Professor and Director, Data Management Research Lab (DaMRL)
School of Computing and Information Science
Florida International University (FIU)
Office: CASE 238B
Phone: (305)348-9934
Email: janki.bhimani@fiu.edu
Janki Bhimani is an eminent figure shaping the landscape of technology and research. Her primary focus encompasses Emerging Memories, Flash-Based Storage Systems, Machine Learning, Cloud Computing, High-Performance Computing, and Parallel and Distributed Computing. She delves into Performance Modeling, Resource Management, and Capacity Planning across interdisciplinary domains. With unmatched expertise and experience in new memory and storage devices, she leaves an indelible mark on the data storage management community. Honored with accolades like FIU Top Scholar, KFSCIS Excellence in Applied Research, and Distinguished Reviewer Award, her contributions are a testament to her impact. Best Paper Awards and publications in highly selective conferences and high impact journals underscore her influence. A trailblazer in innovation, she is a lead inventor on many top-grade patents. Hand-in-hand with her research, she is very passionate about teaching and mentoring. Prior to joining at Florida International University, she previously served Northeastern University as an instructor. She also closely worked with research scientists at Samsung Semiconductor Research Labs towards evolving flash-based SSDs. In her free time, Janki is a creative visual artist. Far from home, amidst nature, she finds her inspiration to paint. She enjoys bringing motivation, healing, and encouragement through the canvas.
Dr. Janki Bhimani is the Director of the Data Management Research Laboratory (DaMRL). Her research focuses on:
- Memory and Storage Systems;
- Cloud Computing;
- Performance Modeling and Prediction;
- Capacity Planning; Resource Management;
- Applied Machine Learning;
- Datacenter Endurance and Reliability Management;
- High-Performance Computing;
- Ph.D. in Computer Engineering, Northeastern University, 2019.
- M.S. in Electrical and Computer Engineering, Northeastern University, 2016.
- B.S. in Electrical and Electronics Engineering, GITAM University, 2013.
CIS 3530: Data Structures
The course covers the collection of classic algorithmic techniques that are useful for solving problems. These algorithms include sorting algorithms (e.g., selection sort, insertion sort, quicksort), recursive backtracking search, tree algorithms (traversals, binary search algorithms), and graph algorithms (traversals, spanning trees forests, shortest paths, etc.). It covers exhaustive approaches, divide and conquer, greedy algorithms, backtracking, branch and bound, and iterative improvement, algorithm analysis, asymptotic notation, and recursion. Data structures covered include vectors, stacks, queues, trees, graphs, priority queues, hashtables, and heaps.
Syllabus – https://damrl.cis.fiu.edu/cop-3530-syllabus/
Spring 2020, Fall 2020, Spring 2021, Fall 2021, Spring 2022, Fall 2022, Spring 2023, many more…
CIS 5346: Storage Systems
Covers the introduction to storage systems, storage devices (hard disk drives, solid-state drives), storage system components, storage architecture, large-scale distributed storage systems, data center storage, non-volatile memory (NVM), reliability and fault tolerance (RAID systems), performance, file-systems, operating systems storage management, memory and storage concepts (caching, consistency, and deduplication), disks and scheduling, emerging storage technologies and future trends
Syllabus – https://damrl.cis.fiu.edu/cis-5346-syllabus/
Fall 2019, Spring 2022, Spring 2023, Fall 2023, many more…
EECE 2560: Fundamentals of Engineering Algorithms
Covers the design and implementation of algorithms to solve engineering problems using a high-level programming language. Reviews elementary data structures, such as arrays, stacks, queues, and lists, and introduces more advanced structures, such as trees and graphs, and the use of recursion. Covers both the algorithms to manipulate these data structures as well as their use in problem-solving. Emphasizes the importance of software engineering principles. Introduces algorithm complexity analysis and its application to developing efficient algorithms
Fall 2017
[Janki_Bhimani_FIU_CV] (updated by Oct, 2023)
