The Hitchhikers Guide to MTech@CSE@IITB Soumen Chakrabarti Faculty Advisor
The big picture, first year § Semester 1 (Fall 2006) • • Heavy! 3 Elective courses (3*6 credits) Need discipline, Software Lab (4 credits) time management Seminar (4 credits) Communication skills (pass/fail) § Semester 2 (Spring 2007) • • Mood Indigo, Tech Fest, PAF, … 4 Electives (4*6 credits), mini-project? 1 Institute elective (6 credits) Fix MTech projects (MTP) by approx middle of semester Major Time Pass 2
The big picture, second year § Summer 2007 • MTP 1 (22 credits) viva end of July § Semester 3 (Fall 2007) • 2 Elective courses (2*6 credits) • MTP 2 (28 credits) • Pre-placement, interviews, … If this is not keeping you busy, you are in trouble § Semester 4 (Spring 2008) • Mood Indigo, Tech Fest, PAF, … • MTP 3 (40 credits) viva mid-end July § MTP: 90 credits, courses: ~68 § Minimum CC grade to remain in program 3
Lifelines: Do not hesitate to… § Look foolish if necessary • Can’t beat your faculty advisor at that! § Ask for help • Solve the problem vs. appear more self-reliant § § § Give your best (your finest years!) Be honest with everyone, all the time Demand that academics be fun Eat well, sleep 7 h, exercise, no matter what Make friends, balance work and life Develop long-term interests and career goals 4
Facilities § Carry your ID card with you at all times § CSE: labs, servers, accounts, classrooms • At the moment spread across many buildings • HQ in EE annex, lectures in Math and KRe. SIT, some groups in Math basement § Computer Center (“CC”) • Institute-level accounts, access, software, email, file server etc. § Other meeting places for coursework • P. C. Saxena Auditorium (a. k. a. “LT”), Girish Gaitonde (“GG”) building, “convo hall” § “Main Building” for administrative paperwork 5
Registration § CC has given you “LDAP” login Ids • Course registration, personal data update, IIT’s central Web proxies, email routing § Right now, some faculty members will describe their research areas and courses they teach § After that, you will use your CC-assigned logins to register for courses • CSE does not have formal “specializations” • You probably want to pick 1— 2 target areas informally 6
Which courses? § Generally MTech/Ph. D students pick “CS 6 xx” or “CS 7 xx” courses § Can also take IT 6 xx, IT 7 xx, EE 6 xx, EE 7 xx § But if you are keen on taking a “CS 4 xx” course talk to the instructor § A course runs in a “slot” that determines lecture hours and exam times § Cannot enroll for more than one course in any slot § http: //www. cse. iitb. ac. in/page 141 7
Seminar and project allocation § Faculty members publish topics and short descriptions § Students express preferences, talk to faculty members § First round of matching based on preference § Completed at some deadline § “Forced matching” for the rest soon after § Students may benefit from continuity from seminar to project § But not required by dept policy 8
Some CSE courses this semester § § Some courses have prerequisites Some lectures are in the evening Also check for KRe. SIT, EE course offerings Deadline for add/drop/mod 4 AUG 9
Broad areas (incomplete) § AI, machine learning, data mining • pb, gn, soumen § Operating systems, performance analysis • dmd, varsha § Databases and information management • krithi, sudarsha, nls, soumen § Formal verification • supratik, siva, krishnas § Graphics, computer vision • sharat, sohoni 10
Broad areas (still incomplete) § Natural language processing • pb § Networking and Internet technologies • siva, varsha, krithi, soumen § Programming languages, compilers, object oriented languages • uday, as, sb, dmd, rkj § Theoretical computer science • sundar, aad, ranade, sohoni, ketan 11
Tentative schedule 12
Intro to specific faculty members
Pushpak Bhattacharyya § Areas of research • Natural language processing, machine translation, machine learning, information extraction § Course this semester • CS 623 (Intro to Neural Nets) § Projects • Lab for Intelligent Systems • Cross Language Information Retrieval and Machine Translation § Lab: CFILT (Math basement) 14
Soumen Chakrabarti § CS 705 in Autumn – Statistical foundations of machine learning (Mtech 1 encouraged!) § CS 610 in Spring – Web search and mining (depends significantly on CS 705) § Searching using types and relations • Searching in entity-relation graphs (with Prof. Sudarshan), learning ranking functions, models for text and the Web graph § Web monitoring and page analysis for mobile networks (with Prof. Ramamritham) • Semi-connected Web view tuned to user profiles 15
Krithi Ramamritham § Course this semester: IT 625, Information and Communication Technologies For Socio. Economic Development § Research areas • Query processing and communication in sensor networks • Monitoring dynamic content (structured and textual) through unreliable networks • Databases for hand-held devices that use flash memory § Labs/Projects: Developmental Informatics Lab, Lab for Intelligent Systems, … 16
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