School of Medicine at the University of Pennsylvania