Head: Dr. N Uday Kiran
The composition of the teaching faculty of the Department of Mathematics & Computer Science (DMACS) provides a mix of expertise in Mathematics and Computer Science. Given this unique position, DMACS is committed to fully exploit its potential and venture into interdisciplinary research. The Department offers excellent facilities for research and projects in theoretical as well as technological areas.
The active areas of research in Mathematics are Ecological and Epidemic Modelling, Microlocal Analysis, Dynamical systems, Differential Equations-Existence and Qualitative study and Interface Problems. High Performance Computing, Image processing and Computer Vision, Machine Learning & Deep Learning, Datamining and Cryptography are major thrust areas in Computer Science. The faculty keeps abreast of the latest developments in their fields by access they have to the leading journals in their respective areas and also by way of collaborating with academia and industry, both in India and abroad. The department has impressive list of adjunct faculty from India and abroad who regularly visit the SSSIHL, adding strength and insight to the academic and research programs. The department has signed several MoUs with IT industries to develop solutions/products of social relevance.
Vision
To achieve excellence and recognition in teaching and research in the fundamental and applied areas of Mathematics, Computer Science and Computational Sciences, with a focus towards serving society at large.
Programmes Offered
Postgraduate
M.Sc. in Mathematics
Professional
M.Tech. in Computer Science
Research
Ph.D.
Facilities
The following facilities are available for students at the Department across all the campuses:
Computing & Networking Facilities
Boston 4U AMD Fenway Server Solution (x2)
4x AMD Opteron 16C 6376 2.3GHz 16M processors
16x 16GB DDR3-ECC reg RoHS (256GB total)
5x 2TB 3.5” 7.2K RPM SATA HDD
NVIDIA Kepler K20 GPU Card
Supermicro 4U Rack server
Processor: 4 X Abu Dhabi 16C 6376 2.3G 16M 6400MT (64 Cores)
Chipset: AMD SR5690/SR5670/SP5 100 Chipset
RAM: 192 Gb DDR 3 ECC Reg
HDD: 5 X 2TB SATA
NVIDIA Kepler K20 GPU Card
Super Micro4U Rack Server INTEL Fenway (x3)
4x Intel Ivy Bridge E5 – 4610 V2 8C 2.3GHz 16M 7.2GT /s QPI
16x 16GB DDR3-1600ECC reg RoHS (256GB total)
SATA HDD (10TB)
NVIDIA Kepler K40 GPU Card
Storage Area Network (SAN)
108 TB storage capacity
Intel C612 chipset; Haswell 8C E5 2630V3 2.4GHz 20 MB 8GT/s
144GB DDR4 RAM
Supermicro 4U Rack Server – Xeon Phi, TITAN X
Processor: 2 x E5-2609 (10M cache, 4 Cores, 4 Threads, 2.40 GHz (80W) 6.40 GT/sec Intel® QPI, 32nm)
RAM: 8 x 8GB DDR 3 ECC Total 16 DIMMS (Total 64 GB)
Card: 1 x Xeon Phi 5110P, 60-Core, 1.053GHz, 8GB, 300W, PCIe2
GPU: NVIDIA TitanX GPU
Supemicro 4U Rack Server with 3 Nvidia GPUs
Processor: 2x Intel Xeon Processors E5-2640 v4 2.4Ghz
Memory: 128 GB DDR4 2400 MHz ECC RAM
Storage: 1x 6 TB SATA3 7200 Enterprise Grade HDD 1x 960GB SSD
Power Supply: 2000 W High Efficiency (96%), redundant PSU(s).
GPU Card: 3 x Zotac GeForce RTX 2080 Ti Blower Cooler 11 GB GDDR6
Workstation AUK_ZEUS
Workstation – 4U Tower single socket workstation with 1600W 80Plus Redundant PSU
Processor – Intel Xeon Gold 5318Y,
24 Core, 2.10 GHz Processor
RAM – 256 GB DDR4 3200
HDD – 8TB 7200 RPM SATA HDD
SSD – 1TB NVMe SSD
NVidia RTX 4090 GPUs X 2 nos.
HP 2910-24G 24 Port 10/100mbps Manageable L3 Switch: 1 No.
HP 2530-24G 24 Port Giga Manageable L2 Switch: 10 Nos
The computing facility at DMACS supports research in the areas of Computer Vision, ML & DL, Security, HPC, etc.
Department Libraries
The department has a good library for books and monographs, as well as access to journals in various domains of interest in mathematics and computer science.
We are part of INFONET, E-Journal Consortium(https://ess.inflibnet.ac.in/eres.php?memID=92). We access nearly 3000 scientific journals from eleven international publishers through INFLIBNET. All these Scientific Journals are available to all the students and staff over our university campus network. These Journals cover various disciplines pursued by the department. Given below are the names of some of the publishers enlisted in the INFLIBNET:
- Web of Science
- Taylor and Francis
- Springer Link 1700 Collection and Nature Journal
- Project Muse
- Oxford University Press
- JGate Plus (JCCC)
- Institute for Studies in Industrial Development (ISID) Database
- Annual Reviews
Faculty
Achievements & Participation 2019/20
Dr. K S Sridharan
Resource Person, Faculty Development Programme on Machine Learning & Deep Learning and Applications, Dept. of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 25-26 2019.
Prof. V Chandrasekaran
Resource Person and Invited talk, Faculty Development Programme on Machine Learning & Deep Learning and Applications, Dept. of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 25-26 2019.
Sri Darshan Gera
Resource person, Faculty Development Programme on Machine Learning & Deep Learning and Applications, Dept. of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 25-26 2019.
Resource person, Workshop on Recent trends in Machine Leaning and Importance of Python Programming, Department of Computer Science, Chennai National Arts and Science College, 7 Mar 2020.
Sri V Bhaskaran
Feasibility Study of an inter-operable data analysis platform for clinical data, Technical Poster accepted at IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), Pune, 16-19 Dec 2019.
Dr. Ajith Padyana
Mentoring and guiding Atal Tinkering Lab students for their research thinking and innovation in latest trends and technology.
Dr. Pallav Kumar Baruah
Key Note Talk on Set Membership Problem, Workshop on Geo Spatial Technology and its Applications, Dr. Ambedkar Institute of Technology, Bangalore, 28-30 Aug 2019.
Resource Person and three Invited talks, Faculty Development Programme on Machine Learning & Deep Learning and Applications, Dept. of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 25-26 2019.
Resource Person on a Panel Discussion: Fostering Industry Academia Partnership, International Conference on High Performance Computing, Data, and Analytics (HiPC 2019), Pune, 16-19 Dec 2019.
Attended the 9th IEEE International Advance Computing Conference (IACC 2019), MAM College of Engineering, Tiruchirappalli, Tamil Nadu, 13-14 Dec 2019.
Attended the 2nd Workshop on Education for High Performance Computing (EduHiPC 2019), Hyderabad, 16-17 Dec 2019.
Attended a Faculty Development Programme on Recent Trends in Information Technology, Dept. of Information Technology, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, 18-24 May 2020
Attend a #EduTECHAsia Webinar on Education going online, now and for the future, 14 May 2020.
Dr. S Balasubramanian
Second Runner up in Indian Driving Dataset Semantic Segmentation Challenge, Workshop on Recent trends in Machine Leaning and Importance of Python Programming, Department of Computer Science, Chennai National Arts and Science College, 7 Mar 2020.
Completed an online certification course on Coursera, Introduction to Ordinary Differential Equations, authorized by Korea Advanced Institute of Science and Technology (KAIST).
Dr. Avadhesh Kumar
Awarded a certificate for serving as a Reviewer of Mathematical Methods in the Applied Sciences, an SCI Journal, 2020.
Sri Udhay R Shankar
Attended the 9th IEEE International Advance Computing Conference (IACC 2019), MAM College of Engineering, Tiruchirappalli, Tamil Nadu, 13-14 Dec 2019.
Sri Sapan Gupta
Attended a workshop on R Programming Language, IIT Bombay, 9 Nov 2019.
Doctoral Research Scholars
Achievements & Participation 2019/20
Sri Ananth V S
Selected for Direct Senior Research Fellowship by Council of Scientific and Industrial Research (CSIR).
Sri S R Pranav Sai
Qualified in the Institute of Actuaries of India (IAI) Exams in ACET (Actuarial Common Entrance Test), CS1 (Actuarial Sciences) and CP3 (Communication Practice)
Rohan Yashraj Gupta
Qualified in the Institute of Actuaries of India (IAI) Exams in ACET (Actuarial Common Entrance Test) and CM2 (Financial Engineering and Loss Reserving)
Students
Achievements 2019/20
Projects & Dissertations
Listed below are the postgraduate and professional programme projects and dissertations for the academic year 2019/20:
SSSIHL Projects & Dissertations – 2019/20 – M.Sc. in Mathematics | M.Sc. in Data Science & Computing | B.C.A. | M.Tech. in Computer Science
National Examinations
A high percentage of SSSIHL postgraduate students qualified in national exams such as the GATE/JEST or the CSIR-UGC NET in 2019/20. The list below includes the national rank for each exam (if available):
GATE
Ajay Mukund (Computer Science) – 13948
Rishi Sridhar Rao (Computer Science) – 8249
CSIR UGC-NET for JRF
Ajay Mukund (Computer Science)
UGC-NET (LS)
Ajay Mukund (Computer Science)
Research Areas
To access the Research Areas for the department, click here.
Research Publications
The faculty and doctoral research scholars at SSSIHL actively contribute to a wide range of publications in esteemed peer-reviewed journals. A detailed department-wise list of these publications is available on the Research Publications page.
Funded Research Projects
A Commutative Algebraic Approach to Generating Functions
Science and Engineering Research Board (SERB) – ₹15 Lakhs (2024-2027)
Principal Investigators: Dr. N Uday Kiran
The project aims to explore the intricate connections between algebraic tools and various aspects of number theory, with a particular focus on generating functions and trigonometric sums. In our previous works, we introduced a novel approach using commutative algebra to simplify and generalize known results, highlighting a striking parallel between the reciprocity laws and a partial fraction identity. This work extends to degenerate Bernoulli and degenerate Euler numbers, Umbral Calculus, and Hypergeometric Functions, with efficient algorithms in Computer Algebra Systems. Our ongoing research includes the investigation of geometric connections between partial fractions and reciprocity laws, establishing an algebraic Mittag-Leffler theorem, exploring algebraic generalizations of Ramanujan sums and their applications to deletion correction codes, and completing the commutative algebraic theory for generating functions.
DeepDroughtUAV: Deep learning based estimation of drought area in the Anantapur Cluster using UAV Surveillance
Andhra Pradesh State Council of Higher Education – ₹10 Lakhs (2024-2026)
Principal Investigators: Dr. Naresh Baba M and Dr. S Balasubramanian
The Anantapur district, located in the arid region of Andhra Pradesh, India, is highly susceptible to droughts due to its low and erratic rainfall. Traditional methods of drought monitoring, such as ground surveys and satellite imagery, often lack the resolution and timeliness required for effective intervention. The advancement of Unmanned Aerial Vehicles (UAVs) combined with deep learning techniques presents a novel approach for precise and real-time drought assessment.
Time-Optimal Control Problems and Bifurcation Analysis of Coupled Non-Linear Dynamical Systems with Application to Pest Eradication
National Board for Higher Mathematics (NBHM) – ₹15 Lakhs (2021-2024)
Principal Investigators: Dr. Krishna Kiran Vamsi Dasu
To prove the existence of optimal control and study the characteristics of the optimal trajectory for the time-optimal control problem for additional food provided predator-prey system exhibiting Holling type III and type IV functional response with quality and quantity of additional food as control parameters for mutually interfering predators.
Role and Interactions of Biological Markers in Causation of Type 1/Type 2 Lepra Reactions: A In Vivo Mathematical Modelling with Clinical Validation
The Council of Scientific & Industrial Research (CSIR) – ₹15 Lakhs (2021-2024)
Principal Investigators: Dr. Krishna Kiran Vamsi Dasu
The research aims to identify the possible factors (Biomarkers) and the underlying In vivo mechanism in causation of Type 1 lepra reaction through IFN – pathway and Interleukin 4 pathway, and determine and quantify the relationship between identified biomarkers and occurrence of lepra reactions. We will then test the relationship identified above through the pilot clinical validation.
Insurance Fraud Classifier for Health Insurance – CAS Individual Grants Competition 2022
Casualty Actuarial Society, USA – ₹14 Lakhs (2022-2024)
Principal Investigators: Prof. Pallav Kumar Baruah and Sri Sathya Sai Baba Mudigonda
To publish a journal research paper regarding creating a tool for insurance fraud detection using machine learning and deep learning models. The tool is intended to augment any organizations current fraud detection solution, giving ability to keep pace with the rapidly changing fraud environment, while minimizing costs and increasing profitability.
Doctoral Research Scholars
Sri Lalith Srikanth Chintalapati
Novel Affinity measures for Spectral clustering
Supervisor: Dr. R Raghunatha Sarma
Sri Subramaniyan M
Data Mining in Healthcare
Supervisor: Dr. R Raghunatha Sarma
Sri Rahul Raju Pattar
Micro Local Analysis for Pseudo Differential Operators
Supervisor: Dr. N Uday Kiran
Sri V Sai Raam
Interpretable Deep Learning
Supervisors: Dr. R Raghunatha Sarma and Dr. S Balasubramanian
Sri Ananth V S
Differential Equations, Mathematical Modeling of Ecological Problems
Supervisor: Dr. Krishna Kiran Vamsi Dasu
Sri Hirak Doshi
Mathematical Aspects of Optical Flow Computation
Supervisor: Dr. N Uday Kiran
Miss Kaluri Suseela Padma Sowndarya
Graph Theory
Supervisor: Dr. (Ms.) Y Lakshmi Naidu
Sri Bishal Chhetri
Mathematical Modelling of Infectious Diseases
Supervisor: Dr. Krishna Kiran Vamsi Dasu
Sri S R Pranav Sai
Actuarial Science: General Insurance
Supervisor: Dr. Pallav Kumar Baruah
Sri Rohan Yashraj Gupta
Fraud Detection and Prevention in Insurance
Supervisor: Dr. Pallav Kumar Baruah
Sri Rahul Poddar
Study of curvatures on manifolds with Applications to Machine Learning
Supervisor: Dr. S Balasubramaniam